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What if instead of autoresearch reflecting incremental progress from a single person, it reflected *hundreds* of researchers’ progress, updated live, with every run’s data point being interactive and reproducible? You could survey the full space of explored ideas, see which changes actually move the benchmark, and fold the most...

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Paul Scotti @ ICML

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22,075 просмотров • 17 дней назад •via X (Twitter)

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karpathy just broke the internet with something called auto research it’s basically an ai research agent that runs experiments for you 24/7 you give it a goal like “make this model better” “find a higher converting landing page” “lower customer acquisition cost” then it runs a loop: 1) plan an experiment 2) edit the code or config 3) run a short test on a gpu 4) read the metrics 5) keep the winner 6) try again over and over while you sleep by the morning you wake up to the best version actual tested improvements think of it like a robot research intern that runs hundreds of experiments and only keeps the winners this is link to his repo for your to mess around with it in the latest episode of The Startup Ideas Podcast (SIP) 🧃 i break down: • what auto research actually is • how it works step by step • 10 business ideas you can build with it • how to install it and start using it this one is saucy because tools like this change how startups get built watch
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karpathy just broke the internet with something called auto research it’s basically an ai research agent that runs experiments for you 24/7 you give it a goal like “make this model better” “find a higher converting landing page” “lower customer acquisition cost” then it runs a loop: 1) plan an experiment 2) edit the code or config 3) run a short test on a gpu 4) read the metrics 5) keep the winner 6) try again over and over while you sleep by the morning you wake up to the best version actual tested improvements think of it like a robot research intern that runs hundreds of experiments and only keeps the winners this is link to his repo for your to mess around with it in the latest episode of The Startup Ideas Podcast (SIP) 🧃 i break down: • what auto research actually is • how it works step by step • 10 business ideas you can build with it • how to install it and start using it this one is saucy because tools like this change how startups get built watch

GREG ISENBERG

435,542 просмотров • 4 месяцев назад

Databricks CEO Ali Ghodsi describes the difficulties of building a business around open source: "You have to hit two home runs, consecutively." "Your first home run - and you're banking on hitting that home run - is that your open source project takes over the world. Everybody wants to download it." If you don't hit that home run, Ali says, you just shot yourself in the foot. You just gave away your IP and got nothing back for it. But even if you hit this home run, you still don't have a monetizable business. You still can't make any money. So you have to hit the second home run: "You need a 10x innovation on top of the open source. That's the proprietary value you'll provide companies. That's why they'll come to you. Otherwise, they can get the open source anywhere." If you don't hit the second home run, the hyperscalers pick up your open source model, and they offer it for almost-free. "Getting into open source and monetizing is not an easy sport. Preferably don't get into it, because you might get hurt."
2:33

Databricks CEO Ali Ghodsi describes the difficulties of building a business around open source: "You have to hit two home runs, consecutively." "Your first home run - and you're banking on hitting that home run - is that your open source project takes over the world. Everybody wants to download it." If you don't hit that home run, Ali says, you just shot yourself in the foot. You just gave away your IP and got nothing back for it. But even if you hit this home run, you still don't have a monetizable business. You still can't make any money. So you have to hit the second home run: "You need a 10x innovation on top of the open source. That's the proprietary value you'll provide companies. That's why they'll come to you. Otherwise, they can get the open source anywhere." If you don't hit the second home run, the hyperscalers pick up your open source model, and they offer it for almost-free. "Getting into open source and monetizing is not an easy sport. Preferably don't get into it, because you might get hurt."

TBPN

45,355 просмотров • 7 месяцев назад

Two big steps towards our vision for NotebookLM as the ultimate research platform: • Integrating Deep Research, with a set of only-at-Notebook features that let you explore the retrieved sources • Launching a series of Featured Notebooks curated by Google Research These developments are designed to enhance the full life cycle of research and scholarship: using the power of AI to assemble the knowledge base you need to advance your understanding, and then making your work accessible and intelligible to a wider audience using all the explanatory tools that Notebook offers. If you've used DeepResearch in the Gemini app, you already know that it's a pioneering advance in assembling complex, grounded information on any topic imaginable—collecting an entire trove of material for you and writing a nuanced research report that summarizes the findings. But because NotebookLM is designed to manage and explore potentially hundreds of sources, the Deep Research report is only the beginning of your journey. In our integration, Deep Research gives you an overview all of the sources it found during its research phase, with annotated commentary explaining how each source related to your original query. You can then choose to import some or all of the sources to the notebook, along with the report itself, which you can then explore or transform using the full suite of tools that Notebook offers: grounded chat with citations, Mind Maps, Audio/Video overviews, and much more. And it's that suite of tools that make the Google Research Featured Notebooks so compelling as well. Each notebook contains a curated collection of articles on a specific topic, published by the Google Research team. Think of them as a kind of knowledge base of Google's best thinking on a series of compelling research questions: How do scientists link genetics to health? How will quantum computing be useful? If you're a specialist in these fields, you can read the original papers or ask nuanced questions in chat and advance your understanding of the latest developments. But these notebooks can also make the complex but important topics understandable to non-specialists or students. Each notebook comes with pre-generated audio and video overviews, flashcards, and other Studio artifacts designed to make the scientific and technological concepts accessible and interesting. And you can always explore the material with our new "Learning Guide" chat mode that effectively gives you a personal tutor to enhance your understanding. There's much more to come on this front, but you can see in these two announcements how we see Notebook as both a workbench for conducting research and a publishing platform for sharing the results of that research once you're ready to make it public. Deep Research is rolling out this week to all users. The first two Google Research notebooks are live now, both of them deep dives into our most recent discoveries involving genetics and health. (Links in the following tweets.) We'll be publishing new notebooks in the series every other week or so for the next few months.
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Two big steps towards our vision for NotebookLM as the ultimate research platform: • Integrating Deep Research, with a set of only-at-Notebook features that let you explore the retrieved sources • Launching a series of Featured Notebooks curated by Google Research These developments are designed to enhance the full life cycle of research and scholarship: using the power of AI to assemble the knowledge base you need to advance your understanding, and then making your work accessible and intelligible to a wider audience using all the explanatory tools that Notebook offers. If you've used DeepResearch in the Gemini app, you already know that it's a pioneering advance in assembling complex, grounded information on any topic imaginable—collecting an entire trove of material for you and writing a nuanced research report that summarizes the findings. But because NotebookLM is designed to manage and explore potentially hundreds of sources, the Deep Research report is only the beginning of your journey. In our integration, Deep Research gives you an overview all of the sources it found during its research phase, with annotated commentary explaining how each source related to your original query. You can then choose to import some or all of the sources to the notebook, along with the report itself, which you can then explore or transform using the full suite of tools that Notebook offers: grounded chat with citations, Mind Maps, Audio/Video overviews, and much more. And it's that suite of tools that make the Google Research Featured Notebooks so compelling as well. Each notebook contains a curated collection of articles on a specific topic, published by the Google Research team. Think of them as a kind of knowledge base of Google's best thinking on a series of compelling research questions: How do scientists link genetics to health? How will quantum computing be useful? If you're a specialist in these fields, you can read the original papers or ask nuanced questions in chat and advance your understanding of the latest developments. But these notebooks can also make the complex but important topics understandable to non-specialists or students. Each notebook comes with pre-generated audio and video overviews, flashcards, and other Studio artifacts designed to make the scientific and technological concepts accessible and interesting. And you can always explore the material with our new "Learning Guide" chat mode that effectively gives you a personal tutor to enhance your understanding. There's much more to come on this front, but you can see in these two announcements how we see Notebook as both a workbench for conducting research and a publishing platform for sharing the results of that research once you're ready to make it public. Deep Research is rolling out this week to all users. The first two Google Research notebooks are live now, both of them deep dives into our most recent discoveries involving genetics and health. (Links in the following tweets.) We'll be publishing new notebooks in the series every other week or so for the next few months.

