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Real-time world models represent a fundamental shift in AI. reactor is building the platform for real-time generative video infrastructure, supporting developers who need the tech for use across entertainment, physical AI, and robotics. Co-founders Alberto and Bryce Schmidtchen joined us last week on The Investment Memo, hosted by Partners...

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Lightspeed

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144,942 просмотров • 3 месяцев назад •via X (Twitter)

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Today Reactor is coming out of stealth. We’ve raised $59M in Seed and Series A funding, led by Lightspeed, with participation from Amplify Partners, wndrco, Sky9 Capital, and FPV Ventures. Reactor is the platform for building in the World Model era: the infrastructure that lets developers build with them at global scale for the first time. Stream from a frontier World Model to your app, in real time, all in under 10 lines of code. World Models represent the next major shift in AI: pixels, audio and actions are generated on the fly, in real-time, in response to user inputs, and to the environment. Every time computing has made a shift from passive to interactive, entire industries appeared that didn't exist before. We're standing in front of such moment again. Over the last 6 months, we’ve assembled an all-star team with alumni from Apple, Meta, Google, Luma AI, Netflix, and Replicate. We're already partnering with some of the biggest names and labs in the world, and hundreds of developers are already building on Reactor. The World Model era starts now.
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Today Reactor is coming out of stealth. We’ve raised $59M in Seed and Series A funding, led by Lightspeed, with participation from Amplify Partners, wndrco, Sky9 Capital, and FPV Ventures. Reactor is the platform for building in the World Model era: the infrastructure that lets developers build with them at global scale for the first time. Stream from a frontier World Model to your app, in real time, all in under 10 lines of code. World Models represent the next major shift in AI: pixels, audio and actions are generated on the fly, in real-time, in response to user inputs, and to the environment. Every time computing has made a shift from passive to interactive, entire industries appeared that didn't exist before. We're standing in front of such moment again. Over the last 6 months, we’ve assembled an all-star team with alumni from Apple, Meta, Google, Luma AI, Netflix, and Replicate. We're already partnering with some of the biggest names and labs in the world, and hundreds of developers are already building on Reactor. The World Model era starts now.

reactor

12,739,249 просмотров • 4 месяцев назад

AI models are upgrading at a new speed. OpenAI’s GPT-6 Astra model, released last week, follows a self-controlled “chain-of-thought” reasoning pattern that can evade certain kinds of monitoring. The next value differentiator for improved models may be less about performance and more about auditability. More on Lightwork this week: → ByteDance is working towards releasing a new real-time world model, pressuring Western frontier labs to keep pace. → Personal agents like Meta’s Muse and Instinct are gaining popularity, raising a conversation over personal autonomy with agents. → Some applications are throttling agent traffic. What does this mean for the companies building them? Claire Zau Josh Machiz Bucky Moore 0:00 Welcome, Bucky Moore! 1:12 OpenAI's Astra 3:50 The New AI Model’s Architecture 4:40 AI Safety and Guardrails 8:01 Trusting AI Agents 11:09 The Future of AI Models 12:06 The AI Agent Land Grab 17:09 AI, Trust, and Personal Data 20:12 Improving AI Agent Capabilities 22:11 Enterprise AI Assistants and Personal Context 24:05 AI Agents and the Future of the Web 25:50 ByteDance and World Models 28:19 World Models and Consumer Content 30:56 Reactor and World Model Infrastructure 34:13 Real-Time Video Models and Scaling
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AI models are upgrading at a new speed. OpenAI’s GPT-6 Astra model, released last week, follows a self-controlled “chain-of-thought” reasoning pattern that can evade certain kinds of monitoring. The next value differentiator for improved models may be less about performance and more about auditability. More on Lightwork this week: → ByteDance is working towards releasing a new real-time world model, pressuring Western frontier labs to keep pace. → Personal agents like Meta’s Muse and Instinct are gaining popularity, raising a conversation over personal autonomy with agents. → Some applications are throttling agent traffic. What does this mean for the companies building them? Claire Zau Josh Machiz Bucky Moore 0:00 Welcome, Bucky Moore! 1:12 OpenAI's Astra 3:50 The New AI Model’s Architecture 4:40 AI Safety and Guardrails 8:01 Trusting AI Agents 11:09 The Future of AI Models 12:06 The AI Agent Land Grab 17:09 AI, Trust, and Personal Data 20:12 Improving AI Agent Capabilities 22:11 Enterprise AI Assistants and Personal Context 24:05 AI Agents and the Future of the Web 25:50 ByteDance and World Models 28:19 World Models and Consumer Content 30:56 Reactor and World Model Infrastructure 34:13 Real-Time Video Models and Scaling

