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25,849 просмотров • 7 месяцев назад •via X (Twitter)

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Someone told me her LLC was approved before she finished her second coffee. I thought she was exaggerating. Then I tried it. 20 minutes. $20. Company done. The legal world has been charging 500 to 2,000+ for something that should've been automated years ago. Lawyers going back and forth. Confusing government portals. Hidden fees everywhere. Getting charged extra for basic things like registered agent and mail forwarding. Lovie.co launched to put an end to all that. It's not a form you fill out. It's a conversation. You describe what you're building. Lovie suggests the right company type. Picks the best state. Prepares all the documents. Explains everything in normal words. Submits it to the state. Helps with your EIN from the IRS. Sets up your registered agent. Starts tracking compliance deadlines. All for $20 a month. Here's what's included: → Formation paperwork for whatever you need — LLC, C-Corp, etc. → State filing fees covered → EIN application help → 3 years of registered agent service → Digital mail scanning and forwarding → Compliance tracking so state deadlines don't sneak up on you → All future products free — banking, invoicing, bookkeeping, payments Their comparison page tells you everything. Stripe Atlas gives you an agent for one year, no mail service. LegalZoom wants 249 a year for the agent,20 a month for mail, extra for EIN. Doola locks you into annual billing and charges more for bookkeeping. Clerky doesn't do agent or mail or ongoing support. Lovie just includes it all. One price. No surprises. Launching today. Used by founders, freelancers, agency owners, ecommerce folks, and people outside the US who want a Delaware company. And check out the product hunt launch here: 👇 Drop "LOVIE" below. I'll send you the link. Free to start. No credit card. ♻️ Repost for the friend who's been saying "I should really form an LLC" for six months straight.
1:41

Someone told me her LLC was approved before she finished her second coffee. I thought she was exaggerating. Then I tried it. 20 minutes. $20. Company done. The legal world has been charging 500 to 2,000+ for something that should've been automated years ago. Lawyers going back and forth. Confusing government portals. Hidden fees everywhere. Getting charged extra for basic things like registered agent and mail forwarding. Lovie.co launched to put an end to all that. It's not a form you fill out. It's a conversation. You describe what you're building. Lovie suggests the right company type. Picks the best state. Prepares all the documents. Explains everything in normal words. Submits it to the state. Helps with your EIN from the IRS. Sets up your registered agent. Starts tracking compliance deadlines. All for $20 a month. Here's what's included: → Formation paperwork for whatever you need — LLC, C-Corp, etc. → State filing fees covered → EIN application help → 3 years of registered agent service → Digital mail scanning and forwarding → Compliance tracking so state deadlines don't sneak up on you → All future products free — banking, invoicing, bookkeeping, payments Their comparison page tells you everything. Stripe Atlas gives you an agent for one year, no mail service. LegalZoom wants 249 a year for the agent,20 a month for mail, extra for EIN. Doola locks you into annual billing and charges more for bookkeeping. Clerky doesn't do agent or mail or ongoing support. Lovie just includes it all. One price. No surprises. Launching today. Used by founders, freelancers, agency owners, ecommerce folks, and people outside the US who want a Delaware company. And check out the product hunt launch here: 👇 Drop "LOVIE" below. I'll send you the link. Free to start. No credit card. ♻️ Repost for the friend who's been saying "I should really form an LLC" for six months straight.

Anuj

14,395 просмотров • 4 месяцев назад

Local AI 101: open models, Hugging Face, and businesses to build (38 min masterclass) I still think cloud AI is the default for most things, and honestly it should be, the frontier models are the strongest and easiest to use. But something shifted in the last 4-5 months. You can now run genuinely good open models directly on your own laptop, or even your phone. And once you actually try it, it changes how you think about what AI is even for. LOCAL AI, CLEARLY EXPLAINED: 1. The model is the brain doing the thinking. Gemma, Llama, Mistral, and Qwen are the main families, and each is better at different things, some at reasoning, some at coding, some small enough to run on a phone. 2. Hugging Face is the warehouse where you find them. You go there to see what each model is good at, check the license, and grab the compressed versions that run on a normal computer. 3. The software is what runs the model on your machine. Start with LM Studio if you're not technical, it feels like a normal app where you search, download, and start chatting. Ollama is the one you reach for when you want to plug a model into your own apps. 4. The workflow is the actual product you build on top of it all. That's what I'm ideating around for some businesses to create. I think local AI just made a specific kind of business way easier to start. Find an industry that: 1. Sits on sensitive data they'd never paste into ChatGPT 2. Does the same review over and over 3. Runs on software from 2003 Then build a local AI tool that does that review on their own machine, so the data never leaves the building! Take home health agencies. Nurses write visit notes all day, and if a note is missing a detail, the billing gets denied or the audit flags it. Here's how I'd start: 1. Find 5 small agencies. Offer to review a batch of their notes for them. 2. Run the notes through Gemma locally (free, private, no cloud). Read every output yourself. 3. Write down the 20 issues that keep showing up: missing vitals, vague med changes, notes that don't support the billed level. 4. That list of 20 is your checklist. The checklist is the product. 5. Turn it into a local desktop app that flags those 20 things before a note gets submitted. You just went from a service anyone could offer to a product nobody else has, and you learned exactly what to build by doing the work by hand first. Same recipe works for restoration contractors (draft the damage report on-site before the tech leaves) and wealth advisors (catch the compliance landmine in a client email before it sends). Basically the framework is sensitive data, repeated review, ancient software. I think there are tons of businesses like this! Almost none of it clicked for me until I actually started using local AI. So if you take one thing from this, go run a model on your own machine once. Also a fun thing to try with your friends. Feel free to send this to a friend. The episode is live for free on The Startup Ideas Podcast (SIP) 🧃 (thanks to Google for sponsoring today's episode and supporting local AI) I feel like local AI one of those things you need to try for it to really click. Run one model on your own machine and you'll see what I mean! I go way deeper in the full 38 minute masterclass, the models, the setup, and the businesses to build. Link below. LINK TO WATCH: OR WATCH BELOW ON X What do you think of local AI?
38:45

Local AI 101: open models, Hugging Face, and businesses to build (38 min masterclass) I still think cloud AI is the default for most things, and honestly it should be, the frontier models are the strongest and easiest to use. But something shifted in the last 4-5 months. You can now run genuinely good open models directly on your own laptop, or even your phone. And once you actually try it, it changes how you think about what AI is even for. LOCAL AI, CLEARLY EXPLAINED: 1. The model is the brain doing the thinking. Gemma, Llama, Mistral, and Qwen are the main families, and each is better at different things, some at reasoning, some at coding, some small enough to run on a phone. 2. Hugging Face is the warehouse where you find them. You go there to see what each model is good at, check the license, and grab the compressed versions that run on a normal computer. 3. The software is what runs the model on your machine. Start with LM Studio if you're not technical, it feels like a normal app where you search, download, and start chatting. Ollama is the one you reach for when you want to plug a model into your own apps. 4. The workflow is the actual product you build on top of it all. That's what I'm ideating around for some businesses to create. I think local AI just made a specific kind of business way easier to start. Find an industry that: 1. Sits on sensitive data they'd never paste into ChatGPT 2. Does the same review over and over 3. Runs on software from 2003 Then build a local AI tool that does that review on their own machine, so the data never leaves the building! Take home health agencies. Nurses write visit notes all day, and if a note is missing a detail, the billing gets denied or the audit flags it. Here's how I'd start: 1. Find 5 small agencies. Offer to review a batch of their notes for them. 2. Run the notes through Gemma locally (free, private, no cloud). Read every output yourself. 3. Write down the 20 issues that keep showing up: missing vitals, vague med changes, notes that don't support the billed level. 4. That list of 20 is your checklist. The checklist is the product. 5. Turn it into a local desktop app that flags those 20 things before a note gets submitted. You just went from a service anyone could offer to a product nobody else has, and you learned exactly what to build by doing the work by hand first. Same recipe works for restoration contractors (draft the damage report on-site before the tech leaves) and wealth advisors (catch the compliance landmine in a client email before it sends). Basically the framework is sensitive data, repeated review, ancient software. I think there are tons of businesses like this! Almost none of it clicked for me until I actually started using local AI. So if you take one thing from this, go run a model on your own machine once. Also a fun thing to try with your friends. Feel free to send this to a friend. The episode is live for free on The Startup Ideas Podcast (SIP) 🧃 (thanks to Google for sponsoring today's episode and supporting local AI) I feel like local AI one of those things you need to try for it to really click. Run one model on your own machine and you'll see what I mean! I go way deeper in the full 38 minute masterclass, the models, the setup, and the businesses to build. Link below. LINK TO WATCH: OR WATCH BELOW ON X What do you think of local AI?

GREG ISENBERG

29,524 просмотров • 5 дней назад

This is a better and more challenging demonstration of my AI music theory cli tool and skills library. I told the agent only that I wanted to take the traditional Irish song, Clare's Dragoons, and to create a piano rendition of the main verse and chorus followed by a series of variations in the style of Mozart's famous "Twinkle Star Variations" (K. 265/300e), and that it should spawn Codex with the skills and prompt it to do that for me and to invoke any relevant skills in the system. This was in Codex with GPT-6 Astra xhigh and with the workspace loaded up with just the 320 skills that are part of the music AI skills library, and with the mtdt (music_theory_data_tool) cli tool available for use by the agent. The agent was able to find suitable sheet music for the Clare's Dragoons song and then used mtdt to convert that into its internal representation form, which makes it easy for the agent to work on the music and to convert it to any other desired format (like a PDF engraving, midi files, etc). It then researched the Twinkle Star variations and used various skills to compose and review and refine the variations. Why do I think this task is more demanding than writing a fugue in the style of Bach? Well, for one, it's a lot more structured, so you have much less flexibility and room for "artistic license." Ultimately, you have to render the original tune accurately, and then the variations have to sound similar enough to the original tune while introducing various creative musical manipulations to be interesting. It's pretty challenging to balance those two priorities: it's easy to lose the thread of the original tune, and easy to overcompensate for that and end up with something that only slightly tweaks one or two aspects of the original. Now, this is obviously not at the level of Mozart, but I think it's not that bad and will likely get much better over the next year as I improve the skills and tool and especially as models get better and more multimodal, so they can "listen" to the results in addition to reading the score. I'll provide the full prompt that the "controller" agent wrote for the agent that actually created the variations in a reply to this post. You can also see in the screenshots in this post the massive number of intermediate working files and artifacts created during the process, which gives a ton of visibility into how the agent did its work and reached its decisions. Not a black box! And I can assure you that I didn't mess with anything at all: this entire process was automated from start to finish and you're seeing the exact end product the agent produced without any revisions or feedback coming from me or any other human (the controller agent did ask for some revisions from the worker agent, which you can see in the final pic in this post). I'm trying to think of some other fun demonstrations. Maybe taking famous video game music (Mario 2? Ocarina of Time?) and making a version in the style of Schumann or Rachmaninoff. I'm open to suggestions!
7:32

This is a better and more challenging demonstration of my AI music theory cli tool and skills library. I told the agent only that I wanted to take the traditional Irish song, Clare's Dragoons, and to create a piano rendition of the main verse and chorus followed by a series of variations in the style of Mozart's famous "Twinkle Star Variations" (K. 265/300e), and that it should spawn Codex with the skills and prompt it to do that for me and to invoke any relevant skills in the system. This was in Codex with GPT-6 Astra xhigh and with the workspace loaded up with just the 320 skills that are part of the music AI skills library, and with the mtdt (music_theory_data_tool) cli tool available for use by the agent. The agent was able to find suitable sheet music for the Clare's Dragoons song and then used mtdt to convert that into its internal representation form, which makes it easy for the agent to work on the music and to convert it to any other desired format (like a PDF engraving, midi files, etc). It then researched the Twinkle Star variations and used various skills to compose and review and refine the variations. Why do I think this task is more demanding than writing a fugue in the style of Bach? Well, for one, it's a lot more structured, so you have much less flexibility and room for "artistic license." Ultimately, you have to render the original tune accurately, and then the variations have to sound similar enough to the original tune while introducing various creative musical manipulations to be interesting. It's pretty challenging to balance those two priorities: it's easy to lose the thread of the original tune, and easy to overcompensate for that and end up with something that only slightly tweaks one or two aspects of the original. Now, this is obviously not at the level of Mozart, but I think it's not that bad and will likely get much better over the next year as I improve the skills and tool and especially as models get better and more multimodal, so they can "listen" to the results in addition to reading the score. I'll provide the full prompt that the "controller" agent wrote for the agent that actually created the variations in a reply to this post. You can also see in the screenshots in this post the massive number of intermediate working files and artifacts created during the process, which gives a ton of visibility into how the agent did its work and reached its decisions. Not a black box! And I can assure you that I didn't mess with anything at all: this entire process was automated from start to finish and you're seeing the exact end product the agent produced without any revisions or feedback coming from me or any other human (the controller agent did ask for some revisions from the worker agent, which you can see in the final pic in this post). I'm trying to think of some other fun demonstrations. Maybe taking famous video game music (Mario 2? Ocarina of Time?) and making a version in the style of Schumann or Rachmaninoff. I'm open to suggestions!

Jeffrey Emanuel

11,607 просмотров • 4 дней назад

This is Professor Ellen Rungani, the daughter of the Zimbabwean national hero buried two days ago, Brigadier-General Victor Chikudo Rungani. She is explaining how her father died, three hospitals could not provide him with a mere ventilator. General Victor Chikudo Rungani was 76 years old when he passed away at Mbuya Dorcas Hospital in Harare on April 22. He was honoured with a national hero’s burial at the National Heroes Acre. His wife, Senator Anna Rungani, is a member of the Zimbabwean Parliament under the ruling ZANUPF party, this is no ordinary Zimbabwean family, they are part of the pollical elite class of Zimbabwe. When the general fell ill, he was taken to a military hospital in Harare at Josiah Magama Tongogara Barracks, formerly known as KG6—short for King George VI, after whom the barracks were originally named. The military hospital there was so ill-equipped that it lacked the most basic medical equipment he needed, a ventilator. The military hospital could only provide a nebuliser, something that you and I can buy over the counter in a pharmacy. A nebuliser is a medical device used to administer medication in the form of a mist, which is inhaled into the lungs. It is commonly used for people with respiratory conditions such as asthma and other lung diseases. The general was then taken to Zimbabwe’s largest public health facility, the Parirenyatwa Group of Hospitals, but still, no ventilator was available for him there. He was stuck there for days without a ventilator. He was subsequently taken to Westend Hospital, whose medical resources running into multiple millions of dollars were looted and plundered by government officials, including the President’s spokesman, George Charamba; yet again, no ventilator was found for the general to save his wife. Finally, he was taken to the ZAOGA church-owned Mbuya Dorcas Hospital in Harare’s Waterfalls suburb. By then, it was too late. The general died there simply because the public hospitals had no ventilators for him to use, and as a result, he caught a respiratory infection that probably killed him. When I speak about the importance of equipping public hospitals, it is because moments like this inevitably arise, where people die needlessly. I say these things because these public hospitals serve all of us regardless of political party affiliation or views, Despite being a general, a decorated war veteran and hero, an illustrious soldier and the husband of a senator, Brigadier-General Victor Chikudo Rungani died because Emmerson Mnangagwa has deliberately failed to provide basic medical equipment in public hospitals, due to the corruption he presides over as the Godfather of looting cartels. The NovaVent ventilator costs only US$500, and a standard low end hospital ventilator starts from around US$5,000, yet none was available to save this illustrious war hero and highly decorated general whose wife is a ZANUPF senator. All because Zimbabwe has a corrupt president who does not care about the citizens and only cares about looting public funds and enriching his family and inner circle of his clansmen. Seven years ago, I warned Zimbabweans that the entire country had only seven ventilators, mostly in private hospitals. Nobody in politics and authority listened and did something about my warning. Two years later, after my ominous warning, COVID-19 struck, and the first person to die because there was no ventilator was up-and-coming highly talented broadcaster, Zororo Makamba, who passed away on 23 March 2020. His father, James Makamba, is currently a ZANUPF Member of Parliament representing Mashonaland Central Province. I repeated the same call again a day after Zororo had died. I reminded Zimbabweans that one Range Rover can buy 80 hospital ventilators, which cost US$5,000 each. Instead of hanging their heads in shame, Mnangagwa and his thugs sent me to jail without trial for saying these things. Since then, Mnangagwa’s regime has bought thousands of Range Rovers for his inner circle in government and state-owned enterprises, known in Zimbabwe as parastatals, yet only a US$5,000 ventilator was needed to save the life of the general! Very little has changed since I made my first call to action about equipping public hospitals with ventilators. More Zimbabweans will continue to die, in both high and low places, until Zimbabweans decide that enough is enough and demand and action sanity. Emmerson Mnangagwa and his two deputies, General Constantino Chiwenga and Kembo Mohadi, receive medical treatment abroad when they fall ill. The money they spend on a single hospital check-up in China, India, Dubai or South Africa could equip the military hospital or Parirenyatwa with ventilators and essential medical supplies, but they do not care, because it does not affect them! The stupidity of Zimbabwean leaders lies in their failure to understand that the money they spend on private jets to China, Dubai, India or South Africa looking for healthcare could equip all public hospitals with the very equipment they travel abroad for. They could be treated at home, and so could everyone else, but Mnangagwa doesn’t care at all about these life and death issues. The breathtaking stupidity of ZANUPF leaders, once predicted by Ian Smith and dismissed then as racist ranting, is now confirmed in Zimbabwe to the whole world daily. Now one of their own has died because they could not place a simple ventilator in a military hospital. Forget about public hospitals for us, the Povo, these ZANUPF leaders are so stupid they cannot even equip their own private military hospitals! What a useless and shameless bunch of clueless leaders! Things are so bad in Zimbabwean hospitals that South Africa had to evacuate one of its nationals by helicopter from Zimbabwe last week so they could receive proper yet basic medical attention. The tragic reality is that when I offered to supply this medical equipment to hospitals for free using my international networks and goodwill, the political class ganged up to demonise me, thinking I wanted to enter politics by helping people. To all those who did not understand why it is important to let those of us who have the capacity to equip these hospitals for free, this is your answer. Corrupt rule does not discriminate; it will find you regardless of who you are in society. You could be very wealthy, but if you are involved in a car accident in Murambinda or Tsholotsho, you will need emergency healthcare to stabilise you before being transferred to a hospital for the wealthy. You will not make it, you will die, along with all that money. Only because you didn’t realise the importance of equipping public hospitals for the poor and the ordinary when you still had the power to do so! I am sure you heard from the professor that her father, an illustrious war hero and military man, was taken to the private section of Parirenyatwa Public Hospital. This means that even the private section of this hospital, which used to be well equipped and where important political figures were once treated, has now collapsed too. Zimbabwe’s first post-colonial First Lady, Sally Mugabe, was treated there. The late Vice President Joshua Nkomo was treated there, as was the late Vice President Simon Muzenda. But under Mnangagwa, even the VIP section of this once-great hospital is now dilapidated and can’t provide for something so basic as a ventilator. Mnangagwa is so demented that he steals public money meant for hospitals, and when these high-profile figures die from his negligence and corrupt rule, he spends millions of state money on their funerals and burials. The state money used on the general’s funeral and burial was more than enough to have saved him and many other ordinary Zimbabweans, had the corrupt dictator simply invested in public hospitals. Meanwhile, the past, current and future victims of this man’s negligence are at the forefront of wanting him to continue misruling the country until 2030. Why, then, do we get angry when other nationalities call us stupid? Until Zimbabweans unite to fight this corrupt dictator as one, his political negligence and criminal misrule will continue to kill them one by one. Kuzvitambira kana kusazvitambira (ukuzamukela noma ukungamukeli), the truth remains what it is, factual!
2:51

