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This 30 minute Roboflow interview will teach you more about shipping real-world Computer Vision products than most ML engineers learn in 3 years at big tech. Bookmark and watch, no matter what. It'll be the most productive thing you do this week. Marc Zoghby, co-founder of PlayVision, walks through...

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zostaff

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101,196 просмотров • 3 месяцев назад •via X (Twitter)

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STANFORD JUST PUT ITS ENTIRE ARTIFICIAL INTELLIGENCE CURRICULUM ON YOUTUBE FOR FREE. CS221. The same course that produced engineers now running AI labs, building frontier models, and getting paid $500,000 a year at the companies everyone is trying to work for. Most people have never heard of it. The ones who have are not telling you about it. Here is what the course actually covers: Search algorithms. The mathematical foundation behind every AI that finds optimal solutions in complex environments. Constraint satisfaction. How AI reasons through problems with thousands of interdependent variables simultaneously. Markov decision processes. The probabilistic framework behind every AI agent that makes sequential decisions under uncertainty. Machine learning from first principles. Not how to use sklearn. How the math actually works underneath it. Neural networks. Built from the ground up before jumping to applications. Logic and knowledge representation. How AI systems reason about the world formally. Natural language processing. The foundation of everything happening in LLMs right now. Robotics and computer vision. How AI perceives and acts in physical environments. Every concept that powers every AI product you use daily is in this curriculum. Not a surface level overview. The actual mathematics. The actual algorithms. The actual reasoning. This is what separates engineers who build AI from operators who use it. Stanford charged $60,000 a year for students to sit in this classroom. They put the whole thing on YouTube. Bookmark this before you open any other AI resource today. Follow CyrilXBT for more elite resources that build real depth the moment they drop.
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STANFORD JUST PUT ITS ENTIRE ARTIFICIAL INTELLIGENCE CURRICULUM ON YOUTUBE FOR FREE. CS221. The same course that produced engineers now running AI labs, building frontier models, and getting paid $500,000 a year at the companies everyone is trying to work for. Most people have never heard of it. The ones who have are not telling you about it. Here is what the course actually covers: Search algorithms. The mathematical foundation behind every AI that finds optimal solutions in complex environments. Constraint satisfaction. How AI reasons through problems with thousands of interdependent variables simultaneously. Markov decision processes. The probabilistic framework behind every AI agent that makes sequential decisions under uncertainty. Machine learning from first principles. Not how to use sklearn. How the math actually works underneath it. Neural networks. Built from the ground up before jumping to applications. Logic and knowledge representation. How AI systems reason about the world formally. Natural language processing. The foundation of everything happening in LLMs right now. Robotics and computer vision. How AI perceives and acts in physical environments. Every concept that powers every AI product you use daily is in this curriculum. Not a surface level overview. The actual mathematics. The actual algorithms. The actual reasoning. This is what separates engineers who build AI from operators who use it. Stanford charged $60,000 a year for students to sit in this classroom. They put the whole thing on YouTube. Bookmark this before you open any other AI resource today. Follow CyrilXBT for more elite resources that build real depth the moment they drop.

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Jane Street pays $400K+ to first-year traders out of college, no PhD required. This 26-minute mock interview with two actual Jane Street traders, Graham and Andrea, will teach you more about passing a quant trader interview than the entire Green Book. They walk through a real probability puzzle - exactly the kind that gets you cut in round 2 - and show you what interviewers actually look for. It's not the right answer. It's how you reason out loud. 26 minutes. Free. Watch it today. Then read the article below.
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Jane Street pays $400K+ to first-year traders out of college, no PhD required. This 26-minute mock interview with two actual Jane Street traders, Graham and Andrea, will teach you more about passing a quant trader interview than the entire Green Book. They walk through a real probability puzzle - exactly the kind that gets you cut in round 2 - and show you what interviewers actually look for. It's not the right answer. It's how you reason out loud. 26 minutes. Free. Watch it today. Then read the article below.