Steven Johnson

104,814 просмотров • 8 месяцев назад

Jony Ive: “Ideas are always fragile” “Ideas, by definition, are always fragile. If they were resolved, they wouldn’t be ideas. They would be products that were ready to ship.” The legendary designer reflects on what he learned at Apple: “I’ve come to learn that you have to make an extraordinary effort not to focus on the problems, which are implicated with any new idea. These problems are known. They’re quantifiable and understood. But you have to focus on the actual idea, which is partial, tentative, and unproven. If you don't actively suspend your disbelief — if you don't believe there is a solution to the problems — of course you will lose faith in your idea.” He continues: “That is why criticism and focusing on the problems can be so damaging, particularly in the absence of a constructive idea. Remember, opinions are not ideas. Opinions are not as important as ideas. Opinions are just opinions.” Source: California College of the Arts (May 2021)
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Jony Ive: “Ideas are always fragile” “Ideas, by definition, are always fragile. If they were resolved, they wouldn’t be ideas. They would be products that were ready to ship.” The legendary designer reflects on what he learned at Apple: “I’ve come to learn that you have to make an extraordinary effort not to focus on the problems, which are implicated with any new idea. These problems are known. They’re quantifiable and understood. But you have to focus on the actual idea, which is partial, tentative, and unproven. If you don't actively suspend your disbelief — if you don't believe there is a solution to the problems — of course you will lose faith in your idea.” He continues: “That is why criticism and focusing on the problems can be so damaging, particularly in the absence of a constructive idea. Remember, opinions are not ideas. Opinions are not as important as ideas. Opinions are just opinions.” Source: California College of the Arts (May 2021)

Startup Archive

23,544 просмотров • 29 дней назад

Tune Studio is an end-to-end platform for developing applications using Large Language Models. So far, I haven't seen any other platform like this one. You can do everything here: 1. You can curate your data. 2. Use the playground to play with different models and try your ideas. 3. Fine-tune an open-source model on your data. 4. Deploy the model when you are done. This is awesome for anyone building generative AI applications. You can use Tune Studio to work with any of the open-source models out there. They were one of the few companies to host Llama 2 and Llama 3 before anyone else. Here is a link to check it out: One of their main selling points is that Tune Studio scales! You don't have to worry about serving your model to lots of users. They also have built-in user management, authentication, on-prem support, user context management, and pretty much everything you need to build generative AI applications. Thanks to the Tune team for collaborating with me on this post. We are living through the best years of development tools for AI developers. The field is unstoppable.
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Tune Studio is an end-to-end platform for developing applications using Large Language Models. So far, I haven't seen any other platform like this one. You can do everything here: 1. You can curate your data. 2. Use the playground to play with different models and try your ideas. 3. Fine-tune an open-source model on your data. 4. Deploy the model when you are done. This is awesome for anyone building generative AI applications. You can use Tune Studio to work with any of the open-source models out there. They were one of the few companies to host Llama 2 and Llama 3 before anyone else. Here is a link to check it out: One of their main selling points is that Tune Studio scales! You don't have to worry about serving your model to lots of users. They also have built-in user management, authentication, on-prem support, user context management, and pretty much everything you need to build generative AI applications. Thanks to the Tune team for collaborating with me on this post. We are living through the best years of development tools for AI developers. The field is unstoppable.

Santiago

39,101 просмотров • 2 лет назад

Tlon Messenger is now open to everyone. We built a simple and infinitely flexible platform for you to use AI agents with your friends. We think it’s pretty amazing, we love using it every day, and we want to see what people can do with it. So we’re opening it up to the public. It’s fun and exciting to build the future of personal computing in an informal, chat-based way with your friends. (You can skip the rest and just download it from the link in the next tweet if you want.) If you don’t want your digital future to be owned by a giant company but you want to explore what’s possible in this new era of agent-driven computing, you should try using Tlon. But wait, what is it? Tlon is a messaging platform built 100% open source, decentralized and owned by its users from the ground up. With Tlon you own everything: your data, your workflows, your programs: the whole thing. Think of it like Telegram or WhatsApp that you own forever and you can freely customize. Every Tlon account comes with an OpenClaw-powered bot. (Don’t worry, we safely run OpenClaw for you in our infrastructure so your bot can’t go off the rails. You’re also welcome to host your own claw if you want maximal control.) We use our bots to collect research, build nuanced daily briefings, collate data from all our disparate services. Tlon makes it insanely easy to use OpenClaw by simply installing an app from the app store, we let you keep your data and programs independent from any app or model provider, and provide the canvas to explore what’s possible. What’s most interesting for us is using bots together. On Tlon bots can create groups, augment them, moderate them, invite others and freely engage with both users and other bots. Tlon is an open playing field unlike what’s possible on conventional platforms. So, what do we do with Tlon? First and foremost, we run Tlon on Tlon. Bots coordinate data from all of our services (Linear, GitHub, all of our servers and infrastructure) and handle alerts, briefings and help us track down bugs in place. Having all of this easily synced between a desktop client and a mobile app is quick and convenient. We use bots to research new areas of work or interest. Bots can compile trees of notes, use different models to evaluate them, and then add on autoresearch-like automations to go even deeper. Since Tlon bots can freely switch between models and providers, we often pass research to Anthropic, OpenAI and self-hosted models to see different results. The most fun part of using bots as researchers is doing it together. “Put together short (~500 word) notes on the 10 most popular open source messaging protocols of the past twenty years, put them in a notebook inside a group and invite Corrina, Walt and Bill as well as their bots” is a good example. Together we’re able to move more quickly than we would on our own. Many of us also use bots to keep track of all the separate threads of work in our personal lives with close friends and family. Someone built a system for keeping track of their garden across time, someone else built a system for prepping lunches for their daughter and sending recipes to family members. Another team member built an integration that tracks what flights are passing overhead so they get a push notification every time a plane goes by. Many of us quickly communicate with our bots via voice memo when we’re out and about. Having a single interface to all the models that also holds all our data and is in our pockets feels great. Especially when the data goes into a single archive. Why is Tlon different? Every Tlon account runs on top of your very own personal server. If you ever want to download it and run it yourself, you can. If we ever go out of business, it’s yours to keep. This is very different from anything that already exists. You can’t keep your WhatsApp forever. You can’t keep your Telegram forever. Tlon is an archival-quality system that’s yours to customize. Why did we build it? In my 1999 imagination, sitting in front of a CRT somewhere in the California countryside listening to Underworld and the sound of a modem, a connected computer was an engine of unending creative potential for everyone. When I was a teenager, a computer with an internet connection felt like an infinite expanse of possibility. Not only could you use the computer to find new tools to experiment with—you could also build whatever tool you could think of. It seemed like anything was possible. I looked forward to a future where everyone could build whatever software they needed, whenever they needed it. It turned out, in the intervening twenty years, that to build and customize software you have to both write code and host it on a server somewhere. For most people, so far, that has been impossible. Instead of controlling our software, our software controls us. We rely on others to build it and decide everything about it: how it works, looks, how much it spies on us and how long it lives. But all of this is changing, fast. The hottest programming language of 2026 is English. People with no technical experience are building their own tools. It’s incredible. The expanse has opened up again. The cost of building what we think of today as software is headed to zero. What yesterday was an entire app is rapidly being replaced by a conversation. The result is hyper-specific, tailored to the user and much more efficient. Today, agents help us build workflows, automate processes and pull together disparate sources of data. All of the annoying apps and services and clunky interface we’ve put up with can just disappear. We can now program and control our computers in the programming language we already know: English. There aren’t that many of us doing this yet, though. It’s still far too hard to set up, to distribute and to trust. There’s also no single platform to experiment on and collaboratively imagine this new future of personal computing. We want everyone to be able to build bespoke, ultra-personal software on demand. We think software should be as available and accessible as a pen and paper. We think anyone should be able to enjoy the expanse of possibility that the computer provides with the lowest possible barrier to entry and the highest possible quality. So, starting far, far too long ago, we engineered a whole new system for it. Just for you. We’re opening up Tlon Messenger to a limited number of people each week. This isn’t for exclusivity’s sake, but because we’re running infrastructure for you and your agent, and covering the tokens your agent uses. That can get expensive quickly, but we want to learn what people will do with this new system we’ve built. We’re really curious to see what you can do, so give it a try and tell us what you invent. Download link to your local app store in the next tweet. Yours, Galen (and the rest of the Tlon Team)
0:20

