正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

❓Fave nugget from our chat w GitHub CEO Thomas Dohmke on our latest Sequoia Capital Training Data episode with me & Sonya Huang 🐥: On what timeframe do you think AI will be as good as an average developer, and a 10x developer? 1⃣ Models today are able to... show more

Stephanie Zhan

32,160 subscribers

22,187 次观看 • 2 年前 •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

5 条评论

Stephanie Zhan 的头像

Stephanie Zhan2 年前

@ashtom @sequoia @sonyatweetybird Apple Podcasts: Spotify: YouTube:

Enrique 的头像

Enrique2 年前

@github @ashtom @sequoia @sonyatweetybird I'm watching now..... I really liked the Lego analogy Thomas gave.

Itamar Friedman 的头像

Itamar Friedman2 年前

@github @ashtom @sequoia @sonyatweetybird But, "prompting the right way and giving the right context" is a big portion of the development work (with or without AI) 🤔

Stephanie Zhan 的头像

Stephanie Zhan2 年前

@github @ashtom @sequoia @sonyatweetybird Agreed!

Christopher Ott 的头像

Christopher Ott2 年前

@github @ashtom @sequoia @sonyatweetybird Incredible to see happening in real time thanks for these episodes

相关视频

🤖 New Sequoia Capital Training Data pod drop with GitHub CEO Thomas Dohmke! A legendary company now at $2B ARR, with 2-year old Copilot now adopted by 77K+ orgs. CEO Thomas Dohmke chats with me and Sonya Huang 🐥 about: 1⃣Github Copilot and Workspace ushering in a new era of 1B developers 2⃣Agent applications across the developer workflow like code scanning Autofix 3⃣What he's excited about in AI in 1, 5, 10 years from today outside of developers, & more! 🔗👇

🤖 New Sequoia Capital Training Data pod drop with GitHub CEO Thomas Dohmke! A legendary company now at $2B ARR, with 2-year old Copilot now adopted by 77K+ orgs. CEO Thomas Dohmke chats with me and Sonya Huang 🐥 about: 1⃣Github Copilot and Workspace ushering in a new era of 1B developers 2⃣Agent applications across the developer workflow like code scanning Autofix 3⃣What he's excited about in AI in 1, 5, 10 years from today outside of developers, & more! 🔗👇

Stephanie Zhan

25,946 次观看 • 2 年前

We asked Shaun Maguire from Sequoia Capital about his latest thesis on AI models. "My current thinking is that the closest analogy is operating systems." "I think there'll be 10-100 times as many open source models in 10 years, but they won't be as valuable." "There are more Linux servers in the world than Microsoft servers, but the value capture of Microsoft is way greater than Linux." "Foundational models will have hardware moats like cloud and will profit from applications on top." From his appearance on the show in June.

We asked Shaun Maguire from Sequoia Capital about his latest thesis on AI models. "My current thinking is that the closest analogy is operating systems." "I think there'll be 10-100 times as many open source models in 10 years, but they won't be as valuable." "There are more Linux servers in the world than Microsoft servers, but the value capture of Microsoft is way greater than Linux." "Foundational models will have hardware moats like cloud and will profit from applications on top." From his appearance on the show in June.

TBPN

123,666 次观看 • 10 个月前

Sam on Kimi, distillation, and open source: “I have always assumed that there are going to be great cheap models in the world, and we better be the greatest and the cheapest. You get a better deal today, at least at a particular latency, using OpenAI's models than Kimi. We distill our own models. That’s how we make smaller, cheaper models. That’s a very good thing to do. There will clearly be an important place for open source models in the world and people that will want their own weights. We have so much usage of our models that we do not need to be a gigantically high-margin business to be able to afford model training. I would rather people not distill from us, for sure. But this is not in my top ten list of worries.”

Sam on Kimi, distillation, and open source: “I have always assumed that there are going to be great cheap models in the world, and we better be the greatest and the cheapest. You get a better deal today, at least at a particular latency, using OpenAI's models than Kimi. We distill our own models. That’s how we make smaller, cheaper models. That’s a very good thing to do. There will clearly be an important place for open source models in the world and people that will want their own weights. We have so much usage of our models that we do not need to be a gigantically high-margin business to be able to afford model training. I would rather people not distill from us, for sure. But this is not in my top ten list of worries.”