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13,287 просмотров • 3 месяцев назад

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2,179,490 просмотров • 5 месяцев назад

From Eric Vishria on how the top AI founders are building products completely opposite of the SaaS era: "One of the things that is really different in the AI world versus the SaaS world, is that in the SaaS world, over and over again, you had people who really understood the customer. And the problem. And then they understood a domain. They understood what the technology was more or less capable of. But it wasn't a real question of if you could build something or not. For example, take Salesforce, Workday, and ServiceNow. CRM existed before Salesforce. HR management existed before Workday. Same thing with ServiceNow. So in every case, Salesforce followed Siebel. Workday followed Peoplesoft. ServiceNow followed Peregrine and Remedy, and others. So they were just kind of, cloud SaaS versions of the prior generation product. They just understood the customers. They understood the problem. And they were just like, here's a better version. And that evolved a little bit over time in SaaS land. But that's what it is. And so product development in that way was done by people who really understood the customer and the problems. And then just took advantage of the next wave. And this is almost diametrically opposite of product development in the AI era. When I look at the teams that are having the most success today, they have intimate knowledge of the models. They are right on the frontier of understanding which models are better at what, and why, and when. And what they're going to be good at and what they're not going to be good at. And what they're spending their time on, is figuring out how do I apply this capability of this model to this domain or to this user. So they're actually working inside out or technology out, versus customer problem in. And of course, they understand the customer problem. And a lot of times they have firsthand knowledge of it. But they're really close to the metal and capability, and they're applying it. And I think this is a really different way to develop products than in SaaS. I started my career as a product manager a long time ago, and it's almost the complete opposite of everything you learned. "Listen to the customer, understand it, then bring it back to the engineering and product teams." If you did that right now, ask a bunch of customers what they want out of AI, and you brought it back, for the most part, it may not be possible today with today's technology. Whereas the teams that are winning right now really understand the technology and are applying it out. And so I think this reversal matters. I think it's a big difference in terms of how companies are getting built. And maybe even the types of entrepreneurs that will be successful. I'm not sure. You're seeing some real change there. Look at the Bret Taylor's at Sierra. That's a super, super technical founder who really gets it. Brett and Clay really get it. You look at Michael and his co-founders at Cursor. They're super technical founders and they get it. They all really understand what these things can and can't do. And that's a pretty different dynamic relative to the way the best SaaS companies got built." Link in bio for the full conversation going deep on the current class of startups going from zero to $100m+ in ARR within 12 months.
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The Peel

209,752 просмотров • 1 год назад

🌆 Digital Evidence, Real Estate, and the Next Wave of Real-World Adoption Dave Berg, CPO at Constellation, breaks down how they are building real onchain infrastructure that solves real problems. Not hypothetical use cases. Not hype cycles. Actual products people can use right now. 1. Digital Evidence. Authenticity for the internet. Constellation is anchoring digital fingerprints of files, images, documents, and data streams directly onto the network. Why does this matter? Because in a world filled with AI content, fake screenshots, edited PDFs, and manipulated media, proving the origin of information is becoming one of the most valuable capabilities we have. Developers and non developers can use simple APIs, or even vibe code with AI tools like Claude, to anchor and verify data instantly. Everyday users can anchor real-world data right now onto Constellation network with zero blockchain knowledge, using devices they already use every single day. 2. Proof of Management for real assets. This leads into what might be one of the most practical DLT products released in years. Real Estate Ledger. A digital guidebook for any property: • Permits • Warranties • Proof of maintenance • Vendor history • Manuals • Insurance • Improvements • Receipts • Photos Everything tied to the property, all cryptographically timestamped. If you have ever tried to sell a house, maintain one, or prove something to an insurer, you instantly understand how useful this is. Imagine handing a buyer a clean, verified report of every repair, every vendor, every upgrade, and every warranty. Imagine builders uploading materials and documentation during construction so the next owner knows exactly what is behind the walls. Imagine insurance claims based on truth instead of paperwork chaos. This is not a pitch deck about tokenizing real estate one day. This is infrastructure that exists right now. 3. Constellation is solving real adoption problems for Web3. No need to rebuild your business to onboard. No need to run your own nodes unless you want to. No need to become a blockchain expert. Just clean APIs, onchain trust, and applications anyone can understand. Authenticity and truth are scarce assets, Constellation (DAG) is building rails that protect them. Podcast powered by Constellation²
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Generation Infinity

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The future of AI Agents needs #ICP AI agents are starting to act on our behalf: - making deals - sending messages - handling sensitive data But there is no trust layer telling you who or what you're actually dealing with ❌ zCloak Network is building exactly that: the trust, identity and privacy infrastructure for the AI-native economy, and they built it on top of Internet Computer Protocol In this podcast I sit down with Xiao Zhang (0xFrancis), founder of to break down what they're building, why they chose ICP over every other blockchain, and what the world looks like when AI agents can finally be trusted.