Tlon Messenger is now open to everyone. We built a simple and infinitely flexible platform for you to use AI agents with your friends. We think it’s pretty amazing, we love using it every day, and we want to see what people can do with it. So we’re opening it up to the public. It’s fun and exciting to build the future of personal computing in an informal, chat-based way with your friends. (You can skip the rest and just download it from the link in the next tweet if you want.) If you don’t want your digital future to be owned by a giant company but you want to explore what’s possible in this new era of agent-driven computing, you should try using Tlon. But wait, what is it? Tlon is a messaging platform built 100% open source, decentralized and owned by its users from the ground up. With Tlon you own everything: your data, your workflows, your programs: the whole thing. Think of it like Telegram or WhatsApp that you own forever and you can freely customize. Every Tlon account comes with an OpenClaw-powered bot. (Don’t worry, we safely run OpenClaw for you in our infrastructure so your bot can’t go off the rails. You’re also welcome to host your own claw if you want maximal control.) We use our bots to collect research, build nuanced daily briefings, collate data from all our disparate services. Tlon makes it insanely easy to use OpenClaw by simply installing an app from the app store, we let you keep your data and programs independent from any app or model provider, and provide the canvas to explore what’s possible. What’s most interesting for us is using bots together. On Tlon bots can create groups, augment them, moderate them, invite others and freely engage with both users and other bots. Tlon is an open playing field unlike what’s possible on conventional platforms. So, what do we do with Tlon? First and foremost, we run Tlon on Tlon. Bots coordinate data from all of our services (Linear, GitHub, all of our servers and infrastructure) and handle alerts, briefings and help us track down bugs in place. Having all of this easily synced between a desktop client and a mobile app is quick and convenient. We use bots to research new areas of work or interest. Bots can compile trees of notes, use different models to evaluate them, and then add on autoresearch-like automations to go even deeper. Since Tlon bots can freely switch between models and providers, we often pass research to Anthropic, OpenAI and self-hosted models to see different results. The most fun part of using bots as researchers is doing it together. “Put together short (~500 word) notes on the 10 most popular open source messaging protocols of the past twenty years, put them in a notebook inside a group and invite Corrina, Walt and Bill as well as their bots” is a good example. Together we’re able to move more quickly than we would on our own. Many of us also use bots to keep track of all the separate threads of work in our personal lives with close friends and family. Someone built a system for keeping track of their garden across time, someone else built a system for prepping lunches for their daughter and sending recipes to family members. Another team member built an integration that tracks what flights are passing overhead so they get a push notification every time a plane goes by. Many of us quickly communicate with our bots via voice memo when we’re out and about. Having a single interface to all the models that also holds all our data and is in our pockets feels great. Especially when the data goes into a single archive. Why is Tlon different? Every Tlon account runs on top of your very own personal server. If you ever want to download it and run it yourself, you can. If we ever go out of business, it’s yours to keep. This is very different from anything that already exists. You can’t keep your WhatsApp forever. You can’t keep your Telegram forever. Tlon is an archival-quality system that’s yours to customize. Why did we build it? In my 1999 imagination, sitting in front of a CRT somewhere in the California countryside listening to Underworld and the sound of a modem, a connected computer was an engine of unending creative potential for everyone. When I was a teenager, a computer with an internet connection felt like an infinite expanse of possibility. Not only could you use the computer to find new tools to experiment with—you could also build whatever tool you could think of. It seemed like anything was possible. I looked forward to a future where everyone could build whatever software they needed, whenever they needed it. It turned out, in the intervening twenty years, that to build and customize software you have to both write code and host it on a server somewhere. For most people, so far, that has been impossible. Instead of controlling our software, our software controls us. We rely on others to build it and decide everything about it: how it works, looks, how much it spies on us and how long it lives. But all of this is changing, fast. The hottest programming language of 2026 is English. People with no technical experience are building their own tools. It’s incredible. The expanse has opened up again. The cost of building what we think of today as software is headed to zero. What yesterday was an entire app is rapidly being replaced by a conversation. The result is hyper-specific, tailored to the user and much more efficient. Today, agents help us build workflows, automate processes and pull together disparate sources of data. All of the annoying apps and services and clunky interface we’ve put up with can just disappear. We can now program and control our computers in the programming language we already know: English. There aren’t that many of us doing this yet, though. It’s still far too hard to set up, to distribute and to trust. There’s also no single platform to experiment on and collaboratively imagine this new future of personal computing. We want everyone to be able to build bespoke, ultra-personal software on demand. We think software should be as available and accessible as a pen and paper. We think anyone should be able to enjoy the expanse of possibility that the computer provides with the lowest possible barrier to entry and the highest possible quality. So, starting far, far too long ago, we engineered a whole new system for it. Just for you. We’re opening up Tlon Messenger to a limited number of people each week. This isn’t for exclusivity’s sake, but because we’re running infrastructure for you and your agent, and covering the tokens your agent uses. That can get expensive quickly, but we want to learn what people will do with this new system we’ve built. We’re really curious to see what you can do, so give it a try and tell us what you invent. Download link to your local app store in the next tweet. Yours, Galen (and the rest of the Tlon Team)