This is Professor Ellen Rungani, the daughter of the Zimbabwean national hero buried two days ago, Brigadier-General Victor Chikudo Rungani. She is explaining how her father died, three hospitals could not provide him with a mere ventilator. General Victor Chikudo Rungani was 76 years old when he passed away at Mbuya Dorcas Hospital in Harare on April 22. He was honoured with a national hero’s burial at the National Heroes Acre. His wife, Senator Anna Rungani, is a member of the Zimbabwean Parliament under the ruling ZANUPF party, this is no ordinary Zimbabwean family, they are part of the pollical elite class of Zimbabwe. When the general fell ill, he was taken to a military hospital in Harare at Josiah Magama Tongogara Barracks, formerly known as KG6—short for King George VI, after whom the barracks were originally named. The military hospital there was so ill-equipped that it lacked the most basic medical equipment he needed, a ventilator. The military hospital could only provide a nebuliser, something that you and I can buy over the counter in a pharmacy. A nebuliser is a medical device used to administer medication in the form of a mist, which is inhaled into the lungs. It is commonly used for people with respiratory conditions such as asthma and other lung diseases. The general was then taken to Zimbabwe’s largest public health facility, the Parirenyatwa Group of Hospitals, but still, no ventilator was available for him there. He was stuck there for days without a ventilator. He was subsequently taken to Westend Hospital, whose medical resources running into multiple millions of dollars were looted and plundered by government officials, including the President’s spokesman, George Charamba; yet again, no ventilator was found for the general to save his wife. Finally, he was taken to the ZAOGA church-owned Mbuya Dorcas Hospital in Harare’s Waterfalls suburb. By then, it was too late. The general died there simply because the public hospitals had no ventilators for him to use, and as a result, he caught a respiratory infection that probably killed him. When I speak about the importance of equipping public hospitals, it is because moments like this inevitably arise, where people die needlessly. I say these things because these public hospitals serve all of us regardless of political party affiliation or views, Despite being a general, a decorated war veteran and hero, an illustrious soldier and the husband of a senator, Brigadier-General Victor Chikudo Rungani died because Emmerson Mnangagwa has deliberately failed to provide basic medical equipment in public hospitals, due to the corruption he presides over as the Godfather of looting cartels. The NovaVent ventilator costs only US$500, and a standard low end hospital ventilator starts from around US$5,000, yet none was available to save this illustrious war hero and highly decorated general whose wife is a ZANUPF senator. All because Zimbabwe has a corrupt president who does not care about the citizens and only cares about looting public funds and enriching his family and inner circle of his clansmen. Seven years ago, I warned Zimbabweans that the entire country had only seven ventilators, mostly in private hospitals. Nobody in politics and authority listened and did something about my warning. Two years later, after my ominous warning, COVID-19 struck, and the first person to die because there was no ventilator was up-and-coming highly talented broadcaster, Zororo Makamba, who passed away on 23 March 2020. His father, James Makamba, is currently a ZANUPF Member of Parliament representing Mashonaland Central Province. I repeated the same call again a day after Zororo had died. I reminded Zimbabweans that one Range Rover can buy 80 hospital ventilators, which cost US$5,000 each. Instead of hanging their heads in shame, Mnangagwa and his thugs sent me to jail without trial for saying these things. Since then, Mnangagwa’s regime has bought thousands of Range Rovers for his inner circle in government and state-owned enterprises, known in Zimbabwe as parastatals, yet only a US$5,000 ventilator was needed to save the life of the general! Very little has changed since I made my first call to action about equipping public hospitals with ventilators. More Zimbabweans will continue to die, in both high and low places, until Zimbabweans decide that enough is enough and demand and action sanity. Emmerson Mnangagwa and his two deputies, General Constantino Chiwenga and Kembo Mohadi, receive medical treatment abroad when they fall ill. The money they spend on a single hospital check-up in China, India, Dubai or South Africa could equip the military hospital or Parirenyatwa with ventilators and essential medical supplies, but they do not care, because it does not affect them! The stupidity of Zimbabwean leaders lies in their failure to understand that the money they spend on private jets to China, Dubai, India or South Africa looking for healthcare could equip all public hospitals with the very equipment they travel abroad for. They could be treated at home, and so could everyone else, but Mnangagwa doesn’t care at all about these life and death issues. The breathtaking stupidity of ZANUPF leaders, once predicted by Ian Smith and dismissed then as racist ranting, is now confirmed in Zimbabwe to the whole world daily. Now one of their own has died because they could not place a simple ventilator in a military hospital. Forget about public hospitals for us, the Povo, these ZANUPF leaders are so stupid they cannot even equip their own private military hospitals! What a useless and shameless bunch of clueless leaders! Things are so bad in Zimbabwean hospitals that South Africa had to evacuate one of its nationals by helicopter from Zimbabwe last week so they could receive proper yet basic medical attention. The tragic reality is that when I offered to supply this medical equipment to hospitals for free using my international networks and goodwill, the political class ganged up to demonise me, thinking I wanted to enter politics by helping people. To all those who did not understand why it is important to let those of us who have the capacity to equip these hospitals for free, this is your answer. Corrupt rule does not discriminate; it will find you regardless of who you are in society. You could be very wealthy, but if you are involved in a car accident in Murambinda or Tsholotsho, you will need emergency healthcare to stabilise you before being transferred to a hospital for the wealthy. You will not make it, you will die, along with all that money. Only because you didn’t realise the importance of equipping public hospitals for the poor and the ordinary when you still had the power to do so! I am sure you heard from the professor that her father, an illustrious war hero and military man, was taken to the private section of Parirenyatwa Public Hospital. This means that even the private section of this hospital, which used to be well equipped and where important political figures were once treated, has now collapsed too. Zimbabwe’s first post-colonial First Lady, Sally Mugabe, was treated there. The late Vice President Joshua Nkomo was treated there, as was the late Vice President Simon Muzenda. But under Mnangagwa, even the VIP section of this once-great hospital is now dilapidated and can’t provide for something so basic as a ventilator. Mnangagwa is so demented that he steals public money meant for hospitals, and when these high-profile figures die from his negligence and corrupt rule, he spends millions of state money on their funerals and burials. The state money used on the general’s funeral and burial was more than enough to have saved him and many other ordinary Zimbabweans, had the corrupt dictator simply invested in public hospitals. Meanwhile, the past, current and future victims of this man’s negligence are at the forefront of wanting him to continue misruling the country until 2030. Why, then, do we get angry when other nationalities call us stupid? Until Zimbabweans unite to fight this corrupt dictator as one, his political negligence and criminal misrule will continue to kill them one by one. Kuzvitambira kana kusazvitambira (ukuzamukela noma ukungamukeli), the truth remains what it is, factual!

Hopewell Chin’ono

106,192 просмотров • 1 год назад

Elon Musk just described how the entire government operates in a single sentence. Musk: “Paying people to do nothing doesn’t make sense.” Then he told a Milton Friedman story that should terrify every bureaucrat on the payroll. Friedman watched workers digging ditches with shovels. He suggested they use excavators instead. Someone pushed back. “But then we’re going to lose a lot of jobs.” Musk: “Friedman says, well, in that case, why don’t you have them use teaspoons?” One sentence. That’s all it took to gut the entire logic of modern government. The teaspoon is not a punchline. It is the actual policy. Every agency that would cease to exist if it actually solved the problem it was created for. Every department that measures success by headcount instead of output. Every approval that routes through nine desks before someone can say yes. Teaspoons. The system doesn’t want excavators. Excavators finish the job. And a finished job is the one thing the system can’t afford. So it hands you a teaspoon. Calls it a career. Gives you a pension for never asking why the ditch took forty years. But this isn’t about laziness. It’s about control. A person digging with a teaspoon doesn’t have time to build something better. Doesn’t have the energy to question the plan. Doesn’t have a thought left to ask if the ditch even needed digging. Busy people don’t ask dangerous questions. That’s the point. The economy doesn’t run on productivity. It runs on the appearance of productivity. Millions of people sit at desks right now doing work a single script could replace by morning. They know it. Their managers know it. The people who sign their budgets know it. But the teaspoon stays in their hand. Because the moment you hand someone an excavator, they finish by noon. And a person with a free afternoon starts thinking. Starts building. Starts wondering why they needed permission to dig in the first place. That’s the thing the system can’t survive. Not unemployment. Free time. Musk didn’t tell a joke on Rogan. He described the longest con in modern governance. Keep them digging. Keep them busy. Keep the teaspoon in their hand so they never look up long enough to see the ditch was pointless from the start. Friedman told that story sixty years ago. He meant it as a warning. The system heard every word. It just made sure everyone kept calling it a joke so no one would recognize it as a confession.
1:01

Elon Musk just described how the entire government operates in a single sentence. Musk: “Paying people to do nothing doesn’t make sense.” Then he told a Milton Friedman story that should terrify every bureaucrat on the payroll. Friedman watched workers digging ditches with shovels. He suggested they use excavators instead. Someone pushed back. “But then we’re going to lose a lot of jobs.” Musk: “Friedman says, well, in that case, why don’t you have them use teaspoons?” One sentence. That’s all it took to gut the entire logic of modern government. The teaspoon is not a punchline. It is the actual policy. Every agency that would cease to exist if it actually solved the problem it was created for. Every department that measures success by headcount instead of output. Every approval that routes through nine desks before someone can say yes. Teaspoons. The system doesn’t want excavators. Excavators finish the job. And a finished job is the one thing the system can’t afford. So it hands you a teaspoon. Calls it a career. Gives you a pension for never asking why the ditch took forty years. But this isn’t about laziness. It’s about control. A person digging with a teaspoon doesn’t have time to build something better. Doesn’t have the energy to question the plan. Doesn’t have a thought left to ask if the ditch even needed digging. Busy people don’t ask dangerous questions. That’s the point. The economy doesn’t run on productivity. It runs on the appearance of productivity. Millions of people sit at desks right now doing work a single script could replace by morning. They know it. Their managers know it. The people who sign their budgets know it. But the teaspoon stays in their hand. Because the moment you hand someone an excavator, they finish by noon. And a person with a free afternoon starts thinking. Starts building. Starts wondering why they needed permission to dig in the first place. That’s the thing the system can’t survive. Not unemployment. Free time. Musk didn’t tell a joke on Rogan. He described the longest con in modern governance. Keep them digging. Keep them busy. Keep the teaspoon in their hand so they never look up long enough to see the ditch was pointless from the start. Friedman told that story sixty years ago. He meant it as a warning. The system heard every word. It just made sure everyone kept calling it a joke so no one would recognize it as a confession.

Dustin

348,331 просмотров • 3 месяцев назад

Busy day today! Today ~16,000 people flew in my free-to-play flight game made with AI 💸 Revenue update for after 10 days: +💬 19x Blimps sold at various prices = $38,000/mo + ✈️ 12x F16's sold @ $29.99 = ~$360 += $38,360/mo In-game ads are now $5,000/mo, if you want one, get them here: As I said b4, I will keep doubling the in-game ads price because I don't want the world to get too busy with ads and have to keep it exclusive!.Next $10K/mo then $20K/mo until we run out of people who want to buy them :D Today was busy mostly with installing all the sponsor ads in the game, I fixed: ✅ Playable now on low FPS ✅ Improved tank driving and turret aiming ✅ Improved rate of fire because it was slowing down when shooting ✅ Added proper refueling to 100% health if you land back at spawn point and make a full stop ✅ Installed lots of ads for all the sponsors (which was a lot of work because I didn't just wanna add blimps everywhere, I wanted some fun stuff for each sponsor) ✅ Added functioning radar on aircraft carrier (see vid) ✅ Added thank you to all sponsors on start (not load because it will never have load screens :D) screen Video games are definitely A LOT harder in many ways than regular apps, I have a new found respect for video game devs. The to-do list is about 10x to 100x as big as any SaaS app I've ever made! Also because it's so creative, the possibilities are just endless. For example Marc Köhlbrugge suggests "add a tank", I add a tank but then next I need to add a turret aiming system and next I get more ideas "let's add lots of vehicles" then "let's add walking mode". It's really fun but I get it better now how video games are infinity rabbit holes A lot of people ridicule my little game rn, and it's not great or perfect or anything yet I agree, but people play it and seem to have fun and I really do wanna make a cool flight game. I'm happy it makes some money already in its first month, which gives me more motivation to work on it! Next: [ ] 5-min or 10-min like rounds so scores reset [ ] interpolation for smooth planes (I know I know) [ ] I will try CannonJS real physics model library
0:58

Busy day today! Today ~16,000 people flew in my free-to-play flight game made with AI 💸 Revenue update for after 10 days: +💬 19x Blimps sold at various prices = $38,000/mo + ✈️ 12x F16's sold @ $29.99 = ~$360 += $38,360/mo In-game ads are now $5,000/mo, if you want one, get them here: As I said b4, I will keep doubling the in-game ads price because I don't want the world to get too busy with ads and have to keep it exclusive!.Next $10K/mo then $20K/mo until we run out of people who want to buy them :D Today was busy mostly with installing all the sponsor ads in the game, I fixed: ✅ Playable now on low FPS ✅ Improved tank driving and turret aiming ✅ Improved rate of fire because it was slowing down when shooting ✅ Added proper refueling to 100% health if you land back at spawn point and make a full stop ✅ Installed lots of ads for all the sponsors (which was a lot of work because I didn't just wanna add blimps everywhere, I wanted some fun stuff for each sponsor) ✅ Added functioning radar on aircraft carrier (see vid) ✅ Added thank you to all sponsors on start (not load because it will never have load screens :D) screen Video games are definitely A LOT harder in many ways than regular apps, I have a new found respect for video game devs. The to-do list is about 10x to 100x as big as any SaaS app I've ever made! Also because it's so creative, the possibilities are just endless. For example Marc Köhlbrugge suggests "add a tank", I add a tank but then next I need to add a turret aiming system and next I get more ideas "let's add lots of vehicles" then "let's add walking mode". It's really fun but I get it better now how video games are infinity rabbit holes A lot of people ridicule my little game rn, and it's not great or perfect or anything yet I agree, but people play it and seem to have fun and I really do wanna make a cool flight game. I'm happy it makes some money already in its first month, which gives me more motivation to work on it! Next: [ ] 5-min or 10-min like rounds so scores reset [ ] interpolation for smooth planes (I know I know) [ ] I will try CannonJS real physics model library

@levelsio

1,731,949 просмотров • 1 год назад

Jeff Bezos just told you where all of Earth’s factories are going. Off the planet. Bezos: “If we want to keep growing our civilization and using more energy per person, we’re eventually going to have to move all of our heavy industry off Earth.” Not a thought experiment. An engineering conclusion. One he has held since childhood. Decades on the same problem. The same answer every time. Earth is too small. Not too small for today. Too small for what today becomes. Every year the species consumes more energy. More compute. More materials. More of everything. The curve does not flatten. It never has. It never will. The planet has a hard ceiling. Fixed energy. Fixed land. Fixed resources. A closed system with a growing appetite. You do not solve that by shrinking the appetite. You solve it by expanding the system. Bezos: “We have unlimited energy in space and unlimited material resources in space.” Unlimited. Not abundant. Not plentiful. Unlimited. The Sun outputs more energy in one second than humanity could burn in a million years. The asteroid belt holds more raw material than every mine ever dug on Earth. The Moon alone carries enough helium-3 and rare earth minerals to fuel industries that do not yet have names. All of it sitting there. Untouched. While nations bleed each other over the scraps. Bezos: “We can start to build factories in space. We can start to build data centers in space.” Factories that produce zero pollution on Earth. Data centers that draw zero power from the grid. Heavy industry that generates zero waste in the atmosphere. Not because the waste disappears. Because the waste happens somewhere it does not matter. Bezos: “This planet is so beautiful and so unusual. This is the one that we’re going to want to protect. There’s no planet B.” The environmentalists and the industrialists have been fighting the same war for fifty years. Grow or protect. Build or conserve. Economy or ecology. Bezos is telling you the war was always false. You do not choose between growth and preservation. You move the growth off-world and the preservation happens automatically. Earth becomes the residential zone. The garden. The one place where biology gets to breathe. Space becomes the factory floor. The power plant. The data center. The refinery. Every smokestack. Every cooling tower. Every server farm drawing gigawatts from the grid. All of it belongs in the vacuum where energy is free and there is no ecosystem to damage. Bezos: “I don’t know how soon it will happen. It’s a job that I won’t finish. Probably my children’s children won’t finish.” He is building something he will never see completed. That is not a business plan. That is a cathedral. The kind of project that takes generations. Where the person who lays the foundation never stands in the finished building. Most founders build for an exit. Bezos is building for a timeline that outlives his grandchildren. The interviewer called it fantastical. Bezos had one response. Bezos: “Go back in time a hundred years and show somebody your iPhone.” Everything that exists today was once fantastical. Flight. Satellites. The internet. A phone carrying the sum of human knowledge in your pocket. Every single one was impossible until the year it was not. Orbital factories sound like science fiction the same way video calls sounded like science fiction in 1950. The pattern never changes. Someone describes the future. Everyone calls it crazy. Then it ships. Then no one can explain what came before. Bezos is not guessing. He is reading the same pattern that has held every single time. And betting his life that this one is no different.
1:52

Jeff Bezos just told you where all of Earth’s factories are going. Off the planet. Bezos: “If we want to keep growing our civilization and using more energy per person, we’re eventually going to have to move all of our heavy industry off Earth.” Not a thought experiment. An engineering conclusion. One he has held since childhood. Decades on the same problem. The same answer every time. Earth is too small. Not too small for today. Too small for what today becomes. Every year the species consumes more energy. More compute. More materials. More of everything. The curve does not flatten. It never has. It never will. The planet has a hard ceiling. Fixed energy. Fixed land. Fixed resources. A closed system with a growing appetite. You do not solve that by shrinking the appetite. You solve it by expanding the system. Bezos: “We have unlimited energy in space and unlimited material resources in space.” Unlimited. Not abundant. Not plentiful. Unlimited. The Sun outputs more energy in one second than humanity could burn in a million years. The asteroid belt holds more raw material than every mine ever dug on Earth. The Moon alone carries enough helium-3 and rare earth minerals to fuel industries that do not yet have names. All of it sitting there. Untouched. While nations bleed each other over the scraps. Bezos: “We can start to build factories in space. We can start to build data centers in space.” Factories that produce zero pollution on Earth. Data centers that draw zero power from the grid. Heavy industry that generates zero waste in the atmosphere. Not because the waste disappears. Because the waste happens somewhere it does not matter. Bezos: “This planet is so beautiful and so unusual. This is the one that we’re going to want to protect. There’s no planet B.” The environmentalists and the industrialists have been fighting the same war for fifty years. Grow or protect. Build or conserve. Economy or ecology. Bezos is telling you the war was always false. You do not choose between growth and preservation. You move the growth off-world and the preservation happens automatically. Earth becomes the residential zone. The garden. The one place where biology gets to breathe. Space becomes the factory floor. The power plant. The data center. The refinery. Every smokestack. Every cooling tower. Every server farm drawing gigawatts from the grid. All of it belongs in the vacuum where energy is free and there is no ecosystem to damage. Bezos: “I don’t know how soon it will happen. It’s a job that I won’t finish. Probably my children’s children won’t finish.” He is building something he will never see completed. That is not a business plan. That is a cathedral. The kind of project that takes generations. Where the person who lays the foundation never stands in the finished building. Most founders build for an exit. Bezos is building for a timeline that outlives his grandchildren. The interviewer called it fantastical. Bezos had one response. Bezos: “Go back in time a hundred years and show somebody your iPhone.” Everything that exists today was once fantastical. Flight. Satellites. The internet. A phone carrying the sum of human knowledge in your pocket. Every single one was impossible until the year it was not. Orbital factories sound like science fiction the same way video calls sounded like science fiction in 1950. The pattern never changes. Someone describes the future. Everyone calls it crazy. Then it ships. Then no one can explain what came before. Bezos is not guessing. He is reading the same pattern that has held every single time. And betting his life that this one is no different.