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SOMEONE FROM THE ANTHROPIC TEAM LEAKED THEIR OBSIDIAN SETUP. 8 MILLION PEOPLE SAW HOW HE ACTUALLY USES CLAUDE the funniest part? all of this information was sitting in claude's documentation from day one. nobody read it one guy did, packed it into a 9-step guide and posted it. and it broke the internet. 4,100 likes, 800 retweets, then china picked it up and 8 million views want to know what's in it? one file. called CLAUDE.md. it holds everything about you: how you think, what you're working on, where you get stuck, even how you want the ai to talk to you. claude reads it first every single session one file changed everything. because now ai doesn't open with "how can i help?" it already knows. it remembers your projects, sees your goals, catches moments where you're contradicting yourself people spent years searching for the perfect prompt. the right temperature. the magic formula. and the answer turned out to be not how you ask ai. but what ai knows about you before you even open your mouth then the guy went deeper. taught claude to work on a schedule. every morning at 7am the ai walks through all notes on its own, finds new stuff, links it, cleans what's stale. no command. no reminder and all of this runs on obsidian. free app. text files on your drive. no cloud, no lock-in. switch models tomorrow and the folder keeps working the most liked comment under the original post: "this is the difference between using ai and building a system. most people won't realize it until they waste hundreds of hours repeating themselves" hundreds of hours. you've already spent some of them full guide in the video. i break down finds like this every day - follow so you don't miss the next one
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SOMEONE FROM THE ANTHROPIC TEAM LEAKED THEIR OBSIDIAN SETUP. 8 MILLION PEOPLE SAW HOW HE ACTUALLY USES CLAUDE the funniest part? all of this information was sitting in claude's documentation from day one. nobody read it one guy did, packed it into a 9-step guide and posted it. and it broke the internet. 4,100 likes, 800 retweets, then china picked it up and 8 million views want to know what's in it? one file. called CLAUDE.md. it holds everything about you: how you think, what you're working on, where you get stuck, even how you want the ai to talk to you. claude reads it first every single session one file changed everything. because now ai doesn't open with "how can i help?" it already knows. it remembers your projects, sees your goals, catches moments where you're contradicting yourself people spent years searching for the perfect prompt. the right temperature. the magic formula. and the answer turned out to be not how you ask ai. but what ai knows about you before you even open your mouth then the guy went deeper. taught claude to work on a schedule. every morning at 7am the ai walks through all notes on its own, finds new stuff, links it, cleans what's stale. no command. no reminder and all of this runs on obsidian. free app. text files on your drive. no cloud, no lock-in. switch models tomorrow and the folder keeps working the most liked comment under the original post: "this is the difference between using ai and building a system. most people won't realize it until they waste hundreds of hours repeating themselves" hundreds of hours. you've already spent some of them full guide in the video. i break down finds like this every day - follow so you don't miss the next one

kai

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Watch this game-changing dissertation on "expert writing." Expert writers write to "think" about the world. 99% of experts write and think at the same time. They use the writing process to help themselves think. This is how they do their best thinking. Write to think about the world. Do this because you care, because you want to be part of progress, because you want to make a dent in the universe. Write to inspire and influence. And when you are finished writing, and you click publish, think about your work this way... the intent of your text is to cause readers to change the way they think about the world. Engagement metrics don't really matter in comparison. Whether or not your text is valuable, depends on whether or not your readers perceive that you have valuably changed what they think, or what they do, or how they decide. One of the reasons it's so hard for smart people to write well is because they don't write to change the way people think about the world. They write to complete a project, to earn a grade, to be assessed. Or they write to publish *their* thoughts without going through a mental and soulful exercise of writing to think about the world, without writing to change how people think about the world. Write to think about the world. Change how people think about the world. In an era of #GenerativeAI, content isn't the end game. Your goal isn't just to get someone's attention, generate reactions, or show up in search. Your mission is to change how people think about the world. Change How People Think About the World. Thank you, Larry McEnerney (now-retired former Director of the University of Chicago's Writing Program).
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Watch this game-changing dissertation on "expert writing." Expert writers write to "think" about the world. 99% of experts write and think at the same time. They use the writing process to help themselves think. This is how they do their best thinking. Write to think about the world. Do this because you care, because you want to be part of progress, because you want to make a dent in the universe. Write to inspire and influence. And when you are finished writing, and you click publish, think about your work this way... the intent of your text is to cause readers to change the way they think about the world. Engagement metrics don't really matter in comparison. Whether or not your text is valuable, depends on whether or not your readers perceive that you have valuably changed what they think, or what they do, or how they decide. One of the reasons it's so hard for smart people to write well is because they don't write to change the way people think about the world. They write to complete a project, to earn a grade, to be assessed. Or they write to publish *their* thoughts without going through a mental and soulful exercise of writing to think about the world, without writing to change how people think about the world. Write to think about the world. Change how people think about the world. In an era of #GenerativeAI, content isn't the end game. Your goal isn't just to get someone's attention, generate reactions, or show up in search. Your mission is to change how people think about the world. Change How People Think About the World. Thank you, Larry McEnerney (now-retired former Director of the University of Chicago's Writing Program).