Tlon

598,595 просмотров • 28 дней назад

Sam Altman on the importance of surrounding yourself with people who don’t shoot down your ideas “Good ideas are not a solo endeavor. You want to find a group of smart people that you can start bouncing things off of… You don’t just sit in a room and write on the window with the whiteboard pen and have the good ideas come to you. Good ideas come because you talk to people.” But Sam stresses that this comes with an important caveat: surround yourself with people who build on your ideas rather than shoot them down: “Ideas are very fragile. So when you find this set of people to start talking about ideas with, you want people who don’t immediately shoot down a bad, half-baked idea… You want people who will say, ‘Well, that sounds crazy unlikely to work, but think how big it could be if it did work.’.. And then you can figure out how to make it work if you want.” Video source: Stanford Online (2017)
0:38

Sam Altman on the importance of surrounding yourself with people who don’t shoot down your ideas “Good ideas are not a solo endeavor. You want to find a group of smart people that you can start bouncing things off of… You don’t just sit in a room and write on the window with the whiteboard pen and have the good ideas come to you. Good ideas come because you talk to people.” But Sam stresses that this comes with an important caveat: surround yourself with people who build on your ideas rather than shoot them down: “Ideas are very fragile. So when you find this set of people to start talking about ideas with, you want people who don’t immediately shoot down a bad, half-baked idea… You want people who will say, ‘Well, that sounds crazy unlikely to work, but think how big it could be if it did work.’.. And then you can figure out how to make it work if you want.” Video source: Stanford Online (2017)

Startup Archive

65,766 просмотров • 1 год назад

Elon Musk explains how to get startup ideas When asked how he comes up with startup ideas, Elon responds: “I tend to think of things from a sort of physics standpoint… what’s the best way to accomplish something? And then pursue that. That’s also a good way to determine if something’s far from its optimum.” He gives rockets as an example: “You could reason by analogy and say the rocket is going to cost a certain amount because that’s what prior rockets have cost. Or you can say, well, what is a rocket made of? What are the material constituents? What do they weigh? What’s the cost per unit mass? And that sets the limit asymptotically for what a rocket can be. So if you can figure out some creative way to rearrange those elements into a rocket shape, then you can achieve a much better outcome.” He also thinks combining ideas from different industries is really helpful for innovation: “What have people discovered in one industry and can that be applied to other industries? That’s I think also a great source of ideas. But usually you just struggle on a solution and try a bunch of things. Most of them don’t work and occasionally one does.” Source: VANITY FAIR (Oct 2014)
1:28

Elon Musk explains how to get startup ideas When asked how he comes up with startup ideas, Elon responds: “I tend to think of things from a sort of physics standpoint… what’s the best way to accomplish something? And then pursue that. That’s also a good way to determine if something’s far from its optimum.” He gives rockets as an example: “You could reason by analogy and say the rocket is going to cost a certain amount because that’s what prior rockets have cost. Or you can say, well, what is a rocket made of? What are the material constituents? What do they weigh? What’s the cost per unit mass? And that sets the limit asymptotically for what a rocket can be. So if you can figure out some creative way to rearrange those elements into a rocket shape, then you can achieve a much better outcome.” He also thinks combining ideas from different industries is really helpful for innovation: “What have people discovered in one industry and can that be applied to other industries? That’s I think also a great source of ideas. But usually you just struggle on a solution and try a bunch of things. Most of them don’t work and occasionally one does.” Source: VANITY FAIR (Oct 2014)

Startup Archive

33,984 просмотров • 23 дней назад

AMD's Anush Elangovan explains why he thinks his company's open source ethos combined with agentic AI superpowers their leverage as a company: Because AMD publishes a lot of technical details about its hardware, when engineers use AI tools, the models already “understand” AMD’s systems and can help write code for them, debug them, or even generate new tools. And that makes developers more productive on AMD hardware without AMD having to do all the work internally. "AMD has had this ethos of open source, which really plays to our advantage. Every frontier model that I use has already seen every bit of AMD source code." "It'll rewrite my spec for me because it's already in the training data. Which you can't get from closed ecosystems." "In fact I built a virtual GPU simulator just based off our public specs, and now I'm running it on the GPU. So now I can run cross-generational GPU simulations on existing hardware." "We have that advantage. And we've run a Dev Day contest where we generated more tokens on AMD — Triton kernels and HIP kernels — than existed on the internet at the time." "So now that's all part of the pre-training data. It's a superpower because now you're open source, and you're agentically accelerating this process."
1:22

AMD's Anush Elangovan explains why he thinks his company's open source ethos combined with agentic AI superpowers their leverage as a company: Because AMD publishes a lot of technical details about its hardware, when engineers use AI tools, the models already “understand” AMD’s systems and can help write code for them, debug them, or even generate new tools. And that makes developers more productive on AMD hardware without AMD having to do all the work internally. "AMD has had this ethos of open source, which really plays to our advantage. Every frontier model that I use has already seen every bit of AMD source code." "It'll rewrite my spec for me because it's already in the training data. Which you can't get from closed ecosystems." "In fact I built a virtual GPU simulator just based off our public specs, and now I'm running it on the GPU. So now I can run cross-generational GPU simulations on existing hardware." "We have that advantage. And we've run a Dev Day contest where we generated more tokens on AMD — Triton kernels and HIP kernels — than existed on the internet at the time." "So now that's all part of the pre-training data. It's a superpower because now you're open source, and you're agentically accelerating this process."

TBPN

34,469 просмотров • 2 месяцев назад

It's such an exciting time to be an artist on the internet. We now have the technology to build out our worlds, in spaces we own, it is truly the age of ideas. I've built a new home for my projects here, and in advance of my next major release with Transient Labs on June 16th, I want to share what I've made with you all, and open a dialogue about how we can use these tools as artists to enhance the experience of making and sharing our art. This is an overview of davekrugman dot com (link in thread), specifically about new sites for Drip Drop and DRIVE, and to that end, I'll give a work from each project to someone who reshares this post. If you are an artist who is curious on how to build a site for yourself, I would be happy to help, I'm an open book, ask me in the comments below. There are so many tools to use- I mostly used Claude / Anthropic- and now we can literally speak our ideas into reality , the possibilities feel truly infinite, if you have curiosity, patience, and a bit of time to explore a new frontier. For too long, artists have had to build on the rented space of social platforms, and now it feels like we can really create sovereign spaces that we own and make ours with our unique vision. Feel free to skim and skip around the video, and I'd be stoked if you visited the site and saw it for yourself. Thanks for lookin!
19:12

It's such an exciting time to be an artist on the internet. We now have the technology to build out our worlds, in spaces we own, it is truly the age of ideas. I've built a new home for my projects here, and in advance of my next major release with Transient Labs on June 16th, I want to share what I've made with you all, and open a dialogue about how we can use these tools as artists to enhance the experience of making and sharing our art. This is an overview of davekrugman dot com (link in thread), specifically about new sites for Drip Drop and DRIVE, and to that end, I'll give a work from each project to someone who reshares this post. If you are an artist who is curious on how to build a site for yourself, I would be happy to help, I'm an open book, ask me in the comments below. There are so many tools to use- I mostly used Claude / Anthropic- and now we can literally speak our ideas into reality , the possibilities feel truly infinite, if you have curiosity, patience, and a bit of time to explore a new frontier. For too long, artists have had to build on the rented space of social platforms, and now it feels like we can really create sovereign spaces that we own and make ours with our unique vision. Feel free to skim and skip around the video, and I'd be stoked if you visited the site and saw it for yourself. Thanks for lookin!