Dustin

30,201 просмотров • 5 месяцев назад

👑For interfans, For interfans and For interfans🌪️ Hey interfans. Let’s get ready to watch the series live together. 🥳 🎯Don't forget, the best thing we can do as interfans is to focus all our energy on the official live broadcast, and then head straight over to iQIYI right after to catch the uncut. ✨To give you a clearer picture, check out the photos and clips attached. 🌻Here is the breakdown of my test run using 5 different devices to watch the live stream: 1⃣Google TV: BugabooTV app + VPN [Paid] 2⃣Samsung Tablet: TrueID app vs. BugabooTV app + VPN [Free] (Clip) 3⃣iPhone: BugabooTV app vs. TrueID web + VPN [Paid] (Clip) 4⃣Windows PC: TrueID web + VPN [Paid] 5⃣Macbook: TrueID web + VPN [Paid] 📢Just a quick heads-up: This is just my personal test and opinion. 🙌 My Recommendation: If you can access BugabooTV whether it's through their website, app, or the official Ch7HD website without any issues, please make that your number one choice. However, if you're struggling to get in, facing slow loading speeds, or the system keeps crashing, switching over to TrueID is a great alternative. And once the live show ends, let’s all move over to iQIYI together. ⚠️ Important Note: Please avoid watching through any other channels not mentioned above. They won't help boost the official live viewership stats at all. 💥If you are living outside of Thailand... you WILL need a VPN to watch via BugabooTV, CH7HD, or TrueID. The only exception is iQIYI (no VPN needed). 📥 App Download Links 🍎App Store (iOS) - BugabooTV : - CH7HD : - TrueID : - iQIYI : 🤖Play Store (Android) - BugabooTV : - CH7HD : - TrueID : - iQIYI : #เสน่หาวาโย #4Elements #บ้านวาทินวณิช #ฟรีนเบค #FreenBecky #srchafreen #beckysangels‌ #WikiFreenBecky
1:15

👑For interfans, For interfans and For interfans🌪️ Hey interfans. Let’s get ready to watch the series live together. 🥳 🎯Don't forget, the best thing we can do as interfans is to focus all our energy on the official live broadcast, and then head straight over to iQIYI right after to catch the uncut. ✨To give you a clearer picture, check out the photos and clips attached. 🌻Here is the breakdown of my test run using 5 different devices to watch the live stream: 1⃣Google TV: BugabooTV app + VPN [Paid] 2⃣Samsung Tablet: TrueID app vs. BugabooTV app + VPN [Free] (Clip) 3⃣iPhone: BugabooTV app vs. TrueID web + VPN [Paid] (Clip) 4⃣Windows PC: TrueID web + VPN [Paid] 5⃣Macbook: TrueID web + VPN [Paid] 📢Just a quick heads-up: This is just my personal test and opinion. 🙌 My Recommendation: If you can access BugabooTV whether it's through their website, app, or the official Ch7HD website without any issues, please make that your number one choice. However, if you're struggling to get in, facing slow loading speeds, or the system keeps crashing, switching over to TrueID is a great alternative. And once the live show ends, let’s all move over to iQIYI together. ⚠️ Important Note: Please avoid watching through any other channels not mentioned above. They won't help boost the official live viewership stats at all. 💥If you are living outside of Thailand... you WILL need a VPN to watch via BugabooTV, CH7HD, or TrueID. The only exception is iQIYI (no VPN needed). 📥 App Download Links 🍎App Store (iOS) - BugabooTV : - CH7HD : - TrueID : - iQIYI : 🤖Play Store (Android) - BugabooTV : - CH7HD : - TrueID : - iQIYI : #เสน่หาวาโย #4Elements #บ้านวาทินวณิช #ฟรีนเบค #FreenBecky #srchafreen #beckysangels‌ #WikiFreenBecky

🌵🏜FreenBecky's World🏜🌵

18,283 просмотров • 3 месяцев назад

Don't Buy a Mac Mini for Clawdbot: The Secret $10,000 Architecture That Costs You Nothing clawdbot might be the reason you feel like you need a ten thousand dollar computer right now but i am about to show you why that fomo is going to leave you broke. if you have been watching everyone rush out to buy mac minis and mac studios just to run open claw or some local models you are witnessing a massive transfer of wealth from your pocket to apple for no reason. there is a specific setup i use that costs almost nothing and keeps my main machine safe from whatever these autonomous agents are doing. if you stick with me i will walk you through the exact architecture of a professional trading system that handles the heavy lifting without you needing to drop a single rack on hardware most people are scared of running these bots on their main computer because they don't want an agent messing with their personal files or browser sessions. instead of buying a second mac mini for six hundred dollars you can just go to the top left of your screen and create a brand new user profile. this acts like a completely isolated sandbox where you can install all your trading tools and agents without them ever seeing your main data. it is essentially like getting a free computer for the price of five minutes of clicking around your settings but what if you aren't on a mac or you need to access your system while you are traveling without carrying three laptops in your backpack. this is where the first loop of professional automation starts to close because i use something called chrome remote desktop to bridge the gap. this allows me to leave a dedicated machine running in a safe place while i access the full desktop environment from a tablet or a cheap laptop anywhere in the world. it solves the mobility issue but it still doesn't solve the problem of those massive ten thousand dollar price tags for high end mac pros if you are a pc user or just someone who doesn't want to own physical hardware yet you should look into a windows vps through a provider like contabo. most developers will tell you to use a linux terminal but if you aren't a coder yet you need a visual interface you can actually see. getting a windows server allows you to log in and see a desktop just like your home computer for about fifteen dollars a month. i usually recommend at least twelve gigabytes of ram to keep things from getting janky when you are running multiple browser windows and agents at once now you might be thinking that the whole point of the big hardware was to run local models like kimi or glm to save on api costs. i spent years thinking i had to own the machines myself and i even spent hundreds of thousands on developers before i realized i could just do this myself. the secret to running those massive open source models without the ten thousand dollar investment is renting gpu power by the hour. sites like lambda labs let you spin up a monster machine that can run any model in existence for just a couple dollars an hour this is the ultimate pivot because it allows you to test if your strategy actually prints money before you commit to the hardware. you can turn the server on when you are iterating and turn it off the second you are done which keeps your overhead near zero. if you haven't proven that your bot can pay for itself yet then buying a mac studio is just an expensive hobby rather than a business move. there is a much bigger loophole involving the anthropic subscriptions that most people are completely overlooking right now right now i am using a specific plan with claude code that costs about two hundred dollars a month but it lets me run open claw all day without hitting api limits. if i were paying for those same tokens through the standard api i would probably be spending hundreds of dollars every single day. it is a massive cost savings that allows you to iterate and fail until you find a winning strategy without draining your bank account. even if they eventually close this loophole or snitch on the usage patterns it serves as the perfect training ground for a data dog the goal is to find a system that works with a smaller or cheaper model like haiku before you ever try to scale up to the heavy weights. if you can make a strategy profitable using a less intelligent and cheaper model then you know you have found real alpha. once you have that foundation you can decide if it finally makes sense to build your own custom pc rig which will always be half the price of an apple machine. i am an apple guy so i usually pay the tax anyway but i only do it once the system is already generating enough to cover the cost ten times over i believe that code is the great equalizer because it took me from losing money and getting liquidated to having fully automated systems doing the work for me. i had to learn to live with the iterations and the failures on youtube to get to this point of clarity. the universe tends to get out of your way once you make a non negotiable contract with yourself to see the process through to the end. you don't need the flashy hardware or the most expensive setup to start winning in this game stay focused on the logic and the data rather than the hype and the fomo that everyone else is falling for. if you can master the bridge between renting power and owning your logic you will be ahead of ninety nine percent of the people in this space. the path to a fully automated life isn't paved with expensive gadgets but with the discipline to iterate until the system finally prints
16:04

Don't Buy a Mac Mini for Clawdbot: The Secret $10,000 Architecture That Costs You Nothing clawdbot might be the reason you feel like you need a ten thousand dollar computer right now but i am about to show you why that fomo is going to leave you broke. if you have been watching everyone rush out to buy mac minis and mac studios just to run open claw or some local models you are witnessing a massive transfer of wealth from your pocket to apple for no reason. there is a specific setup i use that costs almost nothing and keeps my main machine safe from whatever these autonomous agents are doing. if you stick with me i will walk you through the exact architecture of a professional trading system that handles the heavy lifting without you needing to drop a single rack on hardware most people are scared of running these bots on their main computer because they don't want an agent messing with their personal files or browser sessions. instead of buying a second mac mini for six hundred dollars you can just go to the top left of your screen and create a brand new user profile. this acts like a completely isolated sandbox where you can install all your trading tools and agents without them ever seeing your main data. it is essentially like getting a free computer for the price of five minutes of clicking around your settings but what if you aren't on a mac or you need to access your system while you are traveling without carrying three laptops in your backpack. this is where the first loop of professional automation starts to close because i use something called chrome remote desktop to bridge the gap. this allows me to leave a dedicated machine running in a safe place while i access the full desktop environment from a tablet or a cheap laptop anywhere in the world. it solves the mobility issue but it still doesn't solve the problem of those massive ten thousand dollar price tags for high end mac pros if you are a pc user or just someone who doesn't want to own physical hardware yet you should look into a windows vps through a provider like contabo. most developers will tell you to use a linux terminal but if you aren't a coder yet you need a visual interface you can actually see. getting a windows server allows you to log in and see a desktop just like your home computer for about fifteen dollars a month. i usually recommend at least twelve gigabytes of ram to keep things from getting janky when you are running multiple browser windows and agents at once now you might be thinking that the whole point of the big hardware was to run local models like kimi or glm to save on api costs. i spent years thinking i had to own the machines myself and i even spent hundreds of thousands on developers before i realized i could just do this myself. the secret to running those massive open source models without the ten thousand dollar investment is renting gpu power by the hour. sites like lambda labs let you spin up a monster machine that can run any model in existence for just a couple dollars an hour this is the ultimate pivot because it allows you to test if your strategy actually prints money before you commit to the hardware. you can turn the server on when you are iterating and turn it off the second you are done which keeps your overhead near zero. if you haven't proven that your bot can pay for itself yet then buying a mac studio is just an expensive hobby rather than a business move. there is a much bigger loophole involving the anthropic subscriptions that most people are completely overlooking right now right now i am using a specific plan with claude code that costs about two hundred dollars a month but it lets me run open claw all day without hitting api limits. if i were paying for those same tokens through the standard api i would probably be spending hundreds of dollars every single day. it is a massive cost savings that allows you to iterate and fail until you find a winning strategy without draining your bank account. even if they eventually close this loophole or snitch on the usage patterns it serves as the perfect training ground for a data dog the goal is to find a system that works with a smaller or cheaper model like haiku before you ever try to scale up to the heavy weights. if you can make a strategy profitable using a less intelligent and cheaper model then you know you have found real alpha. once you have that foundation you can decide if it finally makes sense to build your own custom pc rig which will always be half the price of an apple machine. i am an apple guy so i usually pay the tax anyway but i only do it once the system is already generating enough to cover the cost ten times over i believe that code is the great equalizer because it took me from losing money and getting liquidated to having fully automated systems doing the work for me. i had to learn to live with the iterations and the failures on youtube to get to this point of clarity. the universe tends to get out of your way once you make a non negotiable contract with yourself to see the process through to the end. you don't need the flashy hardware or the most expensive setup to start winning in this game stay focused on the logic and the data rather than the hype and the fomo that everyone else is falling for. if you can master the bridge between renting power and owning your logic you will be ahead of ninety nine percent of the people in this space. the path to a fully automated life isn't paved with expensive gadgets but with the discipline to iterate until the system finally prints

Moon Dev

17,382 просмотров • 7 месяцев назад

Donchaab’s CEO: How the brand was born and where it’s heading 🍌 #OFFROAD #offroad_KTP #ออฟโรด โดนฉาบ The Origin of DonChaab 🚗: It started when my mom came to visit me from our hometown. She brought snacks I like, and one of them was banana chips. At first, I didn’t even know where she bought them. At that time, P’Ou was visiting too, and we finished all of them. Later, I told my fans about it, and they suggested launching pre-orders for the banana chips — probably around two years ago now. Back then, they were just in these clear plastic packages, without FDA approval or Halal certification. The goal was simply to support the auntie who made them. She was supporting her grandchildren and her disabled husband. So every time we opened pre-orders, it felt like we were giving hope to that family. In return, we felt fulfilled as givers. When the fans learned about this, they realized they were helping support the family too. I kept it going without thinking much about profits. Looking back, I think it was such a beautiful beginning. 🚗: Later, I decided to continue building on it and named the brand DonChaab. The inspiration for the name partly came from the song “Chaab,” which has a fun and cute vibe. I continued selling to fans until demand exceeded supply. They couldn’t produce enough, and orders fell behind. So I thought, let’s start this properly — and that’s how this was born 🍌✨ (shows the current DonChaab) — Nong DonChaab. The mascot’s name is Jao Chaab, proposed and voted on by the fans. (turns the package) And this is Nong’s back. From those clear plastic bags… to this ✨ today. 🚗: On the package, it says “Local Farmers Supported,” because Thailand is an agricultural nation. Many fruits are exported from Thailand, and I thought it would be really cool if Thai traditional fruit snacks could also reach overseas markets. Look — it even says “Product of Thailand” on the back, which I’m really proud of! 🚗: I launched the brand not long ago, and I’m still learning as I go — adjusting the packaging, the service system, the toppings, and everything else. That’s how the brand came to be — expanding from supporting one local farmer to supporting many. In general, not just for DonChaab, when you buy processed agricultural products like this, you help reduce waste. When supply exceeds demand, produce might go to waste. By turning them into processed products, they can instead be distributed to consumers. 🚗: The brand will definitely implement Corporate Social Responsibility (CSR) initiatives, but that depends on your support. A portion of the profits will be allocated toward CSR. As I said in one interview — as someone who has received so much, if one day I feel that I’ve received enough, I want to start giving back. Through this brand, fans get to enjoy the snacks, and I get to run the business my way — building my own team, creating opportunities for recent graduates and people of all ages, and shaping the kind of work environment I’ve always envisioned. 🍌// Currently, DonChaab can be ordered online at and is shipped domestically only. Orders are released in rounds, and the most recent one just closed. So keep an eye out for the next round! In the near future, international shipping may also become available. T/N: I skip some parts where he talks about the products, visit the website for more specific details!
6:36

Donchaab’s CEO: How the brand was born and where it’s heading 🍌 #OFFROAD #offroad_KTP #ออฟโรด โดนฉาบ The Origin of DonChaab 🚗: It started when my mom came to visit me from our hometown. She brought snacks I like, and one of them was banana chips. At first, I didn’t even know where she bought them. At that time, P’Ou was visiting too, and we finished all of them. Later, I told my fans about it, and they suggested launching pre-orders for the banana chips — probably around two years ago now. Back then, they were just in these clear plastic packages, without FDA approval or Halal certification. The goal was simply to support the auntie who made them. She was supporting her grandchildren and her disabled husband. So every time we opened pre-orders, it felt like we were giving hope to that family. In return, we felt fulfilled as givers. When the fans learned about this, they realized they were helping support the family too. I kept it going without thinking much about profits. Looking back, I think it was such a beautiful beginning. 🚗: Later, I decided to continue building on it and named the brand DonChaab. The inspiration for the name partly came from the song “Chaab,” which has a fun and cute vibe. I continued selling to fans until demand exceeded supply. They couldn’t produce enough, and orders fell behind. So I thought, let’s start this properly — and that’s how this was born 🍌✨ (shows the current DonChaab) — Nong DonChaab. The mascot’s name is Jao Chaab, proposed and voted on by the fans. (turns the package) And this is Nong’s back. From those clear plastic bags… to this ✨ today. 🚗: On the package, it says “Local Farmers Supported,” because Thailand is an agricultural nation. Many fruits are exported from Thailand, and I thought it would be really cool if Thai traditional fruit snacks could also reach overseas markets. Look — it even says “Product of Thailand” on the back, which I’m really proud of! 🚗: I launched the brand not long ago, and I’m still learning as I go — adjusting the packaging, the service system, the toppings, and everything else. That’s how the brand came to be — expanding from supporting one local farmer to supporting many. In general, not just for DonChaab, when you buy processed agricultural products like this, you help reduce waste. When supply exceeds demand, produce might go to waste. By turning them into processed products, they can instead be distributed to consumers. 🚗: The brand will definitely implement Corporate Social Responsibility (CSR) initiatives, but that depends on your support. A portion of the profits will be allocated toward CSR. As I said in one interview — as someone who has received so much, if one day I feel that I’ve received enough, I want to start giving back. Through this brand, fans get to enjoy the snacks, and I get to run the business my way — building my own team, creating opportunities for recent graduates and people of all ages, and shaping the kind of work environment I’ve always envisioned. 🍌// Currently, DonChaab can be ordered online at and is shipped domestically only. Orders are released in rounds, and the most recent one just closed. So keep an eye out for the next round! In the near future, international shipping may also become available. T/N: I skip some parts where he talks about the products, visit the website for more specific details!