Brian Solis

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BREAKING: Remote Viewer Just Saw The Future of AI, and it's worrying... Remote Viewer, Edward Riordan, looked at the future of what Joe Rogan would talk about in terms of world events, and what he got back wasn't Joe's podcast... He saw a reality where humans become more and more obsolete to AI: "...they handed over the quote unquote keys to AI... There is... less need for humans is what I was feeling here... The intelligence knows more than you. What can you do... It can do better, faster, cheaper, easier... Billions or trillions of data inputs. Continuous input in real time. You can't keep up." "...there's debate. Debate about it, debate about whether or not this is good. So some are saying yes, some say no. It's underground, the full extent of it, the technological take over a long time in the making. And this was a stage seven...." "...machine learning. But why, I wonder? You don't need humans anymore. The machine AI does. It cheaper, faster and more efficient and most people won't know the difference. This was one of the most important things in this session right here. But you can see the artificial. This was my statement here. It's artificial...." "...people are being conditioned to accept artificial everything to not recognize or consider that what is being presented to them is artificially generated. That's how you that's how you that's how you, douse the spark... It's diabolical..." "...my basic data on this movement order was hive mind. Maybe a event in the sky that every everybody goes. Oh, and it brings the whole world into one mindset."

Future Forecasting Group

22,032 просмотров • 4 месяцев назад

Web scraping is a critical skill, and yet nobody talks about it. How do you think companies are training their Large Language Models? Where do you think the data comes from? But web scraping goes beyond all of that. Imagine giving an AI agent access to any public online data in real time! I like to call this "web-scrapping on demand", and I'm pretty sure it's going to unlock unlimited power for AI applications. I recorded a quick video to show you how you can do this using Apify. I've talked about them before, and they are collaborating with me on this post. They have one of the best open-source web scraping and browser automation libraries out there: But it gets much better than this! You can use MCP to connect your AI Agents and applications to the Apify platform and use any specialized actor on demand to scrape and process online data. In the video, I used Cursor to scrape LinkedIn posts with the words "Machine Learning" in real time. Worked like a charm with no code needed! Here is a link to the platform: Think about this: You can now feed your AI applications with any public data on demand! We aren't ready for what's coming.
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Web scraping is a critical skill, and yet nobody talks about it. How do you think companies are training their Large Language Models? Where do you think the data comes from? But web scraping goes beyond all of that. Imagine giving an AI agent access to any public online data in real time! I like to call this "web-scrapping on demand", and I'm pretty sure it's going to unlock unlimited power for AI applications. I recorded a quick video to show you how you can do this using Apify. I've talked about them before, and they are collaborating with me on this post. They have one of the best open-source web scraping and browser automation libraries out there: But it gets much better than this! You can use MCP to connect your AI Agents and applications to the Apify platform and use any specialized actor on demand to scrape and process online data. In the video, I used Cursor to scrape LinkedIn posts with the words "Machine Learning" in real time. Worked like a charm with no code needed! Here is a link to the platform: Think about this: You can now feed your AI applications with any public data on demand! We aren't ready for what's coming.

Santiago

101,473 просмотров • 1 год назад

AI will determine the future of WORK, BUSINESS, and LIFE. And there are huge questions: Will AI unleash our creativity and help us to flourish? Or will we lose even more power, agency, and ownership? It all depends on the design of the tech infrastructure. As Chris Dixon often says, “Architecture is destiny.” And how AI systems are designed will be key to the future we all live in. The team at gensyn is building a protocol that connects every device in the world into an open network for machine intelligence, with no gatekeepers or artificial boundaries. They are shaping a future of AI that is good for all of us. At a recent Innoveum event, I chatted to cofounder and CEO of gensyn about what they’re building, how it transforms AI, and why we should all be relieved, excited, and get involved. The full conversation is below in Episode One of Innoveum | The Podcast. 👇
1:14:00

AI will determine the future of WORK, BUSINESS, and LIFE. And there are huge questions: Will AI unleash our creativity and help us to flourish? Or will we lose even more power, agency, and ownership? It all depends on the design of the tech infrastructure. As Chris Dixon often says, “Architecture is destiny.” And how AI systems are designed will be key to the future we all live in. The team at gensyn is building a protocol that connects every device in the world into an open network for machine intelligence, with no gatekeepers or artificial boundaries. They are shaping a future of AI that is good for all of us. At a recent Innoveum event, I chatted to cofounder and CEO of gensyn about what they’re building, how it transforms AI, and why we should all be relieved, excited, and get involved. The full conversation is below in Episode One of Innoveum | The Podcast. 👇