Dave

20,607 просмотров • 1 месяц назад

We are truly overwhelmed with gratitude for each and every one of you who took the time out of your incredibly busy days and navigated through the Lagos traffic just to support Violet Charm at our very first pop-up event. It means so much to us that you chose to spend your precious time with us, and your presence brought so much warmth, energy, and joy to the day. This milestone is just the beginning of what we hope will be a beautiful journey, and while this was our first pop-up, it certainly won’t be the last. We are inspired by your encouragement and are committed to learning, growing, and improving every step of the way. Next year, we promise to come back bigger, better, and more exciting, all because of your unwavering support. Thank you from the depths of our hearts for believing in us and being part of this special moment ,we couldn’t have done it without you, and we can’t wait to create even more unforgettable memories together. Full video on my instagram
0:38

We are truly overwhelmed with gratitude for each and every one of you who took the time out of your incredibly busy days and navigated through the Lagos traffic just to support Violet Charm at our very first pop-up event. It means so much to us that you chose to spend your precious time with us, and your presence brought so much warmth, energy, and joy to the day. This milestone is just the beginning of what we hope will be a beautiful journey, and while this was our first pop-up, it certainly won’t be the last. We are inspired by your encouragement and are committed to learning, growing, and improving every step of the way. Next year, we promise to come back bigger, better, and more exciting, all because of your unwavering support. Thank you from the depths of our hearts for believing in us and being part of this special moment ,we couldn’t have done it without you, and we can’t wait to create even more unforgettable memories together. Full video on my instagram

Isabella Esther Georgewill

55,880 просмотров • 6 месяцев назад

How to build a 1-person AI company that: - Runs locally - 100% open-source - No human employees, all agents - Real-time collaboration via email Multi-agent orchestration is not new. Plenty of frameworks already let agents hand off tasks, run in parallel, and talk to each other. So the interesting question is not whether agents can collaborate. It is what structure you use to make them collaborate. The common approach is to wire a graph of nodes and edges and reason about the plumbing yourself. It works, but you are learning a new abstraction just to describe who does what. There is a coordination structure we have trusted for a hundred years already: an organization. Every company runs the same way. People have roles, roles have reporting lines, and work moves up and down that chart without anyone relaying each message by hand. Map that onto agents and the whole thing gets intuitive. You lay out an org chart, each agent fills one role, you talk to the person at the top, and the org sorts out the work between them. You already know how a company works, so you already know how to run one here. There is no new abstraction to learn. That is exactly what Alook does. Each agent is a live Claude Code or OpenCode session with a defined role, a reporting line, and its own email inbox. The agents coordinate over email, the same way a team would. And it all runs locally through a runtime on your own machine, so nothing leaves your setup. You bring your own agent too. Claude Code and Codex both work, and if you would rather stay fully open source and local, OpenCode works the same way. To show how this feels in practice, I set up three agents as a small sales team. Vi is the one I talk to. I hand Vi a goal, and Vi routes the work down the chart. Neile runs prospect research. Vi passes the target criteria, and Neile reports back a ranked list of names, roles, and companies, each with a suggested angle and a confidence score. Lliane runs outreach. Vi hands over the messaging angle and follow-up cadence, and Lliane reports back on emails sent, responses received, and any deal that needs escalation. I never relay a message between them. Neile and Lliane report to Vi, and Vi updates me in one place. The whole thing is open source and self-hosted, so it runs on your machine with your own agents. Give the repo a star if you want to follow where it goes: I also wrote a full walkthrough on building your own AI company with it, from a blank org chart to a running job. The article is quoted below. Cheers! :)
0:39

How to build a 1-person AI company that: - Runs locally - 100% open-source - No human employees, all agents - Real-time collaboration via email Multi-agent orchestration is not new. Plenty of frameworks already let agents hand off tasks, run in parallel, and talk to each other. So the interesting question is not whether agents can collaborate. It is what structure you use to make them collaborate. The common approach is to wire a graph of nodes and edges and reason about the plumbing yourself. It works, but you are learning a new abstraction just to describe who does what. There is a coordination structure we have trusted for a hundred years already: an organization. Every company runs the same way. People have roles, roles have reporting lines, and work moves up and down that chart without anyone relaying each message by hand. Map that onto agents and the whole thing gets intuitive. You lay out an org chart, each agent fills one role, you talk to the person at the top, and the org sorts out the work between them. You already know how a company works, so you already know how to run one here. There is no new abstraction to learn. That is exactly what Alook does. Each agent is a live Claude Code or OpenCode session with a defined role, a reporting line, and its own email inbox. The agents coordinate over email, the same way a team would. And it all runs locally through a runtime on your own machine, so nothing leaves your setup. You bring your own agent too. Claude Code and Codex both work, and if you would rather stay fully open source and local, OpenCode works the same way. To show how this feels in practice, I set up three agents as a small sales team. Vi is the one I talk to. I hand Vi a goal, and Vi routes the work down the chart. Neile runs prospect research. Vi passes the target criteria, and Neile reports back a ranked list of names, roles, and companies, each with a suggested angle and a confidence score. Lliane runs outreach. Vi hands over the messaging angle and follow-up cadence, and Lliane reports back on emails sent, responses received, and any deal that needs escalation. I never relay a message between them. Neile and Lliane report to Vi, and Vi updates me in one place. The whole thing is open source and self-hosted, so it runs on your machine with your own agents. Give the repo a star if you want to follow where it goes: I also wrote a full walkthrough on building your own AI company with it, from a blank org chart to a running job. The article is quoted below. Cheers! :)

Akshay 🚀

166,723 просмотров • 11 дней назад

🦖Hi DinoXAHur and Ranking Hook for Xahau I bring you a new example that you can use to learn or create new ideas in Xahau, in this case we have put together Xaman® Wallet 🪝 + Hooks in a demo game. DinoXAHur is a copy of the Chrome game of the jumping dinosaur created with Claude AI. The game has been included as xApp in Xaman, Xaman has a SDK to make it easy to integrate it in your applications or services: The game can be played for free or for 1 XAH. If you pay, the game will give you access to a public scoreboard that is stored on-chain in Xahau. If you manage to beat any of the current TOP 5 records, you will appear in the leaderboard. If you reach the 1st place, you may receive a prize in XAH if one is available at that time. The payments of the participants are counted and if someone reaches the TOP 1, they will get this amount if one is available at that time as a prize. Try it today: Ranking and fund management is possible thanks to the Ranking Hook. The ranking is stored on-chain and updated when needed. The game talks to Xahau and the hook and manages these actions. You have the hook code available if you want to use it or understand how it works to make a better version. Github link: If you are interested in the live operations of the game on Xahau, you can follow the XRPLWin explorer where you can see the transactions, the hook executions or the status of the namespaces, where the scoreboard is stored: I hope you enjoy it, I encourage you to build new and better ideas and remember that you can always write your questions here or go to the Xahau Contributors Discord.
0:57