Be~nyaa 💫

11,876 просмотров • 6 месяцев назад

Moneytaur study blueprint 🗺️ The process I used to go from not knowing what an order block is to pulling cash from the crypto markets in under 6 months using 🎯 Master concepts. Proof of performance, past 120 days👇 Start date: 09/03/2025 Requirements: - A PC/laptop - Wifi - A basic understanding of trading. ( What candlesticks are, how to actually place trades , etc ) - A free mind - Time or the ability to free up time. Starting: - Structure and routine - Stick to that routine + Pre mortem plan. - Notion / Obsidian setup. The first thing you need to create is a clear routine moulded around how you intend to approach this very large and complex task. This will not be linear and you will naturally adapt it as you progress but especially in the beginning some resemblance of structure each day is vital. This is an individual process but it is important to understand from the beginning that this will require a majority of your free time assuming you work a full time Job or study as a student. For me in the beginning this looked like: - Wake up at 6:30. - Shower - Study/work for 1h 45m before leaving for work. - 09:00 -> 17:00 work - 17:30 Exercise / Train - Eat - 19:00 resume study/work - 22:30 Start to wind down and get ready to sleep. It changed several times over the months and especially now I am full time but this is irrelevant, the only thing that matters is sticking with what you choose. Whatever your own routine may look like, it is important to understand it will inevitably require sacrifice. --- The next thing once you have established a draft framework of your routine is ensuring you will actually stick to that routine. Something I implemented which I found particularly beneficial was the concept of a Pre-Mortem plan. This involves creating several scenarios of a future in which you have failed and working backwards from each of these to find where it went wrong. Here is a video which explains it fully: When I did this I came up with 3 scenarios as well as prevention and cure for each. In the 6 months that followed each scenario presented at some point but I was able to catch them early due to having done this. The last thing is to not over complicate this, don't hyper focus on systems and loose momentum optimizing each detail. Just ensure you do the fucking work. I was a little guilty of the above at times, trying to craft the perfect routine. In reality the person who just gets up, drinks too much coffee and works his ass off out performs the workflow perfectionist who visualizes and repeats affirmations, any day of the week. --- Next you need somewhere to store your notes, journal your trades and build your knowledge. For me this was Obsidian but I have also used Notion before and it is an equally viable option. Whichever one of these you choose be warned you will inevitably want to bang your head against a wall trying to use them for the first few days, but they will both click pretty quick and are 100% better options the word document or paper alternative. Here is my full obsidian setup tutorial: Here is a link to MisterPA 's notion Journal: Here is how I create "Meta-Notes" using obsidian: The process: - How I did it. - How I would do it if doing it again. Now I did things the "hard way" and manually worked my way back through each of MT's tweets starting in 2021, reading every one and logging those that I felt where relevant. You can see in my first post: the very first system I used to do this. I quickly adapted though after about a week and focused less on just logging each relevant tweet but trying to find and focusing on those which contained the most information. There where a lot of charts I looked at then skipped over because especially at the start of his timeline they contained little useful information and my time was better spent finding those where there was something to decode. Now this does not mean skip out on "work" just use your time efficiently. -- If however if I was to start from the beginning again with the goal of levelling up technical understanding as quickly as possible I would take a different approach. To start with I would familiarise myself with all relevant SMC concepts, I have linked the best free recourses for this below 👇 CryptoChase beginner friendly index: Barncore's "The Moneytaur Way" series: Gian's Trading bootcamp playlist: Following this I would then work through all of Taur's subscription posts working backwards, recreating his charts and taking notes on his logic. The subscription feed has the highest value density and least noise. Video example of my notes from his subscription posts 👇: --- Okay so now once you have a basic understanding of concepts and can re-recreate them on charts of your own it is time to put this in to practice. The next step is vigorous backtesting, you can use the trading view tool but I think trade Zella offers a more use friendly option if you pay for the subscription. Especially as it allows you to change timeframes without skipping ahead to candle close time of the timeframe you change too ( like Trading view does ) *my only note would be that their LTF/Micro TF data feed with be different to brokerage charts you will use on Trading view, to start with though you should not be going low enough that this is an issue. When you backtest in this context, treat it like real trading. That means journal and logging like you would if real cash was on the line. Take time, do not rush and focus on quality. Stick to BTC, ETH, Major FX pairs or indices as these assets are less reliant on confluence, backtesting a shitcoin is near useless as whether levels work or not will be highly dependent on Majors PA. Go on HTF, scroll back a couple years and try not too look at chart while doing so and then begin. Start with HTF analysis and work down to 2H or wherever you feel comfortable, chart it fully and then identify setups. Make rough notes / plans and then press play, execute the setups as they hit, log and journal trade management as well as observations and key notes. It is very important to not cheat when you do this, do not skip back and adjust your stoploss because it hit by 0.1%, do not skip back and adjust plan because you missed a block and your TP got frontrun. Instead these are the things you journal, embrace these mistakes because they are the cheapest mistakes you are going to make. Grind this, do it for hours, put some music on and enjoy. To start with focus on HTF's, as you get better and start netting $ on paper you can drop the timeframes and increase the difficulty. HTF = Normal, MTF = Medium, LTF = Hard. Even if you do not intend to day trade, learning how to read the lower TF's that force you to think faster, harder and prepare you for lower win rates / loss streaks can greatly improve your ability on higher TF's. While you are doing this as you start to have concepts click you now want to build up your real trading experience, take a sum of money that you care about but will be okay loosing and dedicate this to live trading. Start taking real trades and expect net losses in the beginning. This is where you will make you 2nd cheapest mistakes. This is also where you can begin to learn about your psychology. You may encounter some elements already in backtesting but the real market is where true colours really start to show. Mental issues are inevitable and part of the game, get used to them and start working to identify and fix them. Reading and applying books like Trading in the Zone and Mental Game of Trading are important and will help a lot but there is no easy fix, for some stuff you I believe you just have to get used to it and it goes away with experience. Losses suck at the beginning but after you loose 100 times you starting getting pretty numb to it, same goes for the winners. To accelerate the learning process, build connections and get advice there is also always the option of private groups, while I never personally chose this route and committed to learning everything through my own endeavours there is no denying that having nearly all the information you need structured and compiled in one place is valuable and can save time. Beyond this having access to real time thoughts and opinions of profitable traders can accelerate performance, however it carries the risk of being a double edged sword if not used properly, if relying on it like a crutch and using it as a substitute for real work you will not succeed. With that said if you take it for what it is, a learning opportunity then I believe it can be very beneficial. I am not a member of, nor affiliated with any paid group. There are now many options available within the community, all run by different people with different styles, tailored to different needs. If I was to make a recommendation though, as a non-member, it would be Albert & Co's 618'ers simply due to the diversity in styles of the traders running it and results I have seen from members I know personally. It is important that as you start to trade with real capital you reduce noise in your social feeds or eliminate it all together. You do not need 5 different opinions, you also do not need 2 people telling you the same thing in their own way so you feel re-assured. What you do need is to develop your independent thinking as a trader and be comfortable making different decisions to others, even traders ahead of yourself if it fits with your system or understanding of market. Taur here is perhaps an exception as this is who you are learning from but down the line a real test of your own ability and independence will be being able to stick with your own plan even when it differs from his. Don't get me wrong, counter trading him is retarded but you must learn to adapt his gift to your own style. This will make sense at some point. The next stage is taking your understanding of specific concepts to higher level as you simultaneously snowball experience. Look back through your journal and review where you lost money and made money, do not over extrapolate from a small sample but start to take notes and observe if trends in performance emerge. This is the beginning of the transition to self reliance, you now understand the strategy but must learn for yourself when and where it works. Here you can also learn more nuanced secondary concepts such as VSA, orderflow etc and add these to your game where appropriate. Do NOT get lost in the sauce though and remember mastery of basics is key. IMO a big focus should be understanding correlation thoroughly but especially on HTF's this is the most important thing and what triggers the majority of large swings where most of your cash will be made and losses recovered. Some people will disagree with me here but IMO you should also not be *focusing* on Odd TF's. These are secondary at best and most people overweight their significance leading to avoidable losses while wondering why price did not care about their 327minute Breaker Block which they think is the key to the market. Study Taurs feed and take note of how he mostly uses: 3M, 1M, 3W, 2W, 1W, 5D, 4D, 3D, 2D, 1D, 12H, 8H, 6H, 4H, 2H, 1H, 30m, 15m + micro time frames. The only thing left is time and repetition, you must show up each day and really do this, for months. Maybe you start to see result's, you catch your first key swing and where able to trade where others froze. Congratulations. Learn from these winners and repeat the actions. Find what assets work best for you, find your style, refine and grow. --- The last thing I will include is a short list of tools or links that can be helpful. - Trading view tutorial: - Dictionary: - Market news Calendar: --- Thank you too all those who have read this, I hope this has been helpful for the beginners who want to start but are just not sure how. 🫶 Don't just bookmark this and move on, start 🙃
0:38

Moneytaur study blueprint 🗺️ The process I used to go from not knowing what an order block is to pulling cash from the crypto markets in under 6 months using 🎯 Master concepts. Proof of performance, past 120 days👇 Start date: 09/03/2025 Requirements: - A PC/laptop - Wifi - A basic understanding of trading. ( What candlesticks are, how to actually place trades , etc ) - A free mind - Time or the ability to free up time. Starting: - Structure and routine - Stick to that routine + Pre mortem plan. - Notion / Obsidian setup. The first thing you need to create is a clear routine moulded around how you intend to approach this very large and complex task. This will not be linear and you will naturally adapt it as you progress but especially in the beginning some resemblance of structure each day is vital. This is an individual process but it is important to understand from the beginning that this will require a majority of your free time assuming you work a full time Job or study as a student. For me in the beginning this looked like: - Wake up at 6:30. - Shower - Study/work for 1h 45m before leaving for work. - 09:00 -> 17:00 work - 17:30 Exercise / Train - Eat - 19:00 resume study/work - 22:30 Start to wind down and get ready to sleep. It changed several times over the months and especially now I am full time but this is irrelevant, the only thing that matters is sticking with what you choose. Whatever your own routine may look like, it is important to understand it will inevitably require sacrifice. --- The next thing once you have established a draft framework of your routine is ensuring you will actually stick to that routine. Something I implemented which I found particularly beneficial was the concept of a Pre-Mortem plan. This involves creating several scenarios of a future in which you have failed and working backwards from each of these to find where it went wrong. Here is a video which explains it fully: When I did this I came up with 3 scenarios as well as prevention and cure for each. In the 6 months that followed each scenario presented at some point but I was able to catch them early due to having done this. The last thing is to not over complicate this, don't hyper focus on systems and loose momentum optimizing each detail. Just ensure you do the fucking work. I was a little guilty of the above at times, trying to craft the perfect routine. In reality the person who just gets up, drinks too much coffee and works his ass off out performs the workflow perfectionist who visualizes and repeats affirmations, any day of the week. --- Next you need somewhere to store your notes, journal your trades and build your knowledge. For me this was Obsidian but I have also used Notion before and it is an equally viable option. Whichever one of these you choose be warned you will inevitably want to bang your head against a wall trying to use them for the first few days, but they will both click pretty quick and are 100% better options the word document or paper alternative. Here is my full obsidian setup tutorial: Here is a link to MisterPA 's notion Journal: Here is how I create "Meta-Notes" using obsidian: The process: - How I did it. - How I would do it if doing it again. Now I did things the "hard way" and manually worked my way back through each of MT's tweets starting in 2021, reading every one and logging those that I felt where relevant. You can see in my first post: the very first system I used to do this. I quickly adapted though after about a week and focused less on just logging each relevant tweet but trying to find and focusing on those which contained the most information. There where a lot of charts I looked at then skipped over because especially at the start of his timeline they contained little useful information and my time was better spent finding those where there was something to decode. Now this does not mean skip out on "work" just use your time efficiently. -- If however if I was to start from the beginning again with the goal of levelling up technical understanding as quickly as possible I would take a different approach. To start with I would familiarise myself with all relevant SMC concepts, I have linked the best free recourses for this below 👇 CryptoChase beginner friendly index: Barncore's "The Moneytaur Way" series: Gian's Trading bootcamp playlist: Following this I would then work through all of Taur's subscription posts working backwards, recreating his charts and taking notes on his logic. The subscription feed has the highest value density and least noise. Video example of my notes from his subscription posts 👇: --- Okay so now once you have a basic understanding of concepts and can re-recreate them on charts of your own it is time to put this in to practice. The next step is vigorous backtesting, you can use the trading view tool but I think trade Zella offers a more use friendly option if you pay for the subscription. Especially as it allows you to change timeframes without skipping ahead to candle close time of the timeframe you change too ( like Trading view does ) *my only note would be that their LTF/Micro TF data feed with be different to brokerage charts you will use on Trading view, to start with though you should not be going low enough that this is an issue. When you backtest in this context, treat it like real trading. That means journal and logging like you would if real cash was on the line. Take time, do not rush and focus on quality. Stick to BTC, ETH, Major FX pairs or indices as these assets are less reliant on confluence, backtesting a shitcoin is near useless as whether levels work or not will be highly dependent on Majors PA. Go on HTF, scroll back a couple years and try not too look at chart while doing so and then begin. Start with HTF analysis and work down to 2H or wherever you feel comfortable, chart it fully and then identify setups. Make rough notes / plans and then press play, execute the setups as they hit, log and journal trade management as well as observations and key notes. It is very important to not cheat when you do this, do not skip back and adjust your stoploss because it hit by 0.1%, do not skip back and adjust plan because you missed a block and your TP got frontrun. Instead these are the things you journal, embrace these mistakes because they are the cheapest mistakes you are going to make. Grind this, do it for hours, put some music on and enjoy. To start with focus on HTF's, as you get better and start netting $ on paper you can drop the timeframes and increase the difficulty. HTF = Normal, MTF = Medium, LTF = Hard. Even if you do not intend to day trade, learning how to read the lower TF's that force you to think faster, harder and prepare you for lower win rates / loss streaks can greatly improve your ability on higher TF's. While you are doing this as you start to have concepts click you now want to build up your real trading experience, take a sum of money that you care about but will be okay loosing and dedicate this to live trading. Start taking real trades and expect net losses in the beginning. This is where you will make you 2nd cheapest mistakes. This is also where you can begin to learn about your psychology. You may encounter some elements already in backtesting but the real market is where true colours really start to show. Mental issues are inevitable and part of the game, get used to them and start working to identify and fix them. Reading and applying books like Trading in the Zone and Mental Game of Trading are important and will help a lot but there is no easy fix, for some stuff you I believe you just have to get used to it and it goes away with experience. Losses suck at the beginning but after you loose 100 times you starting getting pretty numb to it, same goes for the winners. To accelerate the learning process, build connections and get advice there is also always the option of private groups, while I never personally chose this route and committed to learning everything through my own endeavours there is no denying that having nearly all the information you need structured and compiled in one place is valuable and can save time. Beyond this having access to real time thoughts and opinions of profitable traders can accelerate performance, however it carries the risk of being a double edged sword if not used properly, if relying on it like a crutch and using it as a substitute for real work you will not succeed. With that said if you take it for what it is, a learning opportunity then I believe it can be very beneficial. I am not a member of, nor affiliated with any paid group. There are now many options available within the community, all run by different people with different styles, tailored to different needs. If I was to make a recommendation though, as a non-member, it would be Albert & Co's 618'ers simply due to the diversity in styles of the traders running it and results I have seen from members I know personally. It is important that as you start to trade with real capital you reduce noise in your social feeds or eliminate it all together. You do not need 5 different opinions, you also do not need 2 people telling you the same thing in their own way so you feel re-assured. What you do need is to develop your independent thinking as a trader and be comfortable making different decisions to others, even traders ahead of yourself if it fits with your system or understanding of market. Taur here is perhaps an exception as this is who you are learning from but down the line a real test of your own ability and independence will be being able to stick with your own plan even when it differs from his. Don't get me wrong, counter trading him is retarded but you must learn to adapt his gift to your own style. This will make sense at some point. The next stage is taking your understanding of specific concepts to higher level as you simultaneously snowball experience. Look back through your journal and review where you lost money and made money, do not over extrapolate from a small sample but start to take notes and observe if trends in performance emerge. This is the beginning of the transition to self reliance, you now understand the strategy but must learn for yourself when and where it works. Here you can also learn more nuanced secondary concepts such as VSA, orderflow etc and add these to your game where appropriate. Do NOT get lost in the sauce though and remember mastery of basics is key. IMO a big focus should be understanding correlation thoroughly but especially on HTF's this is the most important thing and what triggers the majority of large swings where most of your cash will be made and losses recovered. Some people will disagree with me here but IMO you should also not be *focusing* on Odd TF's. These are secondary at best and most people overweight their significance leading to avoidable losses while wondering why price did not care about their 327minute Breaker Block which they think is the key to the market. Study Taurs feed and take note of how he mostly uses: 3M, 1M, 3W, 2W, 1W, 5D, 4D, 3D, 2D, 1D, 12H, 8H, 6H, 4H, 2H, 1H, 30m, 15m + micro time frames. The only thing left is time and repetition, you must show up each day and really do this, for months. Maybe you start to see result's, you catch your first key swing and where able to trade where others froze. Congratulations. Learn from these winners and repeat the actions. Find what assets work best for you, find your style, refine and grow. --- The last thing I will include is a short list of tools or links that can be helpful. - Trading view tutorial: - Dictionary: - Market news Calendar: --- Thank you too all those who have read this, I hope this has been helpful for the beginners who want to start but are just not sure how. 🫶 Don't just bookmark this and move on, start 🙃