Lightspeed

15,012 просмотров • 1 месяц назад

A Walk In The Park (part II) feat Alberto 🌎 (00:00) 👋 (01:10) What world models are (03:42) Origin story from text-to-3D to reactor (09:22) Deciding to start the company (11:22) GTA, games, and the path into programming (15:09) Building in stealth and keeping secrets (18:32) Picking investors with independent conviction (21:43) Where world models will grow first (26:08) Why low latency matters (29:34) Becoming CEO and scaling the team (32:23) Final advice
32:50

A Walk In The Park (part II) feat Alberto 🌎 (00:00) 👋 (01:10) What world models are (03:42) Origin story from text-to-3D to reactor (09:22) Deciding to start the company (11:22) GTA, games, and the path into programming (15:09) Building in stealth and keeping secrets (18:32) Picking investors with independent conviction (21:43) Where world models will grow first (26:08) Why low latency matters (29:34) Becoming CEO and scaling the team (32:23) Final advice

Nikunj Kothari

24,897 просмотров • 4 месяцев назад

From satellites to skincare, France is building with NVIDIA. 🇫🇷 Developers, researchers, and businesses across France are using NVIDIA technology and open models to bring AI into the real world. Explore France’s AI ecosystem: Meet two of the people building it. 🧵
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From satellites to skincare, France is building with NVIDIA. 🇫🇷 Developers, researchers, and businesses across France are using NVIDIA technology and open models to bring AI into the real world. Explore France’s AI ecosystem: Meet two of the people building it. 🧵

NVIDIA

39,558 просмотров • 1 день назад

SITUATION EXPLAINED: A new generation of AI labs are betting that world models are the path to general intelligence that can interact with the real world. We had General Intuition CEO Pim de Witte on MTS to explain what world models are, and why intuitively world models offer a clearer path towards general intelligence than LLMs. For humans, text is a technology for compressing information about the unfolding, three-dimensional world around us and communicating it to other people. When LLMs reason about the world, they do so by reconstructing the world through text. World models work by modeling the three-dimensional world at the architecture level and then allowing agents to interact with that world. Unlike an LLM, which understands space and time through text, world models perform spatial and temporal reasoning natively. General Intuition hopes to use world models to create embodied AI—machines that can reason and act in the real world. But other companies are also pushing the frontier in this space. Odyssey ML today announced a multi-agent world model, Agora-1. Their launch video shows four participants interacting with a real-time world model simulation of GoldenEye, a first-person shooter for the N64. A playable preview of the GoldenEye simulation is available on their site.
1:31

SITUATION EXPLAINED: A new generation of AI labs are betting that world models are the path to general intelligence that can interact with the real world. We had General Intuition CEO Pim de Witte on MTS to explain what world models are, and why intuitively world models offer a clearer path towards general intelligence than LLMs. For humans, text is a technology for compressing information about the unfolding, three-dimensional world around us and communicating it to other people. When LLMs reason about the world, they do so by reconstructing the world through text. World models work by modeling the three-dimensional world at the architecture level and then allowing agents to interact with that world. Unlike an LLM, which understands space and time through text, world models perform spatial and temporal reasoning natively. General Intuition hopes to use world models to create embodied AI—machines that can reason and act in the real world. But other companies are also pushing the frontier in this space. Odyssey ML today announced a multi-agent world model, Agora-1. Their launch video shows four participants interacting with a real-time world model simulation of GoldenEye, a first-person shooter for the N64. A playable preview of the GoldenEye simulation is available on their site.