🦖Hi DinoXAHur and Ranking Hook for Xahau I bring you a new example that you can use to learn or create new ideas in Xahau, in this case we have put together Xaman® Wallet 🪝 + Hooks in a demo game. DinoXAHur is a copy of the Chrome game of the jumping dinosaur created with Claude AI. The game has been included as xApp in Xaman, Xaman has a SDK to make it easy to integrate it in your applications or services: The game can be played for free or for 1 XAH. If you pay, the game will give you access to a public scoreboard that is stored on-chain in Xahau. If you manage to beat any of the current TOP 5 records, you will appear in the leaderboard. If you reach the 1st place, you may receive a prize in XAH if one is available at that time. The payments of the participants are counted and if someone reaches the TOP 1, they will get this amount if one is available at that time as a prize. Try it today: Ranking and fund management is possible thanks to the Ranking Hook. The ranking is stored on-chain and updated when needed. The game talks to Xahau and the hook and manages these actions. You have the hook code available if you want to use it or understand how it works to make a better version. Github link: If you are interested in the live operations of the game on Xahau, you can follow the XRPLWin explorer where you can see the transactions, the hook executions or the status of the namespaces, where the scoreboard is stored: I hope you enjoy it, I encourage you to build new and better ideas and remember that you can always write your questions here or go to the Xahau Contributors Discord.

Ekiserrepé {X}

31,923 просмотров • 1 год назад

STILL BUZZING FROM RED ROCKS!!!! there is something truly special about this place.. something that always surprises us and brings out our most powerful emotions.. looking back at what happened Friday night.. it is so humbling that this many people would come out in the cold to experience what we have to share with the world… and we sincerely thank you from the bottom of our hearts.. this is also now the 5th show of the tour to surpass over 10,000 in attendance which is absolutely WILDDDDDD to think about.. all we can say right now is if you are reading this we love you more than you know.. and if you have been to any stop on the tour so far you are family and we love you so much.. we can’t wait to finish this incredible run in Atlanta, Chicago, and then Minneapolis.. this tour has ignited so much passion in our souls.. we have reached some heights that we have never even fathomed.. last thing.. if you have a dream.. PLEASE DO IT!!! DON’T LET FEAR STOP YOU!!! FOLLOW THAT VOICE AND FOLLOW YOUR HEART!!! BECOME YOUR HIGHEST SELF ✨ we love you and thank you with all our being ❤️❤️❤️❤️❤️ -Derek & Scott
0:53

STILL BUZZING FROM RED ROCKS!!!! there is something truly special about this place.. something that always surprises us and brings out our most powerful emotions.. looking back at what happened Friday night.. it is so humbling that this many people would come out in the cold to experience what we have to share with the world… and we sincerely thank you from the bottom of our hearts.. this is also now the 5th show of the tour to surpass over 10,000 in attendance which is absolutely WILDDDDDD to think about.. all we can say right now is if you are reading this we love you more than you know.. and if you have been to any stop on the tour so far you are family and we love you so much.. we can’t wait to finish this incredible run in Atlanta, Chicago, and then Minneapolis.. this tour has ignited so much passion in our souls.. we have reached some heights that we have never even fathomed.. last thing.. if you have a dream.. PLEASE DO IT!!! DON’T LET FEAR STOP YOU!!! FOLLOW THAT VOICE AND FOLLOW YOUR HEART!!! BECOME YOUR HIGHEST SELF ✨ we love you and thank you with all our being ❤️❤️❤️❤️❤️ -Derek & Scott

SLANDER

37,363 просмотров • 2 лет назад

KARY MULLIS: NOBEL PRIZE IN CHEMISTRY & inventor of the PCR process being sold as a "Hantavirus test": "If they could find this virus in you at all, and with PCR, if you do it well, you can find almost anything in anybody... ...because if you can amplify one single molecule up to something which you can really measure, which PCR can do then there's very few molecules that you don't have at least a single one in your body: so that can be thought as a misuse to claim that is meaningful." There are 380 trillion viruses in and on the human body, to claim that finding a single one is the cause of a disease is an industrial scale scientific fraud that Kary Mullis, the inventor of the PCR process itself, called out as a misuse of his invention. So why is this process being mis-sold as a disgnostic "test"?
1:46

KARY MULLIS: NOBEL PRIZE IN CHEMISTRY & inventor of the PCR process being sold as a "Hantavirus test": "If they could find this virus in you at all, and with PCR, if you do it well, you can find almost anything in anybody... ...because if you can amplify one single molecule up to something which you can really measure, which PCR can do then there's very few molecules that you don't have at least a single one in your body: so that can be thought as a misuse to claim that is meaningful." There are 380 trillion viruses in and on the human body, to claim that finding a single one is the cause of a disease is an industrial scale scientific fraud that Kary Mullis, the inventor of the PCR process itself, called out as a misuse of his invention. So why is this process being mis-sold as a disgnostic "test"?

Robin Monotti

29,802 просмотров • 2 месяцев назад

How can you solve complex tasks using a Large Language Model? Here is a 2-minute introduction to everything you need to know to 10x the quality of your results. Let's talk about three techniques, in order of complexity, starting with the easiest one: • In-Context Learning • Indexing + In-Context Learning • Fine-tuning In-Context Learning The team that trained GPT-3 found something they couldn't explain: You can condition a model using examples of how you want it to behave. I included an example prompt in the attached video. You can "teach" the model how you want it to interpret questions, select the correct answers, and format the results by giving a few examples. You can also give specific knowledge to the model that will be helpful when formulating answers. We call this approach "grounding the model." There's another example in the video. Indexing + In-Context Learning Unfortunately, there is a limit to how much data you can include in a prompt. We call this the "context size." One version of GPT-4 supports a context of approximately 6,000 words, while the other supports 25,000 words. Although this sounds like a lot, many applications need more than that. Imagine you wrote a book and want to build an application to answer any questions about your story. What happens if your book is longer than the context? That's where Indexing comes in. Using a model, you can turn every book passage into an embedding. These are vectors, numbers that "encode" the passage's text. You can then store these embeddings in a particular database that supports fast retrieval of these vectors. You can then turn any question into an embedding and search the database for the list of passages that are similar to that query. Instead of using the entire book to ask the model, you can now use the relevant passages as in-context information, effectively working around the context size limitation. Fine-tuning Fine-tuning can give you an extra boost to get reliable outputs from your LLM. It is, however, the most complex approach on the list. There are different approaches to fine-tuning a model with your data. A popular technique is to process your data with your LLM and use the outputs to train a new classifier that solves your specific task. Notice that here you aren't modifying the LLM. Instead, you are chaining it with your trained classifier. Another approach is to modify the parameters of the LLM using your data. Think of this as "rewiring" the model in a way that solves your particular task. The results and costs will vary depending on how many layers you want to fine-tune from the original model. Many companies think that fine-tuning is the solution to their problems. In my experience, many will benefit from exploring the other two approaches. I love explaining Machine Learning and Artificial Intelligence ideas. If you enjoy in-depth content like this, follow me Santiago so you don't miss what comes next.
4:50