Ace

45,581 просмотров • 10 месяцев назад

Why Exchanges Banned This Bot: The 142,000% Return Liquidation Strategy Revealed i finally posted the strategy that got me banned and now the exchanges are probably sweating because i am handing you the keys to the liquidation engine. most people think trading is about charts but the real alpha is hidden in the moments when other traders lose everything. if you can understand why market makers hunt these positions you will never look at a candlestick the same way again. it took years of losing money to liquidations and over trading to realize that hand trading is a losing game for almost everyone on the planet. code is the great equalizer because it removes the emotion that usually causes you to hold a losing position until your account hits zero. i spent hundreds of thousands on developers in the past thinking i could not code myself until i realized i just needed to iterate to success. trading by hand is just driving a horse while everyone else is in a ferrari and the fees alone will chop you up before you even realize you were wrong. i watched a guy with a six million dollar short position sitting just two percent away from total liquidation while i was building this. seeing those numbers on the screen gives me ideas that i can automate into a bot so i dont have to spend my life staring at a monitor. the process i follow is called the rbi system which stands for research backtest and implement. most traders skip the first two steps and go straight to implementation which is why they get smoked on their very first bot. research starts with a backlog of ideas from books or papers or even just watching how the market reacts to big moves. once you have that idea you have to see if it worked in the past using a backtest because if it did not work then it certainly won't work in the future. i have been collecting liquidation data for eighteen months because that data is the lifeblood of a winning system. there is a hidden loop in the market where market makers try to liquidate as many people as possible to find liquidity. i wanted to build a strategy that either trades with that momentum or bets on the bounce right after the liquidation happens. the first strategy i tested was a pure liquidation momentum play that looks for a threshold of nine hundred seventy five thousand dollars in liquidations. when longs get liquidated it shorts the market to continue the down move and it tries to take a one percent profit. this strategy showed a return of over four hundred percent in the backtest while the buy and hold was only thirty three percent. it sounds amazing but you have to be careful with optimized results because you can search with math until you find anything. i decided to flip the logic on its head and create an inverse liquidation strategy that acts as a contrarian. instead of following the move it waits for the longs to get liquidated and then buys the dip after a small price spread. this is where i stumbled onto something that felt like a mistake but turned out to be pure alpha. i accidentally typed in a threshold of three hundred thousand dollars instead of three million and the results were unbelievable. the backtest return jumped to over one hundred forty thousand percent because the bot was catching every single micro bounce in the market. even when i doubled the commission fees to account for the high trade volume the strategy still stayed incredibly profitable. most people would have missed this because they are too busy trying to be right instead of just looking at what the data says. i use tools like claude and cursor to build these bots in minutes when it used to take me an entire week to write the code. if you are not using ai to automate your ideas you are essentially choosing to work ten times harder for less money. i built three separate bots during this session including a momentum bot and two different versions of the inverse spread bot. running these together creates a sort of statistical arbitrage where you can hedge your positions across different market conditions. one bot wins when the market cascades and the other wins when it fakes out and reverses. you have to start with tiny ten dollar sizes because a backtest is never a hundred percent guarantee of what will happen today. i always run my p and l close logic first to make sure the bot exits the position if the stop loss or take profit is hit. it is vital to check your position every fifteen seconds and make sure you are not double ordering or getting stuck in a trade. the goal is to have fully automated systems trading for you so you can actually live your life while the bots do the work. i push all of this code to my private github because i believe that wall street will never show you how this actually works. you have to be a doer and not a dabbler if you want to actually make it in this industry. the reason i show everything live on youtube is to prove that anyone can learn to do this if they are willing to iterate. you dont need to be a math genius you just need to follow the rbi system and stay disciplined with your risk. every liquidation you see on the chart is a signal and if you know how to read them you are no longer the one being hunted. i am currently running the third version of the bot to see how it handles the live market volatility. it is a beautiful thing to see a system enter and exit a trade perfectly without you having to click a single button. the fees are the silent killer of hand traders but a bot can be programmed to use limit orders and stay efficient. if you learn to code you can build anything for the rest of your life regardless of where you are in the world. stop trying to guess which way the candle will go and start building systems that can handle both directions. i am going to keep testing these three strategies against each other to find the ultimate ensemble for this current market. once you find a winning edge you just have to scale it up slowly and keep refining the parameters. the exchanges might not like that i am sharing this but code is the great equalizer and it is time for you to use it. i will be back tomorrow to show the results and keep building more systems until everything is fully automated
1:23:35

Why Exchanges Banned This Bot: The 142,000% Return Liquidation Strategy Revealed i finally posted the strategy that got me banned and now the exchanges are probably sweating because i am handing you the keys to the liquidation engine. most people think trading is about charts but the real alpha is hidden in the moments when other traders lose everything. if you can understand why market makers hunt these positions you will never look at a candlestick the same way again. it took years of losing money to liquidations and over trading to realize that hand trading is a losing game for almost everyone on the planet. code is the great equalizer because it removes the emotion that usually causes you to hold a losing position until your account hits zero. i spent hundreds of thousands on developers in the past thinking i could not code myself until i realized i just needed to iterate to success. trading by hand is just driving a horse while everyone else is in a ferrari and the fees alone will chop you up before you even realize you were wrong. i watched a guy with a six million dollar short position sitting just two percent away from total liquidation while i was building this. seeing those numbers on the screen gives me ideas that i can automate into a bot so i dont have to spend my life staring at a monitor. the process i follow is called the rbi system which stands for research backtest and implement. most traders skip the first two steps and go straight to implementation which is why they get smoked on their very first bot. research starts with a backlog of ideas from books or papers or even just watching how the market reacts to big moves. once you have that idea you have to see if it worked in the past using a backtest because if it did not work then it certainly won't work in the future. i have been collecting liquidation data for eighteen months because that data is the lifeblood of a winning system. there is a hidden loop in the market where market makers try to liquidate as many people as possible to find liquidity. i wanted to build a strategy that either trades with that momentum or bets on the bounce right after the liquidation happens. the first strategy i tested was a pure liquidation momentum play that looks for a threshold of nine hundred seventy five thousand dollars in liquidations. when longs get liquidated it shorts the market to continue the down move and it tries to take a one percent profit. this strategy showed a return of over four hundred percent in the backtest while the buy and hold was only thirty three percent. it sounds amazing but you have to be careful with optimized results because you can search with math until you find anything. i decided to flip the logic on its head and create an inverse liquidation strategy that acts as a contrarian. instead of following the move it waits for the longs to get liquidated and then buys the dip after a small price spread. this is where i stumbled onto something that felt like a mistake but turned out to be pure alpha. i accidentally typed in a threshold of three hundred thousand dollars instead of three million and the results were unbelievable. the backtest return jumped to over one hundred forty thousand percent because the bot was catching every single micro bounce in the market. even when i doubled the commission fees to account for the high trade volume the strategy still stayed incredibly profitable. most people would have missed this because they are too busy trying to be right instead of just looking at what the data says. i use tools like claude and cursor to build these bots in minutes when it used to take me an entire week to write the code. if you are not using ai to automate your ideas you are essentially choosing to work ten times harder for less money. i built three separate bots during this session including a momentum bot and two different versions of the inverse spread bot. running these together creates a sort of statistical arbitrage where you can hedge your positions across different market conditions. one bot wins when the market cascades and the other wins when it fakes out and reverses. you have to start with tiny ten dollar sizes because a backtest is never a hundred percent guarantee of what will happen today. i always run my p and l close logic first to make sure the bot exits the position if the stop loss or take profit is hit. it is vital to check your position every fifteen seconds and make sure you are not double ordering or getting stuck in a trade. the goal is to have fully automated systems trading for you so you can actually live your life while the bots do the work. i push all of this code to my private github because i believe that wall street will never show you how this actually works. you have to be a doer and not a dabbler if you want to actually make it in this industry. the reason i show everything live on youtube is to prove that anyone can learn to do this if they are willing to iterate. you dont need to be a math genius you just need to follow the rbi system and stay disciplined with your risk. every liquidation you see on the chart is a signal and if you know how to read them you are no longer the one being hunted. i am currently running the third version of the bot to see how it handles the live market volatility. it is a beautiful thing to see a system enter and exit a trade perfectly without you having to click a single button. the fees are the silent killer of hand traders but a bot can be programmed to use limit orders and stay efficient. if you learn to code you can build anything for the rest of your life regardless of where you are in the world. stop trying to guess which way the candle will go and start building systems that can handle both directions. i am going to keep testing these three strategies against each other to find the ultimate ensemble for this current market. once you find a winning edge you just have to scale it up slowly and keep refining the parameters. the exchanges might not like that i am sharing this but code is the great equalizer and it is time for you to use it. i will be back tomorrow to show the results and keep building more systems until everything is fully automated

Moon Dev

11,948 просмотров • 5 месяцев назад

I Spent $100k On Developers Before Learning This: Build Your AI Bot Today the blueprint to building your first ai trading bot without a degree or a single clue where to start is hidden in plain sight. most people think you need a stanford degree or some crazy math background to build these systems but i spent ten years in tech scared to code for that exact reason. i thought it was only for the geniuses and the nerds while i was just a guy who played video games and wanted his time back the reality is that code is the great equalizer because it doesn't care who you are or where you came from. i lost hundreds of thousands of dollars hiring developers who did shoddy work and i lost even more through liquidations and over trading because i was too emotional to follow my own rules. i knew i had to automate everything if i wanted to survive this game so i decided to learn live on youtube and iterate my way to success everyone is looking for the holy grail indicator that prints money while they sleep but they are looking in the wrong place. the real secret isn't a magical line on a chart but a process i call the rbi system which stands for research backtest and implement. most traders fail because they try to build a bot before they even know if their strategy worked in the past which is basically just gambling with extra steps you have to start with deep research into a strategy like supply and demand zones where you buy where the banks buy and sell where they sell. once you have a solid idea you must backtest it against years of data to see if it actually has an edge. if it doesn't work in the past it definitely won't work in the future but if it shows promise then you move to the implementation phase with small size there is a hidden cost to automation that can wipe out your profits before you even place a trade if you aren't careful. i found myself overusing api credits and running up a massive bill just to fetch wallet balances and token lists. if your bot is calling the exchange every five seconds just to see how much money you have you are essentially burning cash for no reason you can use ai tools like cursor to help you write the python code even if you are a total beginner. i still use ai to explain complex functions and identify where my code is being inefficient or chewing through credits. i had to refactor my entire dashboard and timer logic to only check balances every thirty minutes instead of every few seconds to save those precious credits the man who made thirty one billion dollars in the markets had one rule he never broke throughout his entire career. jim simons was the greatest algorithmic trader to ever live and he proved that systems will always beat human intuition over a long enough timeline. his secret wasn't some complex formula that no one else could understand but a commitment to a specific way of thinking simons always said you just have to make your systems better and better because that is what everyone else is trying to do. the game never really ends because the markets are always evolving and your edge will eventually decay if you don't iterate. this is why i build in public and show every step of the process because the iteration is where the actual money is made the reason you get liquidated isn't the market or the whales or some conspiracy against your small account. the real reason is the conversation you have with yourself at two in the morning when you are down on a trade and decide to move your stop loss. humans are built for survival not for trading and our emotions like fomo and fear will always sabotage our results when you automate your trading you are essentially signing a non negotiable contract with yourself that the bot will execute without question. if the plan says to sell fifty percent in an uptrend and ninety five percent in a downtrend the bot does it every single time. it doesn't feel the panic when a red candle drops or the greed when a green one spikes it just follows the code i used to spend all day staring at screens chasing bars up and down thinking that more screen time equaled more profit. i got into trading to get my time back but i ended up becoming a slave to the charts until i finally learned to code. now i have fully automated systems trading for me instead of getting liquidated because i removed the weakest link in the system which was me you don't need to spend ten years learning how to code before you can start building your own trading bots. if you spend three to six months getting the gist of python and using ai to bridge the gap you can start building immediately. start with a simple supply and demand bot that looks for major coin trends and only enters when the odds are heavily in your favor by checking the trend of bitcoin ethereum and solana simultaneously you can ensure you aren't fighting the overall market direction. i look for at least two out of those three to be trending before my bot is even allowed to look for an entry. this simple filter alone can save you from thousands of dollars in paper cuts during choppy sideways markets if you can't fly then run and if you can't run then walk but by all means you must keep moving toward automation. the process of taking an idea out of your brain and putting it into a system is the most secretive and valuable skill in the world. don't follow the pack and try to solve the same problems as everyone else but find your own edge and code it into existence the deal you make with yourself at the start of your journey is what determines if you will actually make it or not. i made a contract with myself to learn live and show everything because i believe that transparency is the only way to truly learn this craft. stick to your plan and iterate every single day because the systems you build today are the equalizers that will change your life tomorrow
50:50

I Spent $100k On Developers Before Learning This: Build Your AI Bot Today the blueprint to building your first ai trading bot without a degree or a single clue where to start is hidden in plain sight. most people think you need a stanford degree or some crazy math background to build these systems but i spent ten years in tech scared to code for that exact reason. i thought it was only for the geniuses and the nerds while i was just a guy who played video games and wanted his time back the reality is that code is the great equalizer because it doesn't care who you are or where you came from. i lost hundreds of thousands of dollars hiring developers who did shoddy work and i lost even more through liquidations and over trading because i was too emotional to follow my own rules. i knew i had to automate everything if i wanted to survive this game so i decided to learn live on youtube and iterate my way to success everyone is looking for the holy grail indicator that prints money while they sleep but they are looking in the wrong place. the real secret isn't a magical line on a chart but a process i call the rbi system which stands for research backtest and implement. most traders fail because they try to build a bot before they even know if their strategy worked in the past which is basically just gambling with extra steps you have to start with deep research into a strategy like supply and demand zones where you buy where the banks buy and sell where they sell. once you have a solid idea you must backtest it against years of data to see if it actually has an edge. if it doesn't work in the past it definitely won't work in the future but if it shows promise then you move to the implementation phase with small size there is a hidden cost to automation that can wipe out your profits before you even place a trade if you aren't careful. i found myself overusing api credits and running up a massive bill just to fetch wallet balances and token lists. if your bot is calling the exchange every five seconds just to see how much money you have you are essentially burning cash for no reason you can use ai tools like cursor to help you write the python code even if you are a total beginner. i still use ai to explain complex functions and identify where my code is being inefficient or chewing through credits. i had to refactor my entire dashboard and timer logic to only check balances every thirty minutes instead of every few seconds to save those precious credits the man who made thirty one billion dollars in the markets had one rule he never broke throughout his entire career. jim simons was the greatest algorithmic trader to ever live and he proved that systems will always beat human intuition over a long enough timeline. his secret wasn't some complex formula that no one else could understand but a commitment to a specific way of thinking simons always said you just have to make your systems better and better because that is what everyone else is trying to do. the game never really ends because the markets are always evolving and your edge will eventually decay if you don't iterate. this is why i build in public and show every step of the process because the iteration is where the actual money is made the reason you get liquidated isn't the market or the whales or some conspiracy against your small account. the real reason is the conversation you have with yourself at two in the morning when you are down on a trade and decide to move your stop loss. humans are built for survival not for trading and our emotions like fomo and fear will always sabotage our results when you automate your trading you are essentially signing a non negotiable contract with yourself that the bot will execute without question. if the plan says to sell fifty percent in an uptrend and ninety five percent in a downtrend the bot does it every single time. it doesn't feel the panic when a red candle drops or the greed when a green one spikes it just follows the code i used to spend all day staring at screens chasing bars up and down thinking that more screen time equaled more profit. i got into trading to get my time back but i ended up becoming a slave to the charts until i finally learned to code. now i have fully automated systems trading for me instead of getting liquidated because i removed the weakest link in the system which was me you don't need to spend ten years learning how to code before you can start building your own trading bots. if you spend three to six months getting the gist of python and using ai to bridge the gap you can start building immediately. start with a simple supply and demand bot that looks for major coin trends and only enters when the odds are heavily in your favor by checking the trend of bitcoin ethereum and solana simultaneously you can ensure you aren't fighting the overall market direction. i look for at least two out of those three to be trending before my bot is even allowed to look for an entry. this simple filter alone can save you from thousands of dollars in paper cuts during choppy sideways markets if you can't fly then run and if you can't run then walk but by all means you must keep moving toward automation. the process of taking an idea out of your brain and putting it into a system is the most secretive and valuable skill in the world. don't follow the pack and try to solve the same problems as everyone else but find your own edge and code it into existence the deal you make with yourself at the start of your journey is what determines if you will actually make it or not. i made a contract with myself to learn live and show everything because i believe that transparency is the only way to truly learn this craft. stick to your plan and iterate every single day because the systems you build today are the equalizers that will change your life tomorrow

Moon Dev

11,726 просмотров • 7 месяцев назад

Bitcoin hashrate dropped ~20% in just a few days. Because extreme winter weather across the US punished weak mining operations. Here’s what actually breaks miners during a polar vortex (and how operators prepare) 👇 HOW WINTER BREAKS MINERS Cold doesn’t usually kill miners while they’re running. It kills them when: • machines cool down too fast • airflow isn’t controlled • miners restart while still cold Most damage happens during restarts and boot-ups, not steady-state hashing. HOW OPERATORS PROTECT HASHRATE 1️⃣ Control temperature swings (not just temperature) Rapid changes are the enemy. • Insulate containers and buildings to slow heat loss • Limit cold air intake until miners are hashing and warming themselves • Keep container lids closed during startup • Use hot-air feedback to warm machines gradually Goal: warm up slowly, cool down slowly. 2️⃣ Don’t let airflow work against you Airflow that’s great in summer can kill you in winter. Watch out for: • External fans pushing freezing air inside • Chimney effects that pull heat out too fast • Wide-open intakes during startup Common fixes: • Slow or pause intake fans during warm-up • Disrupt chimney effects temporarily • Use finer dust filters to reduce cold airflow Once machines are stable, airflow can come back. 3️⃣ Be careful when rebooting hashing miners Reboots in freezing temperatures are where most costly mistakes happen. Safer approach: • Reboot during the warmest part of the day • Do it one rack at a time • Keep lower shelves running so rising heat protects upper ones Rushing reboots saves minutes now and costs days later. 4️⃣ Booting miners that were offline is different For curtailment, demand response, or long downtime: ⚠️ Do NOT boot if boards are below 0°C What to do instead: • Warm machines gradually • Monitor ambient temperature inside the facility • Physically check miners if possible Cold hardware doesn’t fail immediately. It fails later. 5️⃣ Use firmware to avoid cold-start mistakes With Braiins OS, operators rely on: • Pre-heat to bring chips closer to target temperature before hashing • Fan speed vs chip temperature to confirm miners are actually warming up If fans are low and chip temperature isn’t rising, stop and warm miners more. Booting too early is the fastest way to lose hardware. 6️⃣ Network outages can freeze miners fast When internet drops, miners stop hashing and cool down quickly. Two common safeguards: • Multiple pool fallback URLs • A drain pool as a last resort to keep miners hashing and warm Drain pools burn power, but they can prevent far more expensive cold restarts. ❄️ THE COLD TRUTH Winter punishes poor preparation and rushed decisions. We’ve been running 2+ GW of live hashpower on Braiins OS through harsh winters. The patterns repeat every year. For the full deep dive, read the complete Polar Vortex guide on our blog. Mining is hard. Braiins OS is built for this.
1:23