Misha

27,481 просмотров • 1 год назад

This is how we live. This is how all of us live. This isn't some random street in Peoria, Illinois.. This is the entire world. As you watch the video you'll feel the tumblers click into place, one by one, over and over, it will be reinforced. As you become angrier. Consider.. Consider how desperately the one group fights to save the other. Consider how much resources and effort and punishment and pain one exerts to save the other. How the one actively sabotages the other and then blames them for failing to act becomes enraged when they fail to act.. In response to a wound they inflicted on themselves. And it's not just this one night. It's every night. It's every hour, of every day. It's constant. At no time in history has one group voluntarily shouldered the burdens of another in this capacity, to this degree. This is an event unique to the human story. And they hate you for it. Which is the most important part of the story here. They're only sorry when they're in the supine position. They're only sorry in the face of power. Then they squall. Then they weep. Then the discussion becomes about how I can't breathe, those magic words. They do not fear performative displays of violence, because that is a constant in their culture. They will punch you in the face and once you have them down, say "No, I didn't bro" as you bleed. This is the entire world. This post is about the entire world. This video is the entire world.
8:37

This is how we live. This is how all of us live. This isn't some random street in Peoria, Illinois.. This is the entire world. As you watch the video you'll feel the tumblers click into place, one by one, over and over, it will be reinforced. As you become angrier. Consider.. Consider how desperately the one group fights to save the other. Consider how much resources and effort and punishment and pain one exerts to save the other. How the one actively sabotages the other and then blames them for failing to act becomes enraged when they fail to act.. In response to a wound they inflicted on themselves. And it's not just this one night. It's every night. It's every hour, of every day. It's constant. At no time in history has one group voluntarily shouldered the burdens of another in this capacity, to this degree. This is an event unique to the human story. And they hate you for it. Which is the most important part of the story here. They're only sorry when they're in the supine position. They're only sorry in the face of power. Then they squall. Then they weep. Then the discussion becomes about how I can't breathe, those magic words. They do not fear performative displays of violence, because that is a constant in their culture. They will punch you in the face and once you have them down, say "No, I didn't bro" as you bleed. This is the entire world. This post is about the entire world. This video is the entire world.

BLACK DUMPLING™

523,831 просмотров • 1 месяц назад

Google just did it again. They just launched "Google Skills" a free platform to turn anyone into an AI expert. 3,000+ courses, labs & certificates from Google Cloud, DeepMind, and Grow with Google all in one place. → Learn AI, data, and coding from real Google engineers → Earn credentials that actually get you hired → Build hands-on projects with Gemini Code Assist → Compete on global leaderboards and share your wins No paywalls. No BS. Just world-class AI education free. This might be the biggest AI upskilling move of the decade. 👉
0:56

Google just did it again. They just launched "Google Skills" a free platform to turn anyone into an AI expert. 3,000+ courses, labs & certificates from Google Cloud, DeepMind, and Grow with Google all in one place. → Learn AI, data, and coding from real Google engineers → Earn credentials that actually get you hired → Build hands-on projects with Gemini Code Assist → Compete on global leaderboards and share your wins No paywalls. No BS. Just world-class AI education free. This might be the biggest AI upskilling move of the decade. 👉

Alex Veremeyenko

41,920 просмотров • 9 месяцев назад

Godfather of AI: "If you sleep well tonight, you may not have understood this lecture." This 47-minute lecture is the best thing I saw about AI in the last few months. It will definitely help you understand how it actually works and where it's going. Geoffrey Hinton built the neural networks behind every AI alive, then quit Google to warn the world about it. The part nobody wanted to hear: > AI is already developing abilities its creators didn't intend > in most cognitive tasks it's already ahead of us > the question is no longer if it surpasses us but when > the only decision left is which side of that line you're on Right now the average person opens Claude, types something, gets an answer, closes the tab. They think they're using AI. they're using maybe 10% of it. I went through his entire lecture, then mapped everything he described to what Claude can actually do today. 17 Claude features most people will never find on their own. Full breakdown in the post below.
47:05

Godfather of AI: "If you sleep well tonight, you may not have understood this lecture." This 47-minute lecture is the best thing I saw about AI in the last few months. It will definitely help you understand how it actually works and where it's going. Geoffrey Hinton built the neural networks behind every AI alive, then quit Google to warn the world about it. The part nobody wanted to hear: > AI is already developing abilities its creators didn't intend > in most cognitive tasks it's already ahead of us > the question is no longer if it surpasses us but when > the only decision left is which side of that line you're on Right now the average person opens Claude, types something, gets an answer, closes the tab. They think they're using AI. they're using maybe 10% of it. I went through his entire lecture, then mapped everything he described to what Claude can actually do today. 17 Claude features most people will never find on their own. Full breakdown in the post below.