MTS

11,693 просмотров • 4 месяцев назад

Introducing Deft Robotics' unified deployment platform for physical AI. Frontier models are moving fast. Real world autonomy isn’t. Closing the gap takes more than better models. The missing piece? Infrastructure to deploy, intervene, learn from failures, and continuously improve. For the past year, we’ve been deploying in that gap and building the stack to close it. Now, we’re opening it up. Hardware available now. Software in beta. Here’s how to use it for your use-case 🧵(1/7) ↓
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Introducing Deft Robotics' unified deployment platform for physical AI. Frontier models are moving fast. Real world autonomy isn’t. Closing the gap takes more than better models. The missing piece? Infrastructure to deploy, intervene, learn from failures, and continuously improve. For the past year, we’ve been deploying in that gap and building the stack to close it. Now, we’re opening it up. Hardware available now. Software in beta. Here’s how to use it for your use-case 🧵(1/7) ↓

Shane

16,204 просмотров • 1 месяц назад

🦙 ollama is used by 9 million developers and 85% of the Fortune 500, giving co-founder and CEO Jeffrey Morgan (Jeffrey Morgan) a unique view into which AI models people are actually using and how that’s changing. Right now, the biggest shift he sees is toward open models, driven by coding agents, falling costs, and capabilities that are rapidly catching up to the frontier labs. On Ollama Cloud, that shift has driven a 150x increase in token usage since the start of the year. In this episode of Lightcone Podcast, Jeff joins Garry Tan, Jared Friedman, Diana, and Harj Taggar to talk about the future of open models and the story behind Ollama, from two years of searching for the right idea to building one of the most widely used AI developer tools in the world. 00:43 — The Shift to Open Models 03:03 — How AI Agents Are Driving Token Usage 05:31 — Are Open Models Catching Up? 08:26 — What Happens When a New Model Launches 11:31 — Ollama as an Operating System for AI 14:05 — The New Opportunities Above the Model Layer 18:19 — Why 80–90% of Enterprise Tokens Could Be Open 20:57 — The Future Is Local and Cloud 26:40 — Why AI Is Coming Back to Your Computer 28:56 — The Coming Era of Unlimited Tokens 32:30 — Do We Still Need a “God Model”? 33:41 — Open Models and Geopolitics 36:14 — The Origins of Ollama 40:36 — Two Years Lost in the Wilderness 42:39 — The Pivot That Changed Everything 47:02 — How Ollama Found a Business Model 49:43 — Why Second-Time Founders Did YC
57:15

🦙 ollama is used by 9 million developers and 85% of the Fortune 500, giving co-founder and CEO Jeffrey Morgan (Jeffrey Morgan) a unique view into which AI models people are actually using and how that’s changing. Right now, the biggest shift he sees is toward open models, driven by coding agents, falling costs, and capabilities that are rapidly catching up to the frontier labs. On Ollama Cloud, that shift has driven a 150x increase in token usage since the start of the year. In this episode of Lightcone Podcast, Jeff joins Garry Tan, Jared Friedman, Diana, and Harj Taggar to talk about the future of open models and the story behind Ollama, from two years of searching for the right idea to building one of the most widely used AI developer tools in the world. 00:43 — The Shift to Open Models 03:03 — How AI Agents Are Driving Token Usage 05:31 — Are Open Models Catching Up? 08:26 — What Happens When a New Model Launches 11:31 — Ollama as an Operating System for AI 14:05 — The New Opportunities Above the Model Layer 18:19 — Why 80–90% of Enterprise Tokens Could Be Open 20:57 — The Future Is Local and Cloud 26:40 — Why AI Is Coming Back to Your Computer 28:56 — The Coming Era of Unlimited Tokens 32:30 — Do We Still Need a “God Model”? 33:41 — Open Models and Geopolitics 36:14 — The Origins of Ollama 40:36 — Two Years Lost in the Wilderness 42:39 — The Pivot That Changed Everything 47:02 — How Ollama Found a Business Model 49:43 — Why Second-Time Founders Did YC

Y Combinator

313,654 просмотров • 1 месяц назад

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
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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 просмотров • 10 месяцев назад

Before AI can understand the physical world, it needs data about the physical world. Not just images. Spatial environments. Real streets, buildings, parks, stores, museums, and public spaces captured in 3D. OVER has already reconstructed 290,000+ real-world 3D scenes, creating a growing dataset for the next generation of spatial and embodied AI. And this is exactly the kind of real-world spatial data AI companies are looking for. We're already in conversations with multiple AI and Robotics companies exploring how OVER's dataset can support the development and training of models that need to understand the physical world. The next AI race will be about real-world data.
1:47

Before AI can understand the physical world, it needs data about the physical world. Not just images. Spatial environments. Real streets, buildings, parks, stores, museums, and public spaces captured in 3D. OVER has already reconstructed 290,000+ real-world 3D scenes, creating a growing dataset for the next generation of spatial and embodied AI. And this is exactly the kind of real-world spatial data AI companies are looking for. We're already in conversations with multiple AI and Robotics companies exploring how OVER's dataset can support the development and training of models that need to understand the physical world. The next AI race will be about real-world data.