Bitcoin hashrate dropped ~20% in just a few days. Because extreme winter weather across the US punished weak mining operations. Here’s what actually breaks miners during a polar vortex (and how operators prepare) 👇 HOW WINTER BREAKS MINERS Cold doesn’t usually kill miners while they’re running. It kills them when: • machines cool down too fast • airflow isn’t controlled • miners restart while still cold Most damage happens during restarts and boot-ups, not steady-state hashing. HOW OPERATORS PROTECT HASHRATE 1️⃣ Control temperature swings (not just temperature) Rapid changes are the enemy. • Insulate containers and buildings to slow heat loss • Limit cold air intake until miners are hashing and warming themselves • Keep container lids closed during startup • Use hot-air feedback to warm machines gradually Goal: warm up slowly, cool down slowly. 2️⃣ Don’t let airflow work against you Airflow that’s great in summer can kill you in winter. Watch out for: • External fans pushing freezing air inside • Chimney effects that pull heat out too fast • Wide-open intakes during startup Common fixes: • Slow or pause intake fans during warm-up • Disrupt chimney effects temporarily • Use finer dust filters to reduce cold airflow Once machines are stable, airflow can come back. 3️⃣ Be careful when rebooting hashing miners Reboots in freezing temperatures are where most costly mistakes happen. Safer approach: • Reboot during the warmest part of the day • Do it one rack at a time • Keep lower shelves running so rising heat protects upper ones Rushing reboots saves minutes now and costs days later. 4️⃣ Booting miners that were offline is different For curtailment, demand response, or long downtime: ⚠️ Do NOT boot if boards are below 0°C What to do instead: • Warm machines gradually • Monitor ambient temperature inside the facility • Physically check miners if possible Cold hardware doesn’t fail immediately. It fails later. 5️⃣ Use firmware to avoid cold-start mistakes With Braiins OS, operators rely on: • Pre-heat to bring chips closer to target temperature before hashing • Fan speed vs chip temperature to confirm miners are actually warming up If fans are low and chip temperature isn’t rising, stop and warm miners more. Booting too early is the fastest way to lose hardware. 6️⃣ Network outages can freeze miners fast When internet drops, miners stop hashing and cool down quickly. Two common safeguards: • Multiple pool fallback URLs • A drain pool as a last resort to keep miners hashing and warm Drain pools burn power, but they can prevent far more expensive cold restarts. ❄️ THE COLD TRUTH Winter punishes poor preparation and rushed decisions. We’ve been running 2+ GW of live hashpower on Braiins OS through harsh winters. The patterns repeat every year. For the full deep dive, read the complete Polar Vortex guide on our blog. Mining is hard. Braiins OS is built for this.

Braiins

12,141 просмотров • 7 месяцев назад

A broken laptop on the floor of your room turns into a server that bills $1,800 a month. Total spend: $55. The machine everyone throws away is the one that works for this. Dead battery, cracked bezel, boots in 4 minutes. None of that matters when nothing has to be fast. Get one: yours from the drawer, or a retired office laptop. Dell Latitude, HP EliteBook, ThinkPad T-series, 6th to 8th gen i5. Refurbishers list them at $80 to $150. Spend $55, no more: one stick of RAM to reach 16GB, one small SSD. RAM prices are climbing, so run stock until a job actually stalls. Install it in one evening: Ubuntu Server to a USB, boot the laptop from it, walk through setup. No desktop. Ollama in one line, then a 7B model quantized to 4-bit. 6 tokens a second. Too slow to demo live. Fast enough for work that runs while the room is dark. Service 1: invoice and receipt triage. $300 a month. Sell to bookkeepers, solo accountants, small trades. They forward a folder of receipts. The box extracts vendor, amount, date, category, appends every line to a ledger, and flags anything over $500. Every entry cites its source file. Easiest sale you will make, because one wrong entry costs them more than your fee. Service 2: email drafting. $500 a month. Sell to consultants, agencies, anyone drowning in a shared inbox. The box reads the last 5 messages in a thread, classifies routine versus needs-a-human, writes a reply in their voice, saves it to Drafts. Nothing sends. They open their inbox to a folder of finished replies and approve or delete. Highest perceived value, because they watch it work every single morning. Service 3: weekly digest. $400 a month. Sell to founders and consultants with messy note systems. Sunday night, the box reads everything touched that week, writes 3 to 5 updates, flags contradictions between new notes and old ones, keeps it under 400 words. Lowest effort on your side, set up once, bills monthly. Land the first client: offer 2 weeks free on invoice triage only. Do not pitch all 3. Hand back a filled ledger with source citations, then quote $300 for month one. Upsell drafting in month two. The math: 1 client on the bundle is $1,200 a month. 2 clients on the middle tier is $1,800. The laptop draws 20 watts, so electricity is $4 regardless. Margin sits above 99%, because inference costs nothing once the machine is yours. Where it caps out: around 4 clients. Past that, the box cannot finish overnight, and you upgrade with client money, never your own. It never stops, never asks for a raise, and never sends anything you did not read.
0:54

A broken laptop on the floor of your room turns into a server that bills $1,800 a month. Total spend: $55. The machine everyone throws away is the one that works for this. Dead battery, cracked bezel, boots in 4 minutes. None of that matters when nothing has to be fast. Get one: yours from the drawer, or a retired office laptop. Dell Latitude, HP EliteBook, ThinkPad T-series, 6th to 8th gen i5. Refurbishers list them at $80 to $150. Spend $55, no more: one stick of RAM to reach 16GB, one small SSD. RAM prices are climbing, so run stock until a job actually stalls. Install it in one evening: Ubuntu Server to a USB, boot the laptop from it, walk through setup. No desktop. Ollama in one line, then a 7B model quantized to 4-bit. 6 tokens a second. Too slow to demo live. Fast enough for work that runs while the room is dark. Service 1: invoice and receipt triage. $300 a month. Sell to bookkeepers, solo accountants, small trades. They forward a folder of receipts. The box extracts vendor, amount, date, category, appends every line to a ledger, and flags anything over $500. Every entry cites its source file. Easiest sale you will make, because one wrong entry costs them more than your fee. Service 2: email drafting. $500 a month. Sell to consultants, agencies, anyone drowning in a shared inbox. The box reads the last 5 messages in a thread, classifies routine versus needs-a-human, writes a reply in their voice, saves it to Drafts. Nothing sends. They open their inbox to a folder of finished replies and approve or delete. Highest perceived value, because they watch it work every single morning. Service 3: weekly digest. $400 a month. Sell to founders and consultants with messy note systems. Sunday night, the box reads everything touched that week, writes 3 to 5 updates, flags contradictions between new notes and old ones, keeps it under 400 words. Lowest effort on your side, set up once, bills monthly. Land the first client: offer 2 weeks free on invoice triage only. Do not pitch all 3. Hand back a filled ledger with source citations, then quote $300 for month one. Upsell drafting in month two. The math: 1 client on the bundle is $1,200 a month. 2 clients on the middle tier is $1,800. The laptop draws 20 watts, so electricity is $4 regardless. Margin sits above 99%, because inference costs nothing once the machine is yours. Where it caps out: around 4 clients. Past that, the box cannot finish overnight, and you upgrade with client money, never your own. It never stops, never asks for a raise, and never sends anything you did not read.

AiMind

10,284 просмотров • 1 месяц назад

Just in $AMD Anush "Speed is the moat"|ROCm🎙️ In the race to define the future of AI, what's the one advantage that truly lasts? It's not proprietary tech, argues Anush Elangovan Elangovan, VP of AI Software at AMD , but the sustainable speed of innovation. He explains why AMD is rejecting the "walled garden" model for its open source ROCm stack, betting that an open community flywheel is the key to victory. Listen to understand how this open strategy is designed to out-innovate closed systems by empowering developers to solve everything from frontier-model challenges to the mundane, everyday problems that define the "last mile" of AI. AMD ROCm Software: Part 1 Transcript [00:00:00] Andrew Zigler: Joining me is Anush Elangovan, VP of AI software at AMD. And when people talk about AI compute, the conversation often stops at hardware specs, but it's more than just physical chips that win the game. It's also the software ecosystems supporting them. [00:00:18] Andrew Zigler: The prevailing strategy in the industry has been to build something like a walled garden. You know, something closed, proprietary locks, developers in. But AMD is betting on an entirely different play, open source acceleration, and with rock, their open source AI software stack. AMD is building not just hardware parity, but an innovation flywheel that's powered by the community with interoperability and the freedom to scale without all of that pesky lockin. [00:00:48] Andrew Zigler: And in this world, speed is your moat and how fast you can innovate while your platform remains open, flexible, and standardize across all of its applications. That's what we're gonna explore [00:01:00] today. So Anush, I'm really excited to have you here. Welcome to Dev Interrupted. [00:01:04] Anush Elangovan: Thanks for having me. Uh, super excited to chat about it. [00:01:07] Andrew Zigler: Amazing. Well, let's go ahead and dive right in with kind of what I laid it out with in the beginning, the idea of the moat and it being about speed. I wanna unpack that a bit because that came from you when you and I first spoke. And I, and I want to know, you know, how do you define speed inside of AMD beyond just things like hardware, benchmarks. [00:01:27] Anush Elangovan: Yeah, that's a very good question. So when we typically talk about speed, everyone's like, Hey, hardware benchmark specs, right? Like, uh, memory bandwidth or, or flops. And that is one important part of it, uh, AMD does very well. With that, we do have, a, a very good history of executing on that axis. [00:01:47] Anush Elangovan: But when I say speed is the moat, it is about, uh, how we prepare, how we build the muscle to run the race for a long time and run it fast. And it is [00:02:00] not about a single point in time that you've, you've beat some you know, benchmark and, and you declare victory. It's about building the ability to consistently develop and deliver. [00:02:13] Anush Elangovan: Both hardware and software innovation at scale and do it fast, right? Like, you know, we we're increasingly getting to a point where models come out and they're, uh, you know, a year or two ago it was like, Hey, they work on AMD on day zero, which is great, but now they are performing on AMD the day it releases, right? [00:02:32] Anush Elangovan: So, what does it take to Prefetch where the industry is going? Be prepared to intercept. At that point is what you know, I, I refer to as you know, the, the speed factor in, in creating this mode, right? And the mode is just shed all things that hold you back and run as fast as you can. [00:02:53] Anush Elangovan: Uh, because the pace of innovation that is, uh, being seen in, in AI [00:03:00] industries is just. Amazing. Right? And it's like, it's transformational at at how you generate electricity. It's transformational as at how you build data centers. It's transformational at how you deploy compute, networking. It's transformational at what kind of use cases you, you know, uh, use AI for. [00:03:17] Anush Elangovan: Uh, and for that, you need to be prepared to, see what comes tomorrow and be prepared to run the race tomorrow. [00:03:23] Andrew Zigler: Yeah, it's a really great perspective because it highlights that it's not just like a checkpoint that you run through. I like how you called out, like it's not just hitting that benchmark or being the best in class at that moment, in that snapshot, it's about having a. The throughput and about having that dedication to the idea and continuing to deliver on it. [00:03:43] Andrew Zigler: It's not just crossing the threshold, but it's also being the engine. And that's what, that's what protects a business. That is the moat, because the moat is that innovation layer, the faster and more, uh, future forward. That you can work and think, [00:04:00] you know, the better. Uh, we, we talk a lot about like future forward work styles. [00:04:04] Andrew Zigler: Like what are the things I could be doing right now today that are gonna be like, way more useful tomorrow? Let, let's abandon those, workflows that are older and that kind of like, that translates into. An advantage when you work that way. You know, what kind of things have you learned working with, uh, like across all spectrums of people who would use ROCm, right? [00:04:23] Andrew Zigler: You have like the developers, but then you also have the enterprises and you have this large span of adoptees, right? So what is the, what does that look like that you learn? [00:04:32] Anush Elangovan: Yeah, so, so the way I look at it is there are gonna be pockets of different, uh, you know, cadences, right? Like, so people who are deploying in enterprises, for example, right? The validation and how long it takes for them to deploy an LLM that's secure. It's, with guardrails, et cetera, maybe longer. [00:04:52] Anush Elangovan: but you still have to go through the process and you have to be prepared to like, walk that walk to deploy an enterprises. That doesn't mean it's [00:05:00] not fast, that's as fast as you can do for that industry, right? And if you are deploying AI in healthcare, right, it's, it's got its own, uh, cycle. [00:05:07] Anush Elangovan: but in each one of these, you want to see how, like, go down to the essence of what is it that you actually have to do. And, you know, I, I, I like how you framed it. It's like it's, you shed your prior assumptions of how things are done, right. And, and you kind of build up from a, uh, first principles, uh, approach to say, this is how I could use AI to unlock, whatever I'm doing. [00:05:33] Anush Elangovan: And, and, some of it, you know, it's good to really step back and look at. Just question every part of it, right? Like right now you're getting chat GPT and, Gemini competing for like, math, olympiads and, and, uh, college, uh, reasoning, uh, tests. Right? And, and those are like that, that is amazing and increasingly like complex tasks that they're trying to do. [00:05:58] Anush Elangovan: But there may also be like. [00:06:00] More mundane things that AI could, could get applied to. Right? And, and so when we think about shedding old ways, you wanna shed it not just in like the tip of the spear. It's like, you know, I'm gonna see what's the frontier model. It's also, it could be something as simple as. [00:06:18] Anush Elangovan: How do you choose a, a movie, uh, you know, like a recommendation system, right? Or, or, uh, an automated, uh, flight, uh, rebooking system. So the moment, you know, your flight is late, uh, right now it's a notification, right? It's like, oh, you got a text message saying your flight's late. And I got that like three times this week. [00:06:38] Anush Elangovan: But anyway, uh, and, and, and, and, I was just like, okay, so if I were to rethink this. All this MCPs that we have that should be hooked up into an MCP that says, your flight's delayed. Here are your options. If you want, you know, these are the paid options. Yeah. Here are the free options. This will get you back into your you know, Toronto airport [00:07:00] tonight. [00:07:00] Anush Elangovan: Or if you stay, here's a hotel plus this, plus this, plus. It's just like, go ahead is all I should say. Versus now I'm like, okay, can someone, you know, can I call a travel agent? Can I do this? Can I go online and log into And you know, so we gotta fundamentally rethink even those like small, nuances of, things that we do that can be automated out and AI is really, really good at doing something like this, right? Maybe I just explained an AI startup idea right now. Somebody should just start that. [00:07:29] Andrew Zigler: I think you did. Yeah, you definitely did. Someone, one of our listeners is definitely going to lift that off of you. I, I, I, you know, I hate being on the receiving end of those. You feel a little helpless and then you have to like, follow the whole flow. So I know what you mean. Like I, I like how you called out that the build and this like. [00:07:45] Andrew Zigler: Where speed is your moat and the innovation layer is protecting you, is what makes you better than your competitors. How you scale that and you bring that to market. So by understanding the problems that you're solving, uh, throwing away those older assumptions, but also [00:08:00] recognizing that like. We're building every single day, new things and new ways of using stuff that we're still figuring out the implications of. [00:08:08] Andrew Zigler: And so when you have a lot of velocity and you're introducing a lot of new ideas, and maybe you have that workflow now that automatically rebook your flight off of your late flight text message, and uh, I know I would certainly use it, but you know, what kind of philosophies guide the way that y'all think about building this ecosystem to manage that stability while letting folks. [00:08:29] Andrew Zigler: Play with the speed and the assumptions and the airplane re bookings. [00:08:34] Anush Elangovan: so, so I think, you know, we need to peel one layer down, right? and the philosophy is, Hey, we, we just discovered electricity, right? And you know what we're gonna do? We are gonna make motors, uh, or dynamos, right? Like engines. Uh, sure. We don't know if it's gonna be a Ferrari that you're gonna make, or it's a a a a dump truck. [00:08:57] Anush Elangovan: That's good for doing this. But let's [00:09:00] let, which is also required, right? You need a dump truck. You need a garbage truck. And, [00:09:04] Andrew Zigler: Yeah. You need the [00:09:04] Anush Elangovan: course you need, uh, a Ferrari for a midlife crisis, right? So, [00:09:09] Andrew Zigler: precisely. [00:09:10] Anush Elangovan: But, but my, uh, point is what do we build next? And, uh, and this is what I meant by like, okay, let's, let's take those baby steps to build the. [00:09:20] Anush Elangovan: Infrastructure that's required that we know we'll have to use, right? So, so if I just discovered electricity, okay, great. Now one, how do I save this electricity and how do I use it? So there's battery technology, so you need to do something like that, right? Like so. But then you also want to make it into an actionable thing. [00:09:37] Anush Elangovan: You want to make it for like automobiles, or you wanna use it for, you know, powering, uh, entire cities. So it is that transformational. So, uh, AI is that transformational. So, if you distill down, it'll, it'll come down to how do we think about, what we can do with this this fundamental technology that, We may not be aware of what it [00:10:00] is gonna unlock next, but at least you know the next step is clear, right? It's like a dense fog, you know, it's gonna be like, it, it's the right path. You see the light, but it's kind of like out there and, and the steps you're taking are concrete and you're like, okay, this is good. [00:10:16] Anush Elangovan: I, this is better than where I was or where we were. So we are moving forward. So you can build with the. Intuition from what you see in the short term and a tactical view, but towards what you think the future is gonna be. [00:10:28] Andrew Zigler: Right. You almost like we're all in this like fog of war, right? And like you said, you're reaching out and you're trying to step through it. You could think of it too, as like you're in the dark and your hands are up in front of you and you know that. You're, you're not gonna run your face into a wall because your hands are out in front of you, but you're not gonna maybe do much better than that. [00:10:45] Andrew Zigler: So that's kind of like, I think the eco, the, the industry, the world that we find ourselves in, uh, and we all have to, then this becomes the power of an ecosystem, of a group of people working together to create that layer of, [00:11:00] uh, of establishing the [00:11:01] Anush Elangovan: exactly. And I, I, I just, instead of, you know, saying fog of war I describe it as like, you're in this. Beautiful valley with like a morning, uh, fog that's in. You can smell the flowers. You, you hear the birds. You are like, okay, it's, we are in like, uh, utopian paradise and yes, I just need to like, continue the walk, right? [00:11:24] Anush Elangovan: and then move forward with that, conviction that you're in the right spot. [00:11:27] Andrew Zigler: Yeah. So let's talk about that ecosystem world. This nice, I love how you describe it, this grassy side of a hill in the morning that's covered in some mist and maybe we can't see 30 feet in one direction, but it sure is a beautiful hill and it smells nice. And so we're all here. And why is, in that world, why is. [00:11:44] Andrew Zigler: You know, open source, their strategic advantage that y'all are going for in the AI hardware market. And, and then how does like ROCm turn that into wins for people within that ecosystem? [00:11:56] Anush Elangovan: you know, the, the way we look at it is this, is kind of like how I view [00:12:00] AI and the ecosystem, right? But, but it is for everyone to enjoy. Uh, and so we do want to make sure that. You know, it is, uh, beneficial for everyone. [00:12:09] Anush Elangovan: The ecosystem can come in and, and innovate. It's an open innovation engine. and uh, it is very different from, you know, having a walled garden with, Hey, only I know how to do this and I'm gonna do it and throw it over the fence and you can use it or keep walking, right? So we'd like to be good citizens that way, but also. [00:12:30] Anush Elangovan: Uh, it is self-fulfilling in a way, right? Like it, the, the pace at which we innovate with open source is unmatched. Like, you know, our serving engines are like VLLM and, and sg l. Those things, uh, those frameworks are like super, super aggressive in terms of how fast they come out with features and how fast they can you know, get performant models out. [00:12:52] Anush Elangovan: And that compared with what, uh, you'd get from, you know, the likes of like T-R-T-L-L-M or something is always lagging, right? Because you [00:13:00] just can't keep up with you know, 200 commits a week just on one particular model to get that model really performant [00:13:06] Andrew Zigler: And, and, and in that world where, you know, everyone can enjoy the winds of this, what kind of customer stories or innovation stories have really stood out to you and excite you about building and creating this place for developers? [00:13:19] Anush Elangovan: Yeah. So I think the parts that are super exciting for me are when when we get to see a customer that is first skeptical. Then they start a little like, okay, fine, we'll give you a chance. Uh, we do a simple, uh, POC and then they're like, huh, this seems to work. Yeah, we told you it works. [00:13:42] Anush Elangovan: You don't have to change one line of code. Really? Yes, no need to change one line of code. Okay, let's try a production workload. So then they try it. Oh, you're more performant than the competition. Yes. We're more performant than, than the competition. So how much does it cost? And we're like, oh, it's your TCO is better with, uh, [00:14:00] AMD. [00:14:00] Anush Elangovan: So again, they're like, wow, okay, good. So now how do we deploy at scale? And then we go deploy it at scale. And when they give a thumbs up on that and they say, this is good, right? That's when you know, you, you see it go full circle from like, oh, we, we've never heard about AMD to like actually deploy to tens of thousands of GPUs In the order of a few months, right? It, it, it really is fascinating to see and very exciting and invigorating to [00:14:28] Andrew Zigler: Yeah. At like a great exposure to a lot of interesting problems. And, and then people using the infrastructure, the, the technology available to solve those problems. Really specific problems by the way, that's often why they're bringing their data and AI to it, uh, is because it is really specific and important for them. [00:14:45] Andrew Zigler: And there's a, a lot I think that other engineering orgs can learn and even emulate from AMD's success and, and having this open source ecosystem and it causing this acceleration within. You [00:15:00] know, uh, customers and enterprises that use and adopt the tools and, and, and that creates an advantage. And that goes back to why we're talking and like the real thesis of our conversation today. [00:15:10] Andrew Zigler: So how do you think engineering leaders that are listening to this and obviously tapping into this great success AMD has from an open source flywheel, how do you think other, other folks building in the same space can foster that open, first, that open source oriented culture in order to, you know, accelerate their innovation goals? [00:15:29] Anush Elangovan: Yeah, that's a very good question. So the startup that um, was acquired by AMD we, we built, I mean, we started off doing iot stuff and you know, smart ring and all that, right? But in the, the end of like, uh, and not the end, the last six years of the company was building ML compilers. [00:15:47] Anush Elangovan: And ml, ML compilers are like super, uh, complicated, sophisticated, advanced algorithms, dah, dah, dah. but it was all open source, right? So our VCs were like, wait, what do you mean your core [00:16:00] IP is open source? And um, the speed is the moat applied even then, right? It was just like, yes, if you have an idea that. [00:16:08] Anush Elangovan: Because someone saw this idea that you are, they're gonna be able to catch up, then you probably have the wrong idea anyway. But if they are, you know, you execute and they're gonna catch up, that you should assume they're gonna catch up. Right? So you gotta move forward. So keeping it open source is super important. [00:16:25] Anush Elangovan: But also to your question on like, you know, the learnings from an AMD standpoint, right? If there are, hard problems, I'd say dig in and work through it, right? Like there's no way but through it, right? That should be the simple mentality. And more, uh, frequently than not. you'll see that you'll just make it through in a, in, in good form. [00:16:52] Anush Elangovan: But if you doubt it and you're like, oh, I don't know if I should commit, if I'm, I, you know, what should just commit to do the right thing [00:17:00] every step, right? Every step, and just keep taking one step in front of the other. And in no time you'll see that you'll be running. Right. And, and yes, the first few steps will be like, yeah, everyone's complaining about your software quality. [00:17:15] Anush Elangovan: Everyone's complaining about this and that, and it doesn't work. And, and a few steps in, you know, you get, you get the hang of all the complaints that are coming in. You get the feedback loop. You're like, okay, what, what are you prioritizing again? One step in front of the other, right? You just keep knocking that out and then you get to a point where you're, it just becomes second nature, right? To do the, to do the right thing. And, and then yes, if someone gives you two options, you'll be like, fine. This is, uh, you know, there's always the resource trade off. There's always a human capital trade off, but what's the right thing to do? of course, I, I'm pragmatic about what we choose, but, but if the right thing for your long-term success is dig in, go first, principles, make it [00:18:00] happen. [00:18:00] Anush Elangovan: Well. Then just go for that. There's, there is no shortcut to [00:18:04] Andrew Zigler: acknowledging, you know, how it aligns with your mission, your core company goals, and what you're looking to achieve. And, and I, I love how you rightfully called out that in the open source world and you know, you have your technology that you've built, what you think is your moat upon, right? [00:18:22] Andrew Zigler: It's your code and, and to open source that, or to just make it where anyone could peer in is, you know. Scary in one regard, but two, it just kind of feels like you're handing away your throne room in some kind of sense, a very direct feeling sense. But the ultimately, you were really right to call out, and this is something I think about all the time, that the real power there is still the speed This the speed. [00:18:42] Andrew Zigler: That was the moat at the beginning of our conversation. It's the speed in combination with your. Very specific domain understanding of what you're building and what you're creating, and your new role as the steward of that world and how people plug into it, which [00:19:00] has frankly, a lot more influence and power than lording over a closed. [00:19:04] Andrew Zigler: You know, repository or an ecosystem, and like you said, like throwing things over the wall. Sure. There, there might be people always on the other side of that wall, but you're not gonna have a great connection with them. You're not gonna be able to really clearly understand them. I, I like your metaphor of the side of the field of the mountain a lot more. [00:19:23] Andrew Zigler: But, but in the, in this world, you know, where. That speed is, is the power and, and open source is just one way that you can harness that speed to get really far ahead and to innovate. , There's other parts of this equation that you can be experimenting with too, and I'd love to pick your brain about them as a software leader and, and, and one of them is about looking forward and kind of understanding that future that we're all building towards and beyond today's models and hardware. [00:19:48] Andrew Zigler: You know, what do you see as the next major bottleneck or opportunity in the AI compute space? As, as you know, enterprises and folks start to get a little more mature about what's available to [00:20:00] them. [00:20:00] Anush Elangovan: Yeah, I think, the bottleneck and opportunity is, uh, what I'd call, call walking the last mile of ai. Right. Uh, and like I I, I gave you an example, uh, previously, but, but it's similar to that. It's like there are cases where Humans have so many, uh, things to do in your day. You know, like the, if we sit down and actually had a customer focus like, okay, these customers lives, I'm gonna save four hours of this customer's life. And if you actually sit down and look at all of that, it'll be. Easily automatable, easily you know, uh, applicable, uh, for ai, right? [00:20:39] Anush Elangovan: Like, but then making it happen is gonna take a little bit, right? It's like maybe it's, uh, paying your utility bill, right? Or something like that, right? Or, or, your healthcare explanation of benefits. Uh, like, I'm sure you get an explanation of benefits, and I'm like, I, I don't even know what that thing is. [00:20:55] Anush Elangovan: It's just like EOB and like. [00:20:57] Andrew Zigler: it's a big, a big old PDF. Yeah, [00:21:00] exactly. [00:21:01] Anush Elangovan: Like, like, I'm like great straight to the, uh, shredder, right? And but that could be, you know, automated with the ai, right? It, it, it'd be like, Hey, the summary of this thing is you went and visited this day. Everything is okay. Everything is paid for, so don't worry, it's not a bill. [00:21:17] Anush Elangovan: That again, the same, uh, thing, but the sense of what that information overload is could be. Digested by ai, uh, accumulated over time and retrieved when you need it. Like, I don't, I actually don't even need to know this EOB right now, unless of course, whenever I need to know it, that maybe, you know, like for some benefits I need to figure out what do, what did I do over the past year and how do I apply it? Source:
31:35