Patrick OShaughnessy

270,121 次观看 • 2 个月前

People used to pay me on on average to build their apps for $30K USD in less than a month. I was the go-to-guy because I knew how to build exactly what they wanted with little instruction and I always met their insane deadlines. I was known as "the machine", I wasn't the 10x developer I was the 100x developer. But it took its toll on my health and I left that do tech education. Claude Code can now do it. No computer science degree. No dev team. No $30K invoice. But most non-tech people are still stuck on the outside looking in because there is a tech knowledge gap. What if someone showed you all the steps, used plain speak, provided technical strategy, technical pathing, technical guidance, made it practical, and takes you to production. That's what my Claude Code from Zero course would be. But I'll be honest with you, this won't be a Udemy $20 priced course. It will be $300, $500 or $1200 depending on your needs. But do you want me to build it?

People used to pay me on on average to build their apps for $30K USD in less than a month. I was the go-to-guy because I knew how to build exactly what they wanted with little instruction and I always met their insane deadlines. I was known as "the machine", I wasn't the 10x developer I was the 100x developer. But it took its toll on my health and I left that do tech education. Claude Code can now do it. No computer science degree. No dev team. No $30K invoice. But most non-tech people are still stuck on the outside looking in because there is a tech knowledge gap. What if someone showed you all the steps, used plain speak, provided technical strategy, technical pathing, technical guidance, made it practical, and takes you to production. That's what my Claude Code from Zero course would be. But I'll be honest with you, this won't be a Udemy $20 priced course. It will be $300, $500 or $1200 depending on your needs. But do you want me to build it?

Andrew Brown

26,969 次观看 • 6 个月前

As Larry Ellison explains, there are two types of AI models: real-time models, also called AI on the edge, where you need ultra-low latency decisions (think autonomous driving or robotics), and models that don’t need an immediate response, like ChatGPT, where the system has time to reason. Real-time models require local compute inside the device, and these chips have nothing to do with the GPUs running in data centers. The AI-on-the-edge market is still largely untapped — and it’s going to be a multi-trillion-dollar opportunity. I believe $AMD will be one of the biggest beneficiaries

As Larry Ellison explains, there are two types of AI models: real-time models, also called AI on the edge, where you need ultra-low latency decisions (think autonomous driving or robotics), and models that don’t need an immediate response, like ChatGPT, where the system has time to reason. Real-time models require local compute inside the device, and these chips have nothing to do with the GPUs running in data centers. The AI-on-the-edge market is still largely untapped — and it’s going to be a multi-trillion-dollar opportunity. I believe $AMD will be one of the biggest beneficiaries

Daniel

151,698 次观看 • 9 个月前

More than 800 people are in the field and hundreds more are behind the scenes working to restore service to our customers. Our focus today has been on assessing damage from the storm and restoring power to critical infrastructure—like hospitals—and main electrical feeders, like in #Yarmouth as seen here today. We do our best to give an estimate of when the power will be restored. Once our crews are able to assess damage to infrastructure, those estimates will be updated. The latest information is available on the outage map: #TropicalStormLee #NSStorm

More than 800 people are in the field and hundreds more are behind the scenes working to restore service to our customers. Our focus today has been on assessing damage from the storm and restoring power to critical infrastructure—like hospitals—and main electrical feeders, like in #Yarmouth as seen here today. We do our best to give an estimate of when the power will be restored. Once our crews are able to assess damage to infrastructure, those estimates will be updated. The latest information is available on the outage map: #TropicalStormLee #NSStorm

Nova Scotia Power

36,027 次观看 • 3 年前

Yann LeCun -- Meta's chief AI scientist and a Turing Award winner -- explains why scaling up LLMs will never reach human-level AI, and names the four things today's systems still can't do: "If you think that we're going to get to human-level AI by just training on more data and scaling up LLMs, you're making a mistake." "If you're an investor and you invest in a company that told you we're going to get to human-level AI and PhD level by just training on more data and with a few tricks... that was probably not a good idea." "There are ideas about how to go forward and have systems that are capable of doing what every intelligent animal and human are capable of doing, and that current AI systems are not capable of doing." "Understanding the physical world, having persistent memory, and being able to reason and plan. Those are the four characteristics that need to be there." "That requires systems that can acquire common sense, that can learn from natural sensors like video, as opposed to just text." The entire market is priced on a straight line from bigger models to AGI. One of the people who invented deep learning is telling you the line doesn't reach -- and that the real bottleneck isn't compute, it's world models. If he's right, the winner isn't whoever stacks the most GPUs. It's whoever teaches a machine to learn from video the way a child does.