How can you solve complex tasks using a Large Language Model? Here is a 2-minute introduction to everything you need to know to 10x the quality of your results. Let's talk about three techniques, in order of complexity, starting with the easiest one: • In-Context Learning • Indexing + In-Context Learning • Fine-tuning In-Context Learning The team that trained GPT-3 found something they couldn't explain: You can condition a model using examples of how you want it to behave. I included an example prompt in the attached video. You can "teach" the model how you want it to interpret questions, select the correct answers, and format the results by giving a few examples. You can also give specific knowledge to the model that will be helpful when formulating answers. We call this approach "grounding the model." There's another example in the video. Indexing + In-Context Learning Unfortunately, there is a limit to how much data you can include in a prompt. We call this the "context size." One version of GPT-4 supports a context of approximately 6,000 words, while the other supports 25,000 words. Although this sounds like a lot, many applications need more than that. Imagine you wrote a book and want to build an application to answer any questions about your story. What happens if your book is longer than the context? That's where Indexing comes in. Using a model, you can turn every book passage into an embedding. These are vectors, numbers that "encode" the passage's text. You can then store these embeddings in a particular database that supports fast retrieval of these vectors. You can then turn any question into an embedding and search the database for the list of passages that are similar to that query. Instead of using the entire book to ask the model, you can now use the relevant passages as in-context information, effectively working around the context size limitation. Fine-tuning Fine-tuning can give you an extra boost to get reliable outputs from your LLM. It is, however, the most complex approach on the list. There are different approaches to fine-tuning a model with your data. A popular technique is to process your data with your LLM and use the outputs to train a new classifier that solves your specific task. Notice that here you aren't modifying the LLM. Instead, you are chaining it with your trained classifier. Another approach is to modify the parameters of the LLM using your data. Think of this as "rewiring" the model in a way that solves your particular task. The results and costs will vary depending on how many layers you want to fine-tune from the original model. Many companies think that fine-tuning is the solution to their problems. In my experience, many will benefit from exploring the other two approaches. I love explaining Machine Learning and Artificial Intelligence ideas. If you enjoy in-depth content like this, follow me Santiago so you don't miss what comes next.

Santiago

384,495 просмотров • 3 лет назад

Jordan Peterson: "If you can't fix your room, you can't fix your life" "Why should you even bother improving yourself? The answer is something like: so you don't suffer anymore stupidly than you have to. And maybe so others don't have to either. It's not some casual self-help doctrine. If you don't organize yourself properly, you'll pay for it. In a big way. And so will the people around you." Peterson continues: "You can say, 'Well, I don't care about that.' But that's actually not true, you do care about it. Because if you're in pain, you will care about it. It's very rare that you can find someone in excruciating pain who would say, 'Well, it would be no better if I was out of this.' Pain brings the idea that it would be better if it didn't exist along with it. It's incontrovertible." On how to start: "Look around for something that bothers you and see if you can fix it. You can do this in a room. Sit in your bedroom and think: 'If I wanted to spend ten minutes making this room better, what would I have to do?' You have to ask yourself that, it's a genuine question. And things will pop out. There's a stack of papers bugging you. Some rubbish behind your computer monitor you haven't attended to for six months. Cables tangled up." He explains why this matters: "If you were coming to see me for psychotherapy, the easiest thing would be to get you to organize your room. You think, is that psychotherapy? It depends on how you conceive the limits of your being. Start where you can start. If something announces itself as in need of repair that you could repair, fix it. Fix a hundred things like that, your life will be a lot different." On fixing what you repeat every day: "People tend to think of their daily routines as trivial. You get up, brush your teeth, have breakfast. Those probably constitute 50% of your life. People think, they're mundane, I don't need to pay attention to them. No, that's exactly wrong. The things you do every day are the most important things you do. Hands down. Just do the arithmetic." On staying within your competence: "Sometimes you don't know how to fix something. Imagine you're walking down the street and there's a guy who's alcoholic and schizophrenic and has been homeless for ten years. That's a problem. It would be good if you could fix it, but you haven't got a clue. You walk around that and go find something you could fix. Just because something announces itself as in need of repair doesn't mean it's you, right then and there, who should repair it. You have to have some humility. You don't walk up to a helicopter that isn't working and just start tinkering away." Peterson shares the key insight: "As soon as you give your mind a genuine aim, it'll reconfigure the world in keeping with that aim. That's actually how you see to begin with. You've all seen the video where you watch basketballs being tossed back and forth, and while you're doing that, a gorilla walks into the middle of the video and you don't see it. If you thought about that experiment for five years, that would be about the right amount of time to spend thinking about it." He explains what it reveals: "What it shows you is that you see what you aim at. If you can get one thing through your head, that would be a good one. You see what you aim at. One inference you might draw from that is: be careful what you aim at. What you aim at determines the way the world manifests itself to you. So if the world is manifesting itself in a very negative way, one thing to ask is: are you aiming at the right thing?"
6:59

Jordan Peterson: "If you can't fix your room, you can't fix your life" "Why should you even bother improving yourself? The answer is something like: so you don't suffer anymore stupidly than you have to. And maybe so others don't have to either. It's not some casual self-help doctrine. If you don't organize yourself properly, you'll pay for it. In a big way. And so will the people around you." Peterson continues: "You can say, 'Well, I don't care about that.' But that's actually not true, you do care about it. Because if you're in pain, you will care about it. It's very rare that you can find someone in excruciating pain who would say, 'Well, it would be no better if I was out of this.' Pain brings the idea that it would be better if it didn't exist along with it. It's incontrovertible." On how to start: "Look around for something that bothers you and see if you can fix it. You can do this in a room. Sit in your bedroom and think: 'If I wanted to spend ten minutes making this room better, what would I have to do?' You have to ask yourself that, it's a genuine question. And things will pop out. There's a stack of papers bugging you. Some rubbish behind your computer monitor you haven't attended to for six months. Cables tangled up." He explains why this matters: "If you were coming to see me for psychotherapy, the easiest thing would be to get you to organize your room. You think, is that psychotherapy? It depends on how you conceive the limits of your being. Start where you can start. If something announces itself as in need of repair that you could repair, fix it. Fix a hundred things like that, your life will be a lot different." On fixing what you repeat every day: "People tend to think of their daily routines as trivial. You get up, brush your teeth, have breakfast. Those probably constitute 50% of your life. People think, they're mundane, I don't need to pay attention to them. No, that's exactly wrong. The things you do every day are the most important things you do. Hands down. Just do the arithmetic." On staying within your competence: "Sometimes you don't know how to fix something. Imagine you're walking down the street and there's a guy who's alcoholic and schizophrenic and has been homeless for ten years. That's a problem. It would be good if you could fix it, but you haven't got a clue. You walk around that and go find something you could fix. Just because something announces itself as in need of repair doesn't mean it's you, right then and there, who should repair it. You have to have some humility. You don't walk up to a helicopter that isn't working and just start tinkering away." Peterson shares the key insight: "As soon as you give your mind a genuine aim, it'll reconfigure the world in keeping with that aim. That's actually how you see to begin with. You've all seen the video where you watch basketballs being tossed back and forth, and while you're doing that, a gorilla walks into the middle of the video and you don't see it. If you thought about that experiment for five years, that would be about the right amount of time to spend thinking about it." He explains what it reveals: "What it shows you is that you see what you aim at. If you can get one thing through your head, that would be a good one. You see what you aim at. One inference you might draw from that is: be careful what you aim at. What you aim at determines the way the world manifests itself to you. So if the world is manifesting itself in a very negative way, one thing to ask is: are you aiming at the right thing?"