Over the Reality 🌐

24,152 просмотров • 18 дней назад

Explore where physical AI is headed next with the people shaping it. On Feb. 10 at 9 a.m. PT, join Ming‑Yu, Vice President of Research at NVIDIA, and Chubby♨️ from Superintelligence, for a conversation on how NVIDIA Cosmos reframes AI for a world of robots, AVs, and vision-driven systems. We'll dig into: ✅ Cosmos' origins and designing models for the physical world ✅ The scientific ideas and architectures behind Cosmos and its open models ✅ How open, reasoning-capable physical AI is changing how teams prototype, deploy, and iterate ✅ What a future of AI systems that understand space, time, and causality could unlock If you’re thinking into real‑world AI, this is the conversation to catch ➡️
0:39

Explore where physical AI is headed next with the people shaping it. On Feb. 10 at 9 a.m. PT, join Ming‑Yu, Vice President of Research at NVIDIA, and Chubby♨️ from Superintelligence, for a conversation on how NVIDIA Cosmos reframes AI for a world of robots, AVs, and vision-driven systems. We'll dig into: ✅ Cosmos' origins and designing models for the physical world ✅ The scientific ideas and architectures behind Cosmos and its open models ✅ How open, reasoning-capable physical AI is changing how teams prototype, deploy, and iterate ✅ What a future of AI systems that understand space, time, and causality could unlock If you’re thinking into real‑world AI, this is the conversation to catch ➡️

NVIDIA AI Developer

26,471 просмотров • 8 месяцев назад

AG1 Residency Program is a 10-week residency in Tokyo where founders from around the world live together, build together, and focus intensely on creating great products. Applications for Batch 3 are now open! Every batch, AG1 brings founders to Tokyo from across the world, including the US, China, Korea, and many other countries. For Batch 3, there is one type of founder we’re particularly excited to meet: Founders using AI not just to build better software, but to build new infrastructure and products that make AI accessible to ordinary people. We believe the next wave of AI will not only be about better models. It will be about turning intelligence into something people can actually use in their everyday lives, across work, commerce, education, entertainment, and the physical world. And we think Japan is one of the most interesting places in the world to build this: Japan is one of the world’s most advanced economies, yet many parts of society remain surprisingly under-digitized. There is still a huge gap between what technology can do and what people actually use every day. That gap creates an unusually fertile environment for founders: strong infrastructure, sophisticated consumers, large incumbent industries, and countless workflows that AI can fundamentally reinvent. If you want to build products that bring AI out of the lab and into the real world, we want you at AG1. It’s a rare opportunity to spend 10 weeks in Tokyo living and building side by side with ambitious founders from all over the world. And most importantly, check out the new AG1 video we just made! Applications and shares are very much appreciated 👇
1:15

AG1 Residency Program is a 10-week residency in Tokyo where founders from around the world live together, build together, and focus intensely on creating great products. Applications for Batch 3 are now open! Every batch, AG1 brings founders to Tokyo from across the world, including the US, China, Korea, and many other countries. For Batch 3, there is one type of founder we’re particularly excited to meet: Founders using AI not just to build better software, but to build new infrastructure and products that make AI accessible to ordinary people. We believe the next wave of AI will not only be about better models. It will be about turning intelligence into something people can actually use in their everyday lives, across work, commerce, education, entertainment, and the physical world. And we think Japan is one of the most interesting places in the world to build this: Japan is one of the world’s most advanced economies, yet many parts of society remain surprisingly under-digitized. There is still a huge gap between what technology can do and what people actually use every day. That gap creates an unusually fertile environment for founders: strong infrastructure, sophisticated consumers, large incumbent industries, and countless workflows that AI can fundamentally reinvent. If you want to build products that bring AI out of the lab and into the real world, we want you at AG1. It’s a rare opportunity to spend 10 weeks in Tokyo living and building side by side with ambitious founders from all over the world. And most importantly, check out the new AG1 video we just made! Applications and shares are very much appreciated 👇