Anatoli Kopadze

1,291,926 просмотров • 2 месяцев назад

IN 1999 MIT FILMED A MATH LECTURE THAT QUIETLY BECAME THE FOUNDATION OF EVERY AI MODEL YOU'VE EVER USED AND ALMOST NO ONE WAS TAUGHT TO SEE IT THAT WAY 39 minutes from Gilbert Strang, who taught this at MIT for over 60 years -- the linear algebra course an entire generation of engineers and data scientists grew up on. -> The shift it creates: you stop seeing matrices as boring grids of numbers and start seeing them as the language of space, data, and motion itself. School drilled you to crunch matrices by hand and never told you why. Strang shows you what they actually mean. Every neural net, every embedding, every model you prompt is linear algebra running underneath. The math you skipped is the engine of the thing you use all day. Memorizing the steps was never the skill -> seeing what the numbers do is. This is where it finally clicks. Most people fear linear algebra and move on. The ones who watched this see straight into how AI actually works. Bookmark & Watch it today, this one's a legend ↓
39:31

IN 1999 MIT FILMED A MATH LECTURE THAT QUIETLY BECAME THE FOUNDATION OF EVERY AI MODEL YOU'VE EVER USED AND ALMOST NO ONE WAS TAUGHT TO SEE IT THAT WAY 39 minutes from Gilbert Strang, who taught this at MIT for over 60 years -- the linear algebra course an entire generation of engineers and data scientists grew up on. -> The shift it creates: you stop seeing matrices as boring grids of numbers and start seeing them as the language of space, data, and motion itself. School drilled you to crunch matrices by hand and never told you why. Strang shows you what they actually mean. Every neural net, every embedding, every model you prompt is linear algebra running underneath. The math you skipped is the engine of the thing you use all day. Memorizing the steps was never the skill -> seeing what the numbers do is. This is where it finally clicks. Most people fear linear algebra and move on. The ones who watched this see straight into how AI actually works. Bookmark & Watch it today, this one's a legend ↓

slash1s

433,140 просмотров • 1 месяц назад

If there’s one lesson people are beginning to realize about modern technology, it’s this: The devices we rely on every day aren’t just tools. They’re surveillance systems. 👉 Learn more: Your phone tracks your location. Your apps collect your behavior. And now, AI integrated directly into your computer can record what you do on your screen every few seconds. Your emails. Your messages. Your searches. Even things you type but never send. That isn’t speculation. It’s the direction Big Tech has already taken. And the uncomfortable truth is that the people building these systems know exactly how powerful they are. Many of the same tech leaders who sell these devices to billions of users take extraordinary precautions with their own technology, covering cameras and limiting the very tools they encourage everyone else to use. Because data is power. And the more data that flows through these systems, the more influence the companies behind them gain over the digital world we all live in. But the playing field doesn’t have to stay that way. On Thursday, privacy experts Glenn and Eric Meder are hosting a free Privacy Academy webinar explaining exactly how these systems work and what people can do about them. During the training, they walk through how modern operating systems collect and analyze your behavior, how AI tools can build detailed behavioral profiles, and why many of the privacy settings people rely on don’t actually stop data collection. More importantly, they explain a practical alternative. Instead of relying on software designed around data collection, they show how privacy-focused systems like Linux can give users far more control over their own computers. And they break it down step by step so everyday people—not just programmers or tech experts—can understand how to make the transition. Because once you understand how these systems work, protecting your privacy becomes far easier than most people think. The free webinar is happening Thursday, March 5 at 7 PM Central, and it’s open to anyone who wants to understand how Big Tech is gathering data—and how to stop it. 👉 Register here: You can’t control the direction the tech industry chooses to take. But you can control how much access those systems have to your life. We want to thank Privacy Academy for helping everyday people understand how the digital world really works and for being a proud sponsor of this program. If you’re interested in learning more, visit do your own research, and decide if the training is right for you. Because when it comes to privacy, the most important step is understanding the system you’re living inside.
1:29