Just in $AMD Anush "Speed is the moat"|ROCm🎙️ In the race to define the future of AI, what's the one advantage that truly lasts? It's not proprietary tech, argues Anush Elangovan Elangovan, VP of AI Software at AMD , but the sustainable speed of innovation. He explains why AMD is rejecting the "walled garden" model for its open source ROCm stack, betting that an open community flywheel is the key to victory. Listen to understand how this open strategy is designed to out-innovate closed systems by empowering developers to solve everything from frontier-model challenges to the mundane, everyday problems that define the "last mile" of AI. AMD ROCm Software: Part 1 Transcript [00:00:00] Andrew Zigler: Joining me is Anush Elangovan, VP of AI software at AMD. And when people talk about AI compute, the conversation often stops at hardware specs, but it's more than just physical chips that win the game. It's also the software ecosystems supporting them. [00:00:18] Andrew Zigler: The prevailing strategy in the industry has been to build something like a walled garden. You know, something closed, proprietary locks, developers in. But AMD is betting on an entirely different play, open source acceleration, and with rock, their open source AI software stack. AMD is building not just hardware parity, but an innovation flywheel that's powered by the community with interoperability and the freedom to scale without all of that pesky lockin. [00:00:48] Andrew Zigler: And in this world, speed is your moat and how fast you can innovate while your platform remains open, flexible, and standardize across all of its applications. That's what we're gonna explore [00:01:00] today. So Anush, I'm really excited to have you here. Welcome to Dev Interrupted. [00:01:04] Anush Elangovan: Thanks for having me. Uh, super excited to chat about it. [00:01:07] Andrew Zigler: Amazing. Well, let's go ahead and dive right in with kind of what I laid it out with in the beginning, the idea of the moat and it being about speed. I wanna unpack that a bit because that came from you when you and I first spoke. And I, and I want to know, you know, how do you define speed inside of AMD beyond just things like hardware, benchmarks. [00:01:27] Anush Elangovan: Yeah, that's a very good question. So when we typically talk about speed, everyone's like, Hey, hardware benchmark specs, right? Like, uh, memory bandwidth or, or flops. And that is one important part of it, uh, AMD does very well. With that, we do have, a, a very good history of executing on that axis. [00:01:47] Anush Elangovan: But when I say speed is the moat, it is about, uh, how we prepare, how we build the muscle to run the race for a long time and run it fast. And it is [00:02:00] not about a single point in time that you've, you've beat some you know, benchmark and, and you declare victory. It's about building the ability to consistently develop and deliver. [00:02:13] Anush Elangovan: Both hardware and software innovation at scale and do it fast, right? Like, you know, we we're increasingly getting to a point where models come out and they're, uh, you know, a year or two ago it was like, Hey, they work on AMD on day zero, which is great, but now they are performing on AMD the day it releases, right? [00:02:32] Anush Elangovan: So, what does it take to Prefetch where the industry is going? Be prepared to intercept. At that point is what you know, I, I refer to as you know, the, the speed factor in, in creating this mode, right? And the mode is just shed all things that hold you back and run as fast as you can. [00:02:53] Anush Elangovan: Uh, because the pace of innovation that is, uh, being seen in, in AI [00:03:00] industries is just. Amazing. Right? And it's like, it's transformational at at how you generate electricity. It's transformational as at how you build data centers. It's transformational at how you deploy compute, networking. It's transformational at what kind of use cases you, you know, uh, use AI for. [00:03:17] Anush Elangovan: Uh, and for that, you need to be prepared to, see what comes tomorrow and be prepared to run the race tomorrow. [00:03:23] Andrew Zigler: Yeah, it's a really great perspective because it highlights that it's not just like a checkpoint that you run through. I like how you called out, like it's not just hitting that benchmark or being the best in class at that moment, in that snapshot, it's about having a. The throughput and about having that dedication to the idea and continuing to deliver on it. [00:03:43] Andrew Zigler: It's not just crossing the threshold, but it's also being the engine. And that's what, that's what protects a business. That is the moat, because the moat is that innovation layer, the faster and more, uh, future forward. That you can work and think, [00:04:00] you know, the better. Uh, we, we talk a lot about like future forward work styles. [00:04:04] Andrew Zigler: Like what are the things I could be doing right now today that are gonna be like, way more useful tomorrow? Let, let's abandon those, workflows that are older and that kind of like, that translates into. An advantage when you work that way. You know, what kind of things have you learned working with, uh, like across all spectrums of people who would use ROCm, right? [00:04:23] Andrew Zigler: You have like the developers, but then you also have the enterprises and you have this large span of adoptees, right? So what is the, what does that look like that you learn? [00:04:32] Anush Elangovan: Yeah, so, so the way I look at it is there are gonna be pockets of different, uh, you know, cadences, right? Like, so people who are deploying in enterprises, for example, right? The validation and how long it takes for them to deploy an LLM that's secure. It's, with guardrails, et cetera, maybe longer. [00:04:52] Anush Elangovan: but you still have to go through the process and you have to be prepared to like, walk that walk to deploy an enterprises. That doesn't mean it's [00:05:00] not fast, that's as fast as you can do for that industry, right? And if you are deploying AI in healthcare, right, it's, it's got its own, uh, cycle. [00:05:07] Anush Elangovan: but in each one of these, you want to see how, like, go down to the essence of what is it that you actually have to do. And, you know, I, I, I like how you framed it. It's like it's, you shed your prior assumptions of how things are done, right. And, and you kind of build up from a, uh, first principles, uh, approach to say, this is how I could use AI to unlock, whatever I'm doing. [00:05:33] Anush Elangovan: And, and, some of it, you know, it's good to really step back and look at. Just question every part of it, right? Like right now you're getting chat GPT and, Gemini competing for like, math, olympiads and, and, uh, college, uh, reasoning, uh, tests. Right? And, and those are like that, that is amazing and increasingly like complex tasks that they're trying to do. [00:05:58] Anush Elangovan: But there may also be like. [00:06:00] More mundane things that AI could, could get applied to. Right? And, and so when we think about shedding old ways, you wanna shed it not just in like the tip of the spear. It's like, you know, I'm gonna see what's the frontier model. It's also, it could be something as simple as. [00:06:18] Anush Elangovan: How do you choose a, a movie, uh, you know, like a recommendation system, right? Or, or, uh, an automated, uh, flight, uh, rebooking system. So the moment, you know, your flight is late, uh, right now it's a notification, right? It's like, oh, you got a text message saying your flight's late. And I got that like three times this week. [00:06:38] Anush Elangovan: But anyway, uh, and, and, and, and, I was just like, okay, so if I were to rethink this. All this MCPs that we have that should be hooked up into an MCP that says, your flight's delayed. Here are your options. If you want, you know, these are the paid options. Yeah. Here are the free options. This will get you back into your you know, Toronto airport [00:07:00] tonight. [00:07:00] Anush Elangovan: Or if you stay, here's a hotel plus this, plus this, plus. It's just like, go ahead is all I should say. Versus now I'm like, okay, can someone, you know, can I call a travel agent? Can I do this? Can I go online and log into And you know, so we gotta fundamentally rethink even those like small, nuances of, things that we do that can be automated out and AI is really, really good at doing something like this, right? Maybe I just explained an AI startup idea right now. Somebody should just start that. [00:07:29] Andrew Zigler: I think you did. Yeah, you definitely did. Someone, one of our listeners is definitely going to lift that off of you. I, I, I, you know, I hate being on the receiving end of those. You feel a little helpless and then you have to like, follow the whole flow. So I know what you mean. Like I, I like how you called out that the build and this like. [00:07:45] Andrew Zigler: Where speed is your moat and the innovation layer is protecting you, is what makes you better than your competitors. How you scale that and you bring that to market. So by understanding the problems that you're solving, uh, throwing away those older assumptions, but also [00:08:00] recognizing that like. We're building every single day, new things and new ways of using stuff that we're still figuring out the implications of. [00:08:08] Andrew Zigler: And so when you have a lot of velocity and you're introducing a lot of new ideas, and maybe you have that workflow now that automatically rebook your flight off of your late flight text message, and uh, I know I would certainly use it, but you know, what kind of philosophies guide the way that y'all think about building this ecosystem to manage that stability while letting folks. [00:08:29] Andrew Zigler: Play with the speed and the assumptions and the airplane re bookings. [00:08:34] Anush Elangovan: so, so I think, you know, we need to peel one layer down, right? and the philosophy is, Hey, we, we just discovered electricity, right? And you know what we're gonna do? We are gonna make motors, uh, or dynamos, right? Like engines. Uh, sure. We don't know if it's gonna be a Ferrari that you're gonna make, or it's a a a a dump truck. [00:08:57] Anush Elangovan: That's good for doing this. But let's [00:09:00] let, which is also required, right? You need a dump truck. You need a garbage truck. And, [00:09:04] Andrew Zigler: Yeah. You need the [00:09:04] Anush Elangovan: course you need, uh, a Ferrari for a midlife crisis, right? So, [00:09:09] Andrew Zigler: precisely. [00:09:10] Anush Elangovan: But, but my, uh, point is what do we build next? And, uh, and this is what I meant by like, okay, let's, let's take those baby steps to build the. [00:09:20] Anush Elangovan: Infrastructure that's required that we know we'll have to use, right? So, so if I just discovered electricity, okay, great. Now one, how do I save this electricity and how do I use it? So there's battery technology, so you need to do something like that, right? Like so. But then you also want to make it into an actionable thing. [00:09:37] Anush Elangovan: You want to make it for like automobiles, or you wanna use it for, you know, powering, uh, entire cities. So it is that transformational. So, uh, AI is that transformational. So, if you distill down, it'll, it'll come down to how do we think about, what we can do with this this fundamental technology that, We may not be aware of what it [00:10:00] is gonna unlock next, but at least you know the next step is clear, right? It's like a dense fog, you know, it's gonna be like, it, it's the right path. You see the light, but it's kind of like out there and, and the steps you're taking are concrete and you're like, okay, this is good. [00:10:16] Anush Elangovan: I, this is better than where I was or where we were. So we are moving forward. So you can build with the. Intuition from what you see in the short term and a tactical view, but towards what you think the future is gonna be. [00:10:28] Andrew Zigler: Right. You almost like we're all in this like fog of war, right? And like you said, you're reaching out and you're trying to step through it. You could think of it too, as like you're in the dark and your hands are up in front of you and you know that. You're, you're not gonna run your face into a wall because your hands are out in front of you, but you're not gonna maybe do much better than that. [00:10:45] Andrew Zigler: So that's kind of like, I think the eco, the, the industry, the world that we find ourselves in, uh, and we all have to, then this becomes the power of an ecosystem, of a group of people working together to create that layer of, [00:11:00] uh, of establishing the [00:11:01] Anush Elangovan: exactly. And I, I, I just, instead of, you know, saying fog of war I describe it as like, you're in this. Beautiful valley with like a morning, uh, fog that's in. You can smell the flowers. You, you hear the birds. You are like, okay, it's, we are in like, uh, utopian paradise and yes, I just need to like, continue the walk, right? [00:11:24] Anush Elangovan: and then move forward with that, conviction that you're in the right spot. [00:11:27] Andrew Zigler: Yeah. So let's talk about that ecosystem world. This nice, I love how you describe it, this grassy side of a hill in the morning that's covered in some mist and maybe we can't see 30 feet in one direction, but it sure is a beautiful hill and it smells nice. And so we're all here. And why is, in that world, why is. [00:11:44] Andrew Zigler: You know, open source, their strategic advantage that y'all are going for in the AI hardware market. And, and then how does like ROCm turn that into wins for people within that ecosystem? [00:11:56] Anush Elangovan: you know, the, the way we look at it is this, is kind of like how I view [00:12:00] AI and the ecosystem, right? But, but it is for everyone to enjoy. Uh, and so we do want to make sure that. You know, it is, uh, beneficial for everyone. [00:12:09] Anush Elangovan: The ecosystem can come in and, and innovate. It's an open innovation engine. and uh, it is very different from, you know, having a walled garden with, Hey, only I know how to do this and I'm gonna do it and throw it over the fence and you can use it or keep walking, right? So we'd like to be good citizens that way, but also. [00:12:30] Anush Elangovan: Uh, it is self-fulfilling in a way, right? Like it, the, the pace at which we innovate with open source is unmatched. Like, you know, our serving engines are like VLLM and, and sg l. Those things, uh, those frameworks are like super, super aggressive in terms of how fast they come out with features and how fast they can you know, get performant models out. [00:12:52] Anush Elangovan: And that compared with what, uh, you'd get from, you know, the likes of like T-R-T-L-L-M or something is always lagging, right? Because you [00:13:00] just can't keep up with you know, 200 commits a week just on one particular model to get that model really performant [00:13:06] Andrew Zigler: And, and, and in that world where, you know, everyone can enjoy the winds of this, what kind of customer stories or innovation stories have really stood out to you and excite you about building and creating this place for developers? [00:13:19] Anush Elangovan: Yeah. So I think the parts that are super exciting for me are when when we get to see a customer that is first skeptical. Then they start a little like, okay, fine, we'll give you a chance. Uh, we do a simple, uh, POC and then they're like, huh, this seems to work. Yeah, we told you it works. [00:13:42] Anush Elangovan: You don't have to change one line of code. Really? Yes, no need to change one line of code. Okay, let's try a production workload. So then they try it. Oh, you're more performant than the competition. Yes. We're more performant than, than the competition. So how much does it cost? And we're like, oh, it's your TCO is better with, uh, [00:14:00] AMD. [00:14:00] Anush Elangovan: So again, they're like, wow, okay, good. So now how do we deploy at scale? And then we go deploy it at scale. And when they give a thumbs up on that and they say, this is good, right? That's when you know, you, you see it go full circle from like, oh, we, we've never heard about AMD to like actually deploy to tens of thousands of GPUs In the order of a few months, right? It, it, it really is fascinating to see and very exciting and invigorating to [00:14:28] Andrew Zigler: Yeah. At like a great exposure to a lot of interesting problems. And, and then people using the infrastructure, the, the technology available to solve those problems. Really specific problems by the way, that's often why they're bringing their data and AI to it, uh, is because it is really specific and important for them. [00:14:45] Andrew Zigler: And there's a, a lot I think that other engineering orgs can learn and even emulate from AMD's success and, and having this open source ecosystem and it causing this acceleration within. You [00:15:00] know, uh, customers and enterprises that use and adopt the tools and, and, and that creates an advantage. And that goes back to why we're talking and like the real thesis of our conversation today. [00:15:10] Andrew Zigler: So how do you think engineering leaders that are listening to this and obviously tapping into this great success AMD has from an open source flywheel, how do you think other, other folks building in the same space can foster that open, first, that open source oriented culture in order to, you know, accelerate their innovation goals? [00:15:29] Anush Elangovan: Yeah, that's a very good question. So the startup that um, was acquired by AMD we, we built, I mean, we started off doing iot stuff and you know, smart ring and all that, right? But in the, the end of like, uh, and not the end, the last six years of the company was building ML compilers. [00:15:47] Anush Elangovan: And ml, ML compilers are like super, uh, complicated, sophisticated, advanced algorithms, dah, dah, dah. but it was all open source, right? So our VCs were like, wait, what do you mean your core [00:16:00] IP is open source? And um, the speed is the moat applied even then, right? It was just like, yes, if you have an idea that. [00:16:08] Anush Elangovan: Because someone saw this idea that you are, they're gonna be able to catch up, then you probably have the wrong idea anyway. But if they are, you know, you execute and they're gonna catch up, that you should assume they're gonna catch up. Right? So you gotta move forward. So keeping it open source is super important. [00:16:25] Anush Elangovan: But also to your question on like, you know, the learnings from an AMD standpoint, right? If there are, hard problems, I'd say dig in and work through it, right? Like there's no way but through it, right? That should be the simple mentality. And more, uh, frequently than not. you'll see that you'll just make it through in a, in, in good form. [00:16:52] Anush Elangovan: But if you doubt it and you're like, oh, I don't know if I should commit, if I'm, I, you know, what should just commit to do the right thing [00:17:00] every step, right? Every step, and just keep taking one step in front of the other. And in no time you'll see that you'll be running. Right. And, and yes, the first few steps will be like, yeah, everyone's complaining about your software quality. [00:17:15] Anush Elangovan: Everyone's complaining about this and that, and it doesn't work. And, and a few steps in, you know, you get, you get the hang of all the complaints that are coming in. You get the feedback loop. You're like, okay, what, what are you prioritizing again? One step in front of the other, right? You just keep knocking that out and then you get to a point where you're, it just becomes second nature, right? To do the, to do the right thing. And, and then yes, if someone gives you two options, you'll be like, fine. This is, uh, you know, there's always the resource trade off. There's always a human capital trade off, but what's the right thing to do? of course, I, I'm pragmatic about what we choose, but, but if the right thing for your long-term success is dig in, go first, principles, make it [00:18:00] happen. [00:18:00] Anush Elangovan: Well. Then just go for that. There's, there is no shortcut to [00:18:04] Andrew Zigler: acknowledging, you know, how it aligns with your mission, your core company goals, and what you're looking to achieve. And, and I, I love how you rightfully called out that in the open source world and you know, you have your technology that you've built, what you think is your moat upon, right? [00:18:22] Andrew Zigler: It's your code and, and to open source that, or to just make it where anyone could peer in is, you know. Scary in one regard, but two, it just kind of feels like you're handing away your throne room in some kind of sense, a very direct feeling sense. But the ultimately, you were really right to call out, and this is something I think about all the time, that the real power there is still the speed This the speed. [00:18:42] Andrew Zigler: That was the moat at the beginning of our conversation. It's the speed in combination with your. Very specific domain understanding of what you're building and what you're creating, and your new role as the steward of that world and how people plug into it, which [00:19:00] has frankly, a lot more influence and power than lording over a closed. [00:19:04] Andrew Zigler: You know, repository or an ecosystem, and like you said, like throwing things over the wall. Sure. There, there might be people always on the other side of that wall, but you're not gonna have a great connection with them. You're not gonna be able to really clearly understand them. I, I like your metaphor of the side of the field of the mountain a lot more. [00:19:23] Andrew Zigler: But, but in the, in this world, you know, where. That speed is, is the power and, and open source is just one way that you can harness that speed to get really far ahead and to innovate. , There's other parts of this equation that you can be experimenting with too, and I'd love to pick your brain about them as a software leader and, and, and one of them is about looking forward and kind of understanding that future that we're all building towards and beyond today's models and hardware. [00:19:48] Andrew Zigler: You know, what do you see as the next major bottleneck or opportunity in the AI compute space? As, as you know, enterprises and folks start to get a little more mature about what's available to [00:20:00] them. [00:20:00] Anush Elangovan: Yeah, I think, the bottleneck and opportunity is, uh, what I'd call, call walking the last mile of ai. Right. Uh, and like I I, I gave you an example, uh, previously, but, but it's similar to that. It's like there are cases where Humans have so many, uh, things to do in your day. You know, like the, if we sit down and actually had a customer focus like, okay, these customers lives, I'm gonna save four hours of this customer's life. And if you actually sit down and look at all of that, it'll be. Easily automatable, easily you know, uh, applicable, uh, for ai, right? [00:20:39] Anush Elangovan: Like, but then making it happen is gonna take a little bit, right? It's like maybe it's, uh, paying your utility bill, right? Or something like that, right? Or, or, your healthcare explanation of benefits. Uh, like, I'm sure you get an explanation of benefits, and I'm like, I, I don't even know what that thing is. [00:20:55] Anush Elangovan: It's just like EOB and like. [00:20:57] Andrew Zigler: it's a big, a big old PDF. Yeah, [00:21:00] exactly. [00:21:01] Anush Elangovan: Like, like, I'm like great straight to the, uh, shredder, right? And but that could be, you know, automated with the ai, right? It, it, it'd be like, Hey, the summary of this thing is you went and visited this day. Everything is okay. Everything is paid for, so don't worry, it's not a bill. [00:21:17] Anush Elangovan: That again, the same, uh, thing, but the sense of what that information overload is could be. Digested by ai, uh, accumulated over time and retrieved when you need it. Like, I don't, I actually don't even need to know this EOB right now, unless of course, whenever I need to know it, that maybe, you know, like for some benefits I need to figure out what do, what did I do over the past year and how do I apply it? Source:

Mike

15,145 просмотров • 9 месяцев назад

** Sega Genesis 3D Engine Update 8 ** Significant improvements all round as you can see and hear from the last update !! Foremost - A huge thanks to Toni Gálvez - Megastyle - BG. who has joined the project to create a bit of 16bit low poly magic. Toni's an Amiga fan but also crazy about game dev in general, he's worked on GBC, GBA, PC, MD, PSP, C64, CPC, MSX... and others. Gaming titles include War Times, Metal Gear, Rocketman, Tintin & Asterix to name a few. He's provided the great new ship model you see on screen - new striped buildings, all the backgrounds / palettes etc. There's a lot of models he's given me which need to be added, also he will be planning a lot of the level design. Very happy to have him help me turn this into something more than a tech demo as I have my hands tied pushing the MD as far as it can go haha - there is no cpu cycle to be spared. Also many thanks to my good friend CYBERDEOUS - Crouzet Laurent for the Music for this showing , I wanted to have the music load occurring so we have a realistic benchmark for performance and he was only too obliging. If you're into MD chiptunes check him out !! Since last update : New player model , substantially more detailed than the Arwing. Last update had a 23 triangle Arwing , this update has a 39 triangle custom model from Toni. We had several to choose from , others will be used for enemies . 3D Buffer size increased 25% to 256x160. This was quite tricky as I'm close to the DMA limit even with an extended vblank . Spent a few days thinking of how to do this as like anything retro every solution has a drawback, finally got a workable solution. It makes a big difference to have a bit more vertical height . Z Rotation added ( the screen tilting left to right ) , small hit to vertex transform on cpu thanks to look up tables doing the heavy lifting, saving 4 multiplies per vertex. Multiple speed ups in rendering code. Onscreen paths with no range checking used until Z is close enough to cause clipping , partial onscreen drawing pathes that need to check boundaries, quad rendering completely rewritten - was very very painfull to get right . I found out the hard way that things are great when they are not rotating in the Z axis haha . Partial buffer draw optimisations - which have helped with the massive dma load , sending up to a 20kb buffer in a single frame needs a lot of optimisation. Min / Max tile lines are analysed and only sent if dirtied , reducing most buffer swaps substantially. Still some issues to sort out , at times you can see the flicker near top of screen when frames are near full height . I need to optimise that a bit. Due to the onscreen buffer system a full Sprite background had to be implemented almost Neo Geo style. This flips the usual MD rendering system on its head as it uses both foreground and background layers for a foreground 3d plane and sprites for the background. This presents a few issues, one is to get a tilt effect on the background by using narrow sprites (16x32) we run out of sprites when trying to cover the screen. Thankfully the MD is not limited to 80 sprites, to fix this a 114 sprite multiplexor is used to draw the background, its completely made up of 16x32 sprites ! Why do things this way ? speed . Its the interleaved foreground/background layers that allow a double buffered ram system writing to write to vram using dma in a completely linear fashion - virtually no tile translation needed. The negative is you have no planes for the background, that's where the sprites come in . Thanks to H40 mode we still have a few sprites we can use for effects in the forground also . Thankfully we can implement a fairly good tilt still for the background using sprites, in future updates this will be able to move horizontally also and a bit of vertical movement. XGM1 music driver in use to simulate music cpu load, XGM2 unfortunately with the massive DMA needed to shift the 3d buffers would slow down at times rendering it unusable, XGM1 plays at full speed - albiet with a bit more of a cpu hit. Together with the sprite multiplexor and the music driver active theres a 10 % hit to cpu so I've had to play around with draw distances / object heights and other optimisations to offset that. Not to mention the larger buffer takes more cpu to fill also. Everything is placeholder so will be changed with proper stage design. We are averaging 20 FPS in the current video, I'll push for more as always !! Progress continues on my other projects , updates soon on those - retirement can't come quick enough . #SGDK #SegaGenesis #SegaMegadrive
1:17

** Sega Genesis 3D Engine Update 8 ** Significant improvements all round as you can see and hear from the last update !! Foremost - A huge thanks to Toni Gálvez - Megastyle - BG. who has joined the project to create a bit of 16bit low poly magic. Toni's an Amiga fan but also crazy about game dev in general, he's worked on GBC, GBA, PC, MD, PSP, C64, CPC, MSX... and others. Gaming titles include War Times, Metal Gear, Rocketman, Tintin & Asterix to name a few. He's provided the great new ship model you see on screen - new striped buildings, all the backgrounds / palettes etc. There's a lot of models he's given me which need to be added, also he will be planning a lot of the level design. Very happy to have him help me turn this into something more than a tech demo as I have my hands tied pushing the MD as far as it can go haha - there is no cpu cycle to be spared. Also many thanks to my good friend CYBERDEOUS - Crouzet Laurent for the Music for this showing , I wanted to have the music load occurring so we have a realistic benchmark for performance and he was only too obliging. If you're into MD chiptunes check him out !! Since last update : New player model , substantially more detailed than the Arwing. Last update had a 23 triangle Arwing , this update has a 39 triangle custom model from Toni. We had several to choose from , others will be used for enemies . 3D Buffer size increased 25% to 256x160. This was quite tricky as I'm close to the DMA limit even with an extended vblank . Spent a few days thinking of how to do this as like anything retro every solution has a drawback, finally got a workable solution. It makes a big difference to have a bit more vertical height . Z Rotation added ( the screen tilting left to right ) , small hit to vertex transform on cpu thanks to look up tables doing the heavy lifting, saving 4 multiplies per vertex. Multiple speed ups in rendering code. Onscreen paths with no range checking used until Z is close enough to cause clipping , partial onscreen drawing pathes that need to check boundaries, quad rendering completely rewritten - was very very painfull to get right . I found out the hard way that things are great when they are not rotating in the Z axis haha . Partial buffer draw optimisations - which have helped with the massive dma load , sending up to a 20kb buffer in a single frame needs a lot of optimisation. Min / Max tile lines are analysed and only sent if dirtied , reducing most buffer swaps substantially. Still some issues to sort out , at times you can see the flicker near top of screen when frames are near full height . I need to optimise that a bit. Due to the onscreen buffer system a full Sprite background had to be implemented almost Neo Geo style. This flips the usual MD rendering system on its head as it uses both foreground and background layers for a foreground 3d plane and sprites for the background. This presents a few issues, one is to get a tilt effect on the background by using narrow sprites (16x32) we run out of sprites when trying to cover the screen. Thankfully the MD is not limited to 80 sprites, to fix this a 114 sprite multiplexor is used to draw the background, its completely made up of 16x32 sprites ! Why do things this way ? speed . Its the interleaved foreground/background layers that allow a double buffered ram system writing to write to vram using dma in a completely linear fashion - virtually no tile translation needed. The negative is you have no planes for the background, that's where the sprites come in . Thanks to H40 mode we still have a few sprites we can use for effects in the forground also . Thankfully we can implement a fairly good tilt still for the background using sprites, in future updates this will be able to move horizontally also and a bit of vertical movement. XGM1 music driver in use to simulate music cpu load, XGM2 unfortunately with the massive DMA needed to shift the 3d buffers would slow down at times rendering it unusable, XGM1 plays at full speed - albiet with a bit more of a cpu hit. Together with the sprite multiplexor and the music driver active theres a 10 % hit to cpu so I've had to play around with draw distances / object heights and other optimisations to offset that. Not to mention the larger buffer takes more cpu to fill also. Everything is placeholder so will be changed with proper stage design. We are averaging 20 FPS in the current video, I'll push for more as always !! Progress continues on my other projects , updates soon on those - retirement can't come quick enough . #SGDK #SegaGenesis #SegaMegadrive

Shannon Birt

34,837 просмотров • 1 месяц назад