Luke LI@Asu Capital Partners--e/acc

72,663 просмотров • 1 месяц назад

“Is there an AI bubble?” Gavin Baker and David George In this conversation from a16z’s Runtime conference, Gavin Baker, Managing Partner and CIO of Atreides Management, joins David George, General Partner at a16z, to unpack the macro view of AI: the trillion-dollar data center buildout, the new economics of GPUs, and what this boom means for investors, founders, and the global economy. They discuss how this cycle compares to the dot-com era, why “there are no dark GPUs,” and what makes today’s infrastructure spending different from past bubbles. Gavin explains why he believes we’re still early in the AI supercycle, the changing margins in SaaS and software, and how business models and consumer interfaces are being rewritten in real time. 00:00 Intro 01:02 Are we in an AI Bubble? 02:41 Dark fiber vs. “no dark GPUs” 05:07 ROI on AI: Why this time is different 08:36 Round-tripping deals 12:22 The application layer: It’s still early 15:24 Margins, scaling laws 23:26 Reasoning models and the flywheel 27:18 The future of business models 29:41 Robotics and Elon’s Optimus vision Gavin Baker David George
31:52

“Is there an AI bubble?” Gavin Baker and David George In this conversation from a16z’s Runtime conference, Gavin Baker, Managing Partner and CIO of Atreides Management, joins David George, General Partner at a16z, to unpack the macro view of AI: the trillion-dollar data center buildout, the new economics of GPUs, and what this boom means for investors, founders, and the global economy. They discuss how this cycle compares to the dot-com era, why “there are no dark GPUs,” and what makes today’s infrastructure spending different from past bubbles. Gavin explains why he believes we’re still early in the AI supercycle, the changing margins in SaaS and software, and how business models and consumer interfaces are being rewritten in real time. 00:00 Intro 01:02 Are we in an AI Bubble? 02:41 Dark fiber vs. “no dark GPUs” 05:07 ROI on AI: Why this time is different 08:36 Round-tripping deals 12:22 The application layer: It’s still early 15:24 Margins, scaling laws 23:26 Reasoning models and the flywheel 27:18 The future of business models 29:41 Robotics and Elon’s Optimus vision Gavin Baker David George

a16z

92,161 просмотров • 11 месяцев назад

Missed the World Models talk featuring Daniel Berkovitz, Chief Product Officer, @LTXStudio and Ben Michel of Asteria at #RenderCon2026? Here's what was covered: 00:08 - Intro: Why open source video models matter for Render Network 02:13 - LTX's philosophy on open source and building tools for creative professionals 06:01 - Running LTX over a 3D viewport to get a final render 17:22 - Why generative video needs to move past the "slot machine" experience 20:27 - The case for multi-keyframe conditioning 27:53 - Why video models are rendering engines, not prompt interfaces Full talk:
43:25

Missed the World Models talk featuring Daniel Berkovitz, Chief Product Officer, @LTXStudio and Ben Michel of Asteria at #RenderCon2026? Here's what was covered: 00:08 - Intro: Why open source video models matter for Render Network 02:13 - LTX's philosophy on open source and building tools for creative professionals 06:01 - Running LTX over a 3D viewport to get a final render 17:22 - Why generative video needs to move past the "slot machine" experience 20:27 - The case for multi-keyframe conditioning 27:53 - Why video models are rendering engines, not prompt interfaces Full talk:

The Render Network

17,798 просмотров • 4 месяцев назад

One of the biggest surprises in AI over the last few years has been how well coding agents generalize beyond software. In a recent essay, MIT professor Philip Isola argued that we may be entering the era of robot-use agents: general-purpose models that can control different robots, write policies, and learn new physical tasks with little or no robot-specific training. In this episode of Decoded, we're joined by the founders of Waddle Labs and Robocurve PBC, two of the startups whose work helped drive this realization. They're working at the frontier of using general-purpose models to control robots, and their recent demos helped inspire the growing conversation around robot-use agents. Together, we dig into the research behind that idea, from code-as-policies and vision-language-action models to the harnesses and evals needed to make these systems work in the real world. 00:00 — What Are Robot-Use Agents? 02:11 — From Vision-Language-Action Models to General LLMs 04:07 — The Bitter Lesson for Robotics 07:04 — How Coding Agents Learned to Control Robots 10:41 — How Robots Learn From Experience 14:22 — The Harness as a Form of Robot Intelligence 16:14 — Watching Astra Control a Robot 20:55 — Why General Models May Win in Robotics 26:05 — How Close Are General-Purpose Robots?
29:49