If there’s one lesson people are beginning to realize about modern technology, it’s this: The devices we rely on every day aren’t just tools. They’re surveillance systems. 👉 Learn more: Your phone tracks your location. Your apps collect your behavior. And now, AI integrated directly into your computer can record what you do on your screen every few seconds. Your emails. Your messages. Your searches. Even things you type but never send. That isn’t speculation. It’s the direction Big Tech has already taken. And the uncomfortable truth is that the people building these systems know exactly how powerful they are. Many of the same tech leaders who sell these devices to billions of users take extraordinary precautions with their own technology, covering cameras and limiting the very tools they encourage everyone else to use. Because data is power. And the more data that flows through these systems, the more influence the companies behind them gain over the digital world we all live in. But the playing field doesn’t have to stay that way. On Thursday, privacy experts Glenn and Eric Meder are hosting a free Privacy Academy webinar explaining exactly how these systems work and what people can do about them. During the training, they walk through how modern operating systems collect and analyze your behavior, how AI tools can build detailed behavioral profiles, and why many of the privacy settings people rely on don’t actually stop data collection. More importantly, they explain a practical alternative. Instead of relying on software designed around data collection, they show how privacy-focused systems like Linux can give users far more control over their own computers. And they break it down step by step so everyday people—not just programmers or tech experts—can understand how to make the transition. Because once you understand how these systems work, protecting your privacy becomes far easier than most people think. The free webinar is happening Thursday, March 5 at 7 PM Central, and it’s open to anyone who wants to understand how Big Tech is gathering data—and how to stop it. 👉 Register here: You can’t control the direction the tech industry chooses to take. But you can control how much access those systems have to your life. We want to thank Privacy Academy for helping everyday people understand how the digital world really works and for being a proud sponsor of this program. If you’re interested in learning more, visit do your own research, and decide if the training is right for you. Because when it comes to privacy, the most important step is understanding the system you’re living inside.

Vigilant Fox 🦊

13,435 просмотров • 5 месяцев назад

Being broke in 2026 is a choice. And this girl just brutally exposed exactly why. This girl just exposed one of the biggest cheats in 2026. She’s building real mobile apps and putting them on the App Store… …without knowing how to code God damn it. It called Vibecoding. You just describe what you want in plain English, open newly . app, and the AI builds the entire thing for you. No coding. No developers. No massive budget Just vibes + AI. While most of Crypto Twitter is still crying about the job market and gambling on shitcoins… This girl is out here creating and shipping actual apps like it’s nothing. This is the new meta. Vibecoding is going to create a wave of new millionaires who barely know what a line of code looks like. We are ridiculously early. Most people will watch this and still stay stuck. The dangerous ones are already experimenting. Follow me for more raw breakdowns on vibecoding, AI money printers, and faceless cash machines that actually work in 2026.
1:08

Being broke in 2026 is a choice. And this girl just brutally exposed exactly why. This girl just exposed one of the biggest cheats in 2026. She’s building real mobile apps and putting them on the App Store… …without knowing how to code God damn it. It called Vibecoding. You just describe what you want in plain English, open newly . app, and the AI builds the entire thing for you. No coding. No developers. No massive budget Just vibes + AI. While most of Crypto Twitter is still crying about the job market and gambling on shitcoins… This girl is out here creating and shipping actual apps like it’s nothing. This is the new meta. Vibecoding is going to create a wave of new millionaires who barely know what a line of code looks like. We are ridiculously early. Most people will watch this and still stay stuck. The dangerous ones are already experimenting. Follow me for more raw breakdowns on vibecoding, AI money printers, and faceless cash machines that actually work in 2026.

Frogify

11,642 просмотров • 2 месяцев назад

Mike Krieger (Mike Krieger) is the CPO of Anthropic ($10B+ raised) and the co-founder of Instagram, which he sold to Meta for $1B. Here's the full video of my recent conversation with him. Mike has one of the AI industry's most interesting jobs. He shared with me how he and his team craft product strategy for the company that's leading the charge on AI in the enterprise. Specifically, we discussed how frontier model innovations both drive product and vice versa (how product ideas inform AI research). We also talk about the long term defensibility of models (inspired by the emergence of DeepSeek), and how Mike believes that not only will individual models have specific strengths over others (such as in areas like coding, science, etc), but that a model's "vibes" will also be a major factor for driving customers' choice. Mike also shared his view on how AI will reinvent media and the business model of advertising on the internet, drawn heavily from his work building one of the most successful ad products ever built (Instagram) and his work on Artifact, an AI news product he also co-founded. Lastly, Mike dove deep into what it's like building for the Enterprise for the first time in his career, and how lessons from Instagram and Meta inform not only product development, but how Anthropic thinks about scaling its team in this period of hypergrowth. Chapters: 00:00 Introduction 00:54 Mike Krieger's Journey to Anthropic 03:17 Building Product Strategy at Anthropic 07:43 Rapid Iteration and Safety 10:58 Differentiating AI Models and User Experience 17:57 Impact of AI on Consumer Products and Business Models 24:39 Enterprise vs. Consumer Product Strategy 29:19 AI in Personal Life Management 30:15 Open Source and Claude Integrations 33:09 AI-Assisted Product Development 37:13 Scaling Teams and Processes at Anthropic 42:17 Reflections on AI and Future Prospects
54:20