Yann LeCun -- Meta's chief AI scientist and a Turing Award winner -- explains why scaling up LLMs will never reach human-level AI, and names the four things today's systems still can't do: "If you think that we're going to get to human-level AI by just training on more data and scaling up LLMs, you're making a mistake." "If you're an investor and you invest in a company that told you we're going to get to human-level AI and PhD level by just training on more data and with a few tricks... that was probably not a good idea." "There are ideas about how to go forward and have systems that are capable of doing what every intelligent animal and human are capable of doing, and that current AI systems are not capable of doing." "Understanding the physical world, having persistent memory, and being able to reason and plan. Those are the four characteristics that need to be there." "That requires systems that can acquire common sense, that can learn from natural sensors like video, as opposed to just text." The entire market is priced on a straight line from bigger models to AGI. One of the people who invented deep learning is telling you the line doesn't reach -- and that the real bottleneck isn't compute, it's world models. If he's right, the winner isn't whoever stacks the most GPUs. It's whoever teaches a machine to learn from video the way a child does.

Karl Mehta

34,847 次观看 • 3 个月前

From a single image, you can create CSI scenes in minutes with AI! all you need are the right prompts and models, and I’ll show you how to do it on Freepik just below 👇

From a single image, you can create CSI scenes in minutes with AI! all you need are the right prompts and models, and I’ll show you how to do it on Freepik just below 👇

TechHalla

89,316 次观看 • 9 个月前

Today, we're launching Belvedir We're making private AI models cheap and easy so the world can have trillions of them. Private AI models are cheaper, better, faster, and protect your data from frontier labs, but they're still to expensive and difficult to make for startups and consumers. Belvedir makes private AI models autonomously with less than 5 minutes of setup, so that private AI can finally be accessible to everyone

Today, we're launching Belvedir We're making private AI models cheap and easy so the world can have trillions of them. Private AI models are cheaper, better, faster, and protect your data from frontier labs, but they're still to expensive and difficult to make for startups and consumers. Belvedir makes private AI models autonomously with less than 5 minutes of setup, so that private AI can finally be accessible to everyone

Zachary Yu

88,832 次观看 • 1 个月前

#WATCH | India AI Impact Summit 2026 | Delhi: Founder Chairman and CEO of Sampark Foundation & former CEO of HCL Technologies, Vineet Nayar says, "...From an employment point of view I think it is very important for us to understand that Indian companies, including Indian IT companies, are going to be profit-driven and therefore if you believe that they are going to create employment you must be dreaming. Therefore, the question is how do we create employment in this environment, and that employment comes from mass scale startups, which is what this government has already doing. So, how do we create new sets of people who are trying to solve new sets of problems not new sets of technology and if we do that we will get it right. I think we as Indians have to be very careful on who does data belong to and that is the debate we have a problem with. The LLM models which exist worldwide are far superior than the Indian models. Unfortunately, in India, we never develop products, so therefore we do not have SLMs and LLMs which are world-class. On one side, we have global LLM products which are coming to India and trading on our Indian data. Should we allowed that or should we not allowed that? But on the other side if we don't allow that then we have the data but we don't have the LLM models. So, how do we encourage technology completely to develop the LLM models. This needs radicals strategic thinking and a very important aspect otherwise we will either give up a data. So, I think it's a very critical aspect for us to think about - who does this data belong, what is the kind of incentives we are going to give to develop LLM technologies or SLM technologies fast so that we train on our data otherwise an LLM will come in with our data and we'll immediately see return and we'll celebrate and we will do all these kind of press releases but the India will lose a competitive advantage on something which is very critical for the next decade."

#WATCH | India AI Impact Summit 2026 | Delhi: Founder Chairman and CEO of Sampark Foundation & former CEO of HCL Technologies, Vineet Nayar says, "...From an employment point of view I think it is very important for us to understand that Indian companies, including Indian IT companies, are going to be profit-driven and therefore if you believe that they are going to create employment you must be dreaming. Therefore, the question is how do we create employment in this environment, and that employment comes from mass scale startups, which is what this government has already doing. So, how do we create new sets of people who are trying to solve new sets of problems not new sets of technology and if we do that we will get it right. I think we as Indians have to be very careful on who does data belong to and that is the debate we have a problem with. The LLM models which exist worldwide are far superior than the Indian models. Unfortunately, in India, we never develop products, so therefore we do not have SLMs and LLMs which are world-class. On one side, we have global LLM products which are coming to India and trading on our Indian data. Should we allowed that or should we not allowed that? But on the other side if we don't allow that then we have the data but we don't have the LLM models. So, how do we encourage technology completely to develop the LLM models. This needs radicals strategic thinking and a very important aspect otherwise we will either give up a data. So, I think it's a very critical aspect for us to think about - who does this data belong, what is the kind of incentives we are going to give to develop LLM technologies or SLM technologies fast so that we train on our data otherwise an LLM will come in with our data and we'll immediately see return and we'll celebrate and we will do all these kind of press releases but the India will lose a competitive advantage on something which is very critical for the next decade."