One of the biggest surprises in AI over the last few years has been how well coding agents generalize beyond software. In a recent essay, MIT professor Philip Isola argued that we may be entering the era of robot-use agents: general-purpose models that can control different robots, write policies, and learn new physical tasks with little or no robot-specific training. In this episode of Decoded, we're joined by the founders of Waddle Labs and Robocurve PBC, two of the startups whose work helped drive this realization. They're working at the frontier of using general-purpose models to control robots, and their recent demos helped inspire the growing conversation around robot-use agents. Together, we dig into the research behind that idea, from code-as-policies and vision-language-action models to the harnesses and evals needed to make these systems work in the real world. 00:00 — What Are Robot-Use Agents? 02:11 — From Vision-Language-Action Models to General LLMs 04:07 — The Bitter Lesson for Robotics 07:04 — How Coding Agents Learned to Control Robots 10:41 — How Robots Learn From Experience 14:22 — The Harness as a Form of Robot Intelligence 16:14 — Watching Astra Control a Robot 20:55 — Why General Models May Win in Robotics 26:05 — How Close Are General-Purpose Robots?

Y Combinator

93,369 просмотров • 17 дней назад

Today we're incredibly excited to announce Dreamscale Labs (YC F26) (YC F26)! We're an applied research company putting robot brains in the cloud. Robot AI models are growing larger and on-board compute is getting increasingly inaccessible due to cost. We're taking a contrarian bet that the future is moving inference off the robot and into the cloud, while still meeting real-time deadlines required by robot motion. We're building the real-time inference infrastructure that enables frontier physical AI models to run smoothly on your robot. We optimize for low latency across the full stack: from the model, down to the GPU kernels, and over the network. Our mission is to unlock a future of safe and intelligent robots doing meaningful work, and we think this is only possible by letting you deploy and run robot models in the cloud. Reach out to us at founders@dreamscalelabs.com or visit our website at to learn more. Kevin L Antoine Nguyen Eric R
1:50

Today we're incredibly excited to announce Dreamscale Labs (YC F26) (YC F26)! We're an applied research company putting robot brains in the cloud. Robot AI models are growing larger and on-board compute is getting increasingly inaccessible due to cost. We're taking a contrarian bet that the future is moving inference off the robot and into the cloud, while still meeting real-time deadlines required by robot motion. We're building the real-time inference infrastructure that enables frontier physical AI models to run smoothly on your robot. We optimize for low latency across the full stack: from the model, down to the GPU kernels, and over the network. Our mission is to unlock a future of safe and intelligent robots doing meaningful work, and we think this is only possible by letting you deploy and run robot models in the cloud. Reach out to us at [email protected] or visit our website at to learn more. Kevin L Antoine Nguyen Eric R

Chris Yoo

48,856 просмотров • 26 дней назад

Today’s the day🚀 We’re opening the doors to the Daydream platform - API + Playground Experience🌊 We’re the world’s first hosted StreamDiffusion platform: 1⃣ No GPU required 2⃣Sub-second latency 3⃣Advanced controls that let you experiment quickly and scale seamlessly. This is the start of an open ecosystem for real-time video and world models. Your home for open source, real-time video AI 👇🧵
0:58

Today’s the day🚀 We’re opening the doors to the Daydream platform - API + Playground Experience🌊 We’re the world’s first hosted StreamDiffusion platform: 1⃣ No GPU required 2⃣Sub-second latency 3⃣Advanced controls that let you experiment quickly and scale seamlessly. This is the start of an open ecosystem for real-time video and world models. Your home for open source, real-time video AI 👇🧵

Daydream

94,889 просмотров • 1 год назад

> "In no scenario is it bad for the US to have frontier-class open-source models." > "Every time there’s a step-function improvement in AI, a human bottleneck emerges alongside it." > "Your desire to be liked sometimes takes away from your desire to do the right thing and seek the truth." > "Every job will get refactored. The people who aren’t AI fluent will have a very hard time finding jobs." Jeetu Patel (Jeetu Patel), President & Chief Product Officer at Cisco sat down for an expansive talk about life and the future. 00:00 AI, jobs, and human potential 00:41 AI cybersecurity and Cisco’s security models 06:33 Why Cisco released the models openly 08:08 Running AI models locally 10:12 Why people are negative about AI 12:14 Will humans always be needed? 14:56 Can curiosity and ambition be taught? 17:12 Passion vs. expertise 19:39 The importance of unlearning 23:52 How to find the truth 26:06 How to get people excited about AI 33:35 How open source affects the AI industry 35:07 Can open-source AI make money? 46:44 Are Chinese open-source models good for the US? 49:55 Should the US restrict Chinese AI models? 53:05 Does open source make humanity safer? 54:11 Advice for people worried about AI
57:20