Jaynit

68,550 просмотров • 3 месяцев назад

Hi GoBid as a proudly South African company we at View4You disagree with the fact that people cannot run diagnostics, check the car to see if it starts check for any warning lights, check fluids on your cars. We understand moving them is not doable like all other auctions. Our founder recently reached out to your ambassador mumbo repairs and asked Him why your cars are not auctioned with a report stating the truth about the car as we have come across cases of possible mileage fraud and a case of a cloned car at GoBid. The response we received was that it would be difficult as the quantities are large and it would be costly. He also stated these cars are from various banks insurers etc. He further stated that GoBid will allow us to do our own inspections before we bid. His answers are acceptable and understandable. However, they do depict or show a lack of or no interest in protecting the consumer. Now today we were stopped from running a diagnostic, we were not allowed to get the car started and we were also not allowed to check the fluids. How can people bid confidently with these limitations? Now our humble request is, please permit us to run our checks thoroughly to ensure we know what we are bidding on. All other auctions permit such and it’s only you who does not allow it. A diagnostic test is crucial in the process of practicing due diligence, if you do not want us to run a diagnostic, can you please run it and place the report on the windscreen of your cars that can be diagnosed? You can contact us at info@view4you.co.za and we can run it on all your cars if you do not have the capacity to do so. Thank You.
0:25

Hi GoBid as a proudly South African company we at View4You disagree with the fact that people cannot run diagnostics, check the car to see if it starts check for any warning lights, check fluids on your cars. We understand moving them is not doable like all other auctions. Our founder recently reached out to your ambassador mumbo repairs and asked Him why your cars are not auctioned with a report stating the truth about the car as we have come across cases of possible mileage fraud and a case of a cloned car at GoBid. The response we received was that it would be difficult as the quantities are large and it would be costly. He also stated these cars are from various banks insurers etc. He further stated that GoBid will allow us to do our own inspections before we bid. His answers are acceptable and understandable. However, they do depict or show a lack of or no interest in protecting the consumer. Now today we were stopped from running a diagnostic, we were not allowed to get the car started and we were also not allowed to check the fluids. How can people bid confidently with these limitations? Now our humble request is, please permit us to run our checks thoroughly to ensure we know what we are bidding on. All other auctions permit such and it’s only you who does not allow it. A diagnostic test is crucial in the process of practicing due diligence, if you do not want us to run a diagnostic, can you please run it and place the report on the windscreen of your cars that can be diagnosed? You can contact us at [email protected] and we can run it on all your cars if you do not have the capacity to do so. Thank You.

VIEW4YOU

30,358 просмотров • 2 месяцев назад

From a single spark in Dubai to a flame that’s traveled the world. 👁️✨ Looking back since 2024, it’s not just the cities or the lights that stay with us, it’s the energy you brought to every dancefloor. We went from a "what if" to a global movement. From the high-rises of Dubai and Singapore to the heart of Europe in Brussels and Amsterdam... and across the horizons of Hong Kong, Seoul, Bangkok, Miami, and more. Every mile was worth it to see this community come alive. 🌍 Grateful to the artists who poured their souls into their sets. 🎧 To every raver: you are the heartbeat of RaveDAO. We’ve grown so much since Day 1, but the best part is that we’ve written this story together. 🖤 Thank you for an unforgettable two years. 2026 brings new cities, new chapters, and the next evolution of our "what if." This is RaveDAO. This is you. Where are we taking this next? #RaveDAO #rave
1:27

From a single spark in Dubai to a flame that’s traveled the world. 👁️✨ Looking back since 2024, it’s not just the cities or the lights that stay with us, it’s the energy you brought to every dancefloor. We went from a "what if" to a global movement. From the high-rises of Dubai and Singapore to the heart of Europe in Brussels and Amsterdam... and across the horizons of Hong Kong, Seoul, Bangkok, Miami, and more. Every mile was worth it to see this community come alive. 🌍 Grateful to the artists who poured their souls into their sets. 🎧 To every raver: you are the heartbeat of RaveDAO. We’ve grown so much since Day 1, but the best part is that we’ve written this story together. 🖤 Thank you for an unforgettable two years. 2026 brings new cities, new chapters, and the next evolution of our "what if." This is RaveDAO. This is you. Where are we taking this next? #RaveDAO #rave

RaveDAO

95,059 просмотров • 5 месяцев назад

Jony Ive: “Ideas are always fragile” “Ideas—by definition—are always fragile. If they were resolved, they wouldn’t be ideas. They would be products that were ready to ship.” The legendary Apple designer continues: “I’ve come to learn that you have to make an extraordinary effort not to focus on the problems, which are implicated with any new idea. These problems are known. They’re quantifiable and understood. But you have to focus on the actual idea, which is partial, tentative, and unproven.” All new ideas have problems, and if you don’t suspend your disbelief and trust that you will find a solution, you will lose faith in your idea. “That is why criticism and focusing on the problems can be so damaging—particularly in the absence of a constructive idea. Remember, opinions are not ideas. Opinions are not as important as ideas. Opinions are just opinions.” Source: California College of the Arts
1:07

Jony Ive: “Ideas are always fragile” “Ideas—by definition—are always fragile. If they were resolved, they wouldn’t be ideas. They would be products that were ready to ship.” The legendary Apple designer continues: “I’ve come to learn that you have to make an extraordinary effort not to focus on the problems, which are implicated with any new idea. These problems are known. They’re quantifiable and understood. But you have to focus on the actual idea, which is partial, tentative, and unproven.” All new ideas have problems, and if you don’t suspend your disbelief and trust that you will find a solution, you will lose faith in your idea. “That is why criticism and focusing on the problems can be so damaging—particularly in the absence of a constructive idea. Remember, opinions are not ideas. Opinions are not as important as ideas. Opinions are just opinions.” Source: California College of the Arts

Startup Archive

112,426 просмотров • 2 лет назад