ANI

18,753 次观看 • 7 个月前

I'm teaching a new course! AI Python for Beginners is a series of four short courses that teach anyone to code, regardless of current technical skill. We are offering these courses free for a limited time. Generative AI is transforming coding. This course teaches coding in a way that’s aligned with where the field is going, rather than where it has been: (1) AI as a Coding Companion. Experienced coders are using AI to help write snippets of code, debug code, and the like. We embrace this approach and describe best-practices for coding with a chatbot. Throughout the course, you'll have access to an AI chatbot that will be your own coding companion that can assist you every step of the way as you code. (2) Learning by Building AI Applications. You'll write code that interacts with large language models to quickly create fun applications to customize poems, write recipes, and manage a to-do list. This hands-on approach helps you see how writing code that calls on powerful AI models will make you more effective in your work and personal projects. With this approach, beginning programmers can learn to do useful things with code far faster than they could have even a year ago. Knowing a little bit of coding is increasingly helping people in job roles other than software engineers. For example, I've seen a marketing professional write code to download web pages and use generative AI to derive insights; a reporter write code to flag important stories; and an investor automate the initial drafts of contracts. With this course you’ll be equipped to automate repetitive tasks, analyze data more efficiently, and leverage AI to enhance your productivity. If you are already an experienced developer, please help me spread the word and encourage your non-developer friends to learn a little bit of coding. I hope you'll check out the first two short courses here!

I'm teaching a new course! AI Python for Beginners is a series of four short courses that teach anyone to code, regardless of current technical skill. We are offering these courses free for a limited time. Generative AI is transforming coding. This course teaches coding in a way that’s aligned with where the field is going, rather than where it has been: (1) AI as a Coding Companion. Experienced coders are using AI to help write snippets of code, debug code, and the like. We embrace this approach and describe best-practices for coding with a chatbot. Throughout the course, you'll have access to an AI chatbot that will be your own coding companion that can assist you every step of the way as you code. (2) Learning by Building AI Applications. You'll write code that interacts with large language models to quickly create fun applications to customize poems, write recipes, and manage a to-do list. This hands-on approach helps you see how writing code that calls on powerful AI models will make you more effective in your work and personal projects. With this approach, beginning programmers can learn to do useful things with code far faster than they could have even a year ago. Knowing a little bit of coding is increasingly helping people in job roles other than software engineers. For example, I've seen a marketing professional write code to download web pages and use generative AI to derive insights; a reporter write code to flag important stories; and an investor automate the initial drafts of contracts. With this course you’ll be equipped to automate repetitive tasks, analyze data more efficiently, and leverage AI to enhance your productivity. If you are already an experienced developer, please help me spread the word and encourage your non-developer friends to learn a little bit of coding. I hope you'll check out the first two short courses here!

Andrew Ng

1,226,013 次观看 • 2 年前

Rep. Roy on One Big Beautiful Bill: “In my view, we still need to get the bill right and right now, I don't think the bill is right. I didn't come to Washington to make deficits worse. As much as I want the tax cuts to be extended, and I do. As much as that is important for the average hard working family, it is. As much as I think that we've made some improvements on Medicaid, that we've done some good on the inflation Reduction Act subsidies, we're still far away from where we need to be.”

Rep. Roy on One Big Beautiful Bill: “In my view, we still need to get the bill right and right now, I don't think the bill is right. I didn't come to Washington to make deficits worse. As much as I want the tax cuts to be extended, and I do. As much as that is important for the average hard working family, it is. As much as I think that we've made some improvements on Medicaid, that we've done some good on the inflation Reduction Act subsidies, we're still far away from where we need to be.”

Rep. Chip Roy Press Office

48,089 次观看 • 1 年前

Netlify CEO Matt Biilmann on software development going from being a job to being a baseline skill: "Today you’re either a developer or not." "I think software development will just be a skill." "Just like with writing, there will still be professional writers, but all of us also have to know how to write as part of our jobs." "There'll still be some expert developers... but it’ll be the minority." Matt Biilmann Netlify martin_casado