> "In no scenario is it bad for the US to have frontier-class open-source models." > "Every time there’s a step-function improvement in AI, a human bottleneck emerges alongside it." > "Your desire to be liked sometimes takes away from your desire to do the right thing and seek the truth." > "Every job will get refactored. The people who aren’t AI fluent will have a very hard time finding jobs." Jeetu Patel (Jeetu Patel), President & Chief Product Officer at Cisco sat down for an expansive talk about life and the future. 00:00 AI, jobs, and human potential 00:41 AI cybersecurity and Cisco’s security models 06:33 Why Cisco released the models openly 08:08 Running AI models locally 10:12 Why people are negative about AI 12:14 Will humans always be needed? 14:56 Can curiosity and ambition be taught? 17:12 Passion vs. expertise 19:39 The importance of unlearning 23:52 How to find the truth 26:06 How to get people excited about AI 33:35 How open source affects the AI industry 35:07 Can open-source AI make money? 46:44 Are Chinese open-source models good for the US? 49:55 Should the US restrict Chinese AI models? 53:05 Does open source make humanity safer? 54:11 Advice for people worried about AI

Matthew Berman

69,339 просмотров • 2 месяцев назад

1/ New episode – Enabling AI Models to Drive Robots with Michael Cho - Rbt/Acc from BitRobot 🦾 Hosts: Connor Lovely 🎬 EV3 Sal We discuss: - Building the world's largest robotic driving dataset - Working with researchers from Google DeepMind - Launching a memecoin ($SAM) pre-TGE Timestamps: 00:00 - Introduction 01:47 - Intersection of Robotics and AI 02:50 - Real-World Evaluation vs. Digital AI 06:00 - The Importance of Real-World Testing 07:07 - Mapping and Navigation in Robotics 08:12 - Value of Real-World Data for AI 09:38 - Differences in Data Utility 13:07 - Exploring Different Robotic Form Factors 14:04 - Cross-Embodiment in Robotics 16:35 - Introduction to BitRobot 17:30 - Transition from Frotobots to BitRobot 22:05 - Future Plans for BitRobot 24:27 - Meme Coins in Community Building 27:46 - Conclusion Watch on all platforms below ⬇️
29:16

1/ New episode – Enabling AI Models to Drive Robots with Michael Cho - Rbt/Acc from BitRobot 🦾 Hosts: Connor Lovely 🎬 EV3 Sal We discuss: - Building the world's largest robotic driving dataset - Working with researchers from Google DeepMind - Launching a memecoin ($SAM) pre-TGE Timestamps: 00:00 - Introduction 01:47 - Intersection of Robotics and AI 02:50 - Real-World Evaluation vs. Digital AI 06:00 - The Importance of Real-World Testing 07:07 - Mapping and Navigation in Robotics 08:12 - Value of Real-World Data for AI 09:38 - Differences in Data Utility 13:07 - Exploring Different Robotic Form Factors 14:04 - Cross-Embodiment in Robotics 16:35 - Introduction to BitRobot 17:30 - Transition from Frotobots to BitRobot 22:05 - Future Plans for BitRobot 24:27 - Meme Coins in Community Building 27:46 - Conclusion Watch on all platforms below ⬇️

Proof of Coverage | Tech’s Creative Agency

10,748 просмотров • 1 год назад

🚨 NEW: DNI Director Jay Clayton tells Fox’s Bret Baier on AI: "I think this is a race that we need to win.” “And the reason... is if you talk to people who have seen what these models can do and are projecting what they will be able to do in the future, the power is immense.” “I believe that if we are the strongest country in the world, the world will be a much better place. And I look at AI frontier models in the very same framework."
4:46

🚨 NEW: DNI Director Jay Clayton tells Fox’s Bret Baier on AI: "I think this is a race that we need to win.” “And the reason... is if you talk to people who have seen what these models can do and are projecting what they will be able to do in the future, the power is immense.” “I believe that if we are the strongest country in the world, the world will be a much better place. And I look at AI frontier models in the very same framework."

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10,946 просмотров • 1 месяц назад