Mike Krieger (Mike Krieger) is the CPO of Anthropic ($10B+ raised) and the co-founder of Instagram, which he sold to Meta for $1B. Here's the full video of my recent conversation with him. Mike has one of the AI industry's most interesting jobs. He shared with me how he and his team craft product strategy for the company that's leading the charge on AI in the enterprise. Specifically, we discussed how frontier model innovations both drive product and vice versa (how product ideas inform AI research). We also talk about the long term defensibility of models (inspired by the emergence of DeepSeek), and how Mike believes that not only will individual models have specific strengths over others (such as in areas like coding, science, etc), but that a model's "vibes" will also be a major factor for driving customers' choice. Mike also shared his view on how AI will reinvent media and the business model of advertising on the internet, drawn heavily from his work building one of the most successful ad products ever built (Instagram) and his work on Artifact, an AI news product he also co-founded. Lastly, Mike dove deep into what it's like building for the Enterprise for the first time in his career, and how lessons from Instagram and Meta inform not only product development, but how Anthropic thinks about scaling its team in this period of hypergrowth. Chapters: 00:00 Introduction 00:54 Mike Krieger's Journey to Anthropic 03:17 Building Product Strategy at Anthropic 07:43 Rapid Iteration and Safety 10:58 Differentiating AI Models and User Experience 17:57 Impact of AI on Consumer Products and Business Models 24:39 Enterprise vs. Consumer Product Strategy 29:19 AI in Personal Life Management 30:15 Open Source and Claude Integrations 33:09 AI-Assisted Product Development 37:13 Scaling Teams and Processes at Anthropic 42:17 Reflections on AI and Future Prospects

Michael Mignano

85,943 просмотров • 1 год назад

The CEO of OpenAI said something that should terrify every coder alive. Sam Altman was asked: "What is the most important skill people should learn in the age of AI?" His answer was not what anyone expected. He said learning to program, the thing every career advisor has drilled into an entire generation is "no longer obviously the right thing." So what does he think actually matters now? Four things and all of them are soft skills. And none of them taught in any computer science program on Earth.​ Become a high agency, act without being told. Make things happen on your own. Get good at generating ideas because when AI can execute anything, the person who knows what to build wins.​ Be very resilient, things will break constantly in a world moving at this speed.​ Be very adaptable, the world is rewriting itself every few months. Keep up or get left behind. But here is the part that changes everything. Altman says these skills are not just personality traits you are born with. They are learnable and deeply learnable.​ He watched people completely transform in three month bootcamps when he was a startup investor. That was, in his own words, "a big update" to how he sees the world.​ Now think about what this really means. The CEO of a company worth hundreds of billions is telling the world, the moat is no longer what you know. It is how you think and how you move and the old playbook is dead. The people who understand this right now have a massive head start. Everyone else is studying for a test that no longer exists.
1:09

The CEO of OpenAI said something that should terrify every coder alive. Sam Altman was asked: "What is the most important skill people should learn in the age of AI?" His answer was not what anyone expected. He said learning to program, the thing every career advisor has drilled into an entire generation is "no longer obviously the right thing." So what does he think actually matters now? Four things and all of them are soft skills. And none of them taught in any computer science program on Earth.​ Become a high agency, act without being told. Make things happen on your own. Get good at generating ideas because when AI can execute anything, the person who knows what to build wins.​ Be very resilient, things will break constantly in a world moving at this speed.​ Be very adaptable, the world is rewriting itself every few months. Keep up or get left behind. But here is the part that changes everything. Altman says these skills are not just personality traits you are born with. They are learnable and deeply learnable.​ He watched people completely transform in three month bootcamps when he was a startup investor. That was, in his own words, "a big update" to how he sees the world.​ Now think about what this really means. The CEO of a company worth hundreds of billions is telling the world, the moat is no longer what you know. It is how you think and how you move and the old playbook is dead. The people who understand this right now have a massive head start. Everyone else is studying for a test that no longer exists.

StockMarket.News

168,221 просмотров • 5 месяцев назад