Netlify CEO Matt Biilmann on software development going from being a job to being a baseline skill: "Today you’re either a developer or not." "I think software development will just be a skill." "Just like with writing, there will still be professional writers, but all of us also have to know how to write as part of our jobs." "There'll still be some expert developers... but it’ll be the minority." Matt Biilmann Netlify martin_casado

a16z

40,895 次观看 • 8 个月前

We're coming out of stealth to announce our cyber defense research lab. We are exploring data and post-training techniques to build superhuman cyber defenders. Our mission is to make sure the West always wins. The last 3 months we've built an automated data pipeline to create training data from 80k CVEs (aka public vulnerabilities). Our next topic? Post training a model that's better at fixing all the vulnerabilities in your codebase. Like really fixing them. Not saying it's secure when there are still ways to exploit them. Here are the questions that keep us awake at night: How do you train a model to defend without improving its capabilities to attack? What's the right reward? How to measure the defense capabilities? How do you create synth training data that reproduces real systems? What kind of access do you give an ai cyber defender? How far can you trust it? If you know insanely good cyber experts (red team, blue team, CTF aficionados) or ML engineers (synth data generation and post-training models), send them my way. We need to make models far better at defending.

We're coming out of stealth to announce our cyber defense research lab. We are exploring data and post-training techniques to build superhuman cyber defenders. Our mission is to make sure the West always wins. The last 3 months we've built an automated data pipeline to create training data from 80k CVEs (aka public vulnerabilities). Our next topic? Post training a model that's better at fixing all the vulnerabilities in your codebase. Like really fixing them. Not saying it's secure when there are still ways to exploit them. Here are the questions that keep us awake at night: How do you train a model to defend without improving its capabilities to attack? What's the right reward? How to measure the defense capabilities? How do you create synth training data that reproduces real systems? What kind of access do you give an ai cyber defender? How far can you trust it? If you know insanely good cyber experts (red team, blue team, CTF aficionados) or ML engineers (synth data generation and post-training models), send them my way. We need to make models far better at defending.

Paco Villetard

121,071 次观看 • 5 个月前

You don't need to memorize a dozen Git commands on day one. Start with the visual tools in VS Code, learn what commits and branches actually do, and build from there. That's exactly what we're covering in our latest GitHub for Beginners episode.

You don't need to memorize a dozen Git commands on day one. Start with the visual tools in VS Code, learn what commits and branches actually do, and build from there. That's exactly what we're covering in our latest GitHub for Beginners episode.

GitHub

24,609 次观看 • 3 个月前

Waymo Co-CEO on Waymo’s sensor approach in a new Bloomberg interview: “If you can see and smell and taste and have all of your senses—why wouldn’t you? Especially with a safety-critical function, we think it’s very important to take in as much data as possible to inform the models and achieve the outcomes. Then we can debate how we go forward from there. This has been critical to our approach.”

Waymo Co-CEO on Waymo’s sensor approach in a new Bloomberg interview: “If you can see and smell and taste and have all of your senses—why wouldn’t you? Especially with a safety-critical function, we think it’s very important to take in as much data as possible to inform the models and achieve the outcomes. Then we can debate how we go forward from there. This has been critical to our approach.”

Nic Cruz Patane

34,405 次观看 • 7 个月前

Today we're announcing Base Labs, a dedicated research organization focused on advancing open-source AI. We believe in a healthy, open frontier model ecosystem. To enable this, we are working on: - Blue-sky research on continual learning, the science of RL, and how models learn across their full lifecycle, with every experiment and recipe shared openly. - The BaseHub Data Foundry: the highest-quality open RL environments, training data, and real-world benchmarks, built for anyone to train and benchmark on. - Post-post training: taking open-source models and making them better, safer, and more aligned through continual post-training, built on our research, and deployed with our frontier safety stack so organizations can use open-source models with confidence. - Making models cheaper and more performant through our model performance research. This is a mission-driven research effort, not a commercial product. We believe the health of the open-source AI ecosystem matters and that the best way to advance it is to do science in the open. We’re hiring engineers, researchers, and research fellows to advance this mission.

Today we're announcing Base Labs, a dedicated research organization focused on advancing open-source AI. We believe in a healthy, open frontier model ecosystem. To enable this, we are working on: - Blue-sky research on continual learning, the science of RL, and how models learn across their full lifecycle, with every experiment and recipe shared openly. - The BaseHub Data Foundry: the highest-quality open RL environments, training data, and real-world benchmarks, built for anyone to train and benchmark on. - Post-post training: taking open-source models and making them better, safer, and more aligned through continual post-training, built on our research, and deployed with our frontier safety stack so organizations can use open-source models with confidence. - Making models cheaper and more performant through our model performance research. This is a mission-driven research effort, not a commercial product. We believe the health of the open-source AI ecosystem matters and that the best way to advance it is to do science in the open. We’re hiring engineers, researchers, and research fellows to advance this mission.

Base Labs

241,481 次观看 • 27 天前