| Time | Entity | Sector | Event / capture |
|---|---|---|---|
| 10:30 AM ET | UBUber | 10:30 AM ETUBUber @TheRundownAI on X Top stories in robotics today: - Uber and Wayve bring robotaxis to London - Altman says OpenAI ‘will definitely’ build a humanoid - MIT’s AI shows what self-driving cars are thinking - Skild wants to teach robots with a single video https://t.co/rWKeG9fqxP | |
| 11:11 PM ET | — | 11:11 PM ET @Avin_lucia on X @Arifx0001 @BitRobotNetwork Great synergy leveraging high-end and affordable tools for teleop to scale AI efficiently | |
| 3:36 PM ET | 3:36 PM ET @HumanoidsHQ on X Stats time! Humanoid robot startups raised $8.6B this year. Almost none of them ship robots. The company shipping 44% of the world's humanoids is worth a fraction of the one still running pilots. Here's the humanoid money board, valuation vs what actually shipped: 1. Unitree. ~$53B market cap. $235M revenue in 2025, sells humanoids from $5,900. IPO popped roughly 460% in August. 2. Figure. $39B. A BMW pilot that has handled 90,000+ parts. 3. Skild AI. $14B+. Software only. No robot. 4. 1X Technologies. ~$10B reported. 10,000 preorders for its home robot in 5 days. 5. NEURA Robotics. ~$7B.… | ||
| 9:00 PM ET | 9:00 PM ET @XSeyvion on X Skild AI unveiled its S1 robot foundation model. They say a robot can learn a new task by watching a video of the task. That changes deployment. Instead of writing a fresh program for each job, an operator can demonstrate once and then ask the robot to repeat it. If the long tail of tasks becomes video based training, the fight shifts to safety checks that run before the robot touches the world. What task would you try first? | ||
| 8:36 PM ET | 8:36 PM ET The Robot Report: Skild AI unveils S1 robot foundation model | AI Understanding Back to News ProductAI Understanding briefing The Robot Report: Skild AI unveils S1 robot foundation model The Robot Report reports that Skild AI unveiled S1, a robot foundation model that the company says can learn complex tasks from a single human demonstration video and operate across multiple robot forms. By AI Understanding EditorialSeptember 1, 2026 at 12:36 AM UTCUpdatedSeptember 1, 2026 at 1:47 AM UTC6 min read Read the primary source The short version The Robot Report reports that Skild AI unveiled S1, a robot foundation model that the company says can learn complex tasks from a… | ||
| 8:00 PM ET | 8:00 PM ET Skild AI unveils S1 robot foundation model; ~$1.7B raised Brianna Wessling / The Robot Report (Firecrawl dated ~5 hours before Aug 31 evening): Skild AI unveiled S1, flagship robot foundation model. Company founded 2023 has raised nearly $1.7 billion. CEO Deepak Pathak: model uses in-context learning — add a video of a human doing a task in the prompt and the robot can follow; tasks shown are long-horizon, not 3-4 second demos; targeting tasks up to 10 minutes (repotting, coffee, pancakes). Omni-bodied (quadruped, humanoid, static arm); humanoid scale still pending. Pathak: coming weeks will show S1 helping in production; Fetch Robotics asset acquisition (from Zebra) is about deployment talent. Does not claim a ChatGPT moment yet. | ||
| 7:20 PM ET | 7:20 PM ET @ParadisLabs on X AI is still so early, but so bullish. We're witnessing a huge unlock of economic value with the adoption of AI models like Claude, and more recently, agents like Grok Bot. This then filters down into the most bullish of bull points for AI. Enterprise AI adoption increases productivity -> increases enterprise earnings -> increases token demand as a flywheel effect -> increases ROI for the AI labs -> increases demand for AI infra e.g. compute. I recently heard from an ex-colleague that a large consulting firm is increasing their AI spend by 100x at their London office for their back office… | ||
| 7:11 PM ET | SCSequoia Capital | 7:11 PM ETSCSequoia Capital @davidcao01 on X Fifteen years after "software is eating the world," Marc Andreessen's own firm just admitted atoms are eating software's margins. SUMMARY This is not an a16z story. a16z's $1.1B Machine Age Fund is simply the loudest confirmation yet of a rotation already underway across Silicon Valley's largest pools of capital — Sequoia Capital , Lightspeed , General Catalyst , and SoftBank have all made comparable moves in 2026. Global venture funding into physical AI hit $47.4B across 521 deals in H1 2026 — nearly 4x the prior half. For builders and investors in robotics, autonomous systems, and… | |
| 7:11 PM ET | 7:11 PM ET @Robot_AIsignals on X Show it once. That is the entire instruction. In a post published in August, Skild AI introduced S1, a robotics foundation model prompted with a video demonstration in place of a written command. The company says the same frozen weights then performed four tasks absent from its pre-training — potting a plant, cooking pancakes, brewing pour-over coffee, assembling a kit. Skild builds Skild Brain, which it calls the first unified robotics foundation model to generalise across both tasks and robot hardware. It raised $1.4bn in January at a valuation the company puts above $14 billion (company… | ||
| 10:56 AM ET | GEGeneralist | 10:56 AM ETGEGeneralist @chris_j_paxton on X In-Context Learning Results Hint at a “GPT Moment” for Robotics For general-purpose robots to be useful and economical, you need to be able to teach them new skills on the fly. And now we can see how this will work, with in-context long horizon video demonstrations shown by companies like Generalist, Skild, Rhoda, Rhoda, and RobbyAnt. The idea is simple: prompt with a demonstration, mixed video and proprioception information. Language isn't enough -- it doesn't specify the problem well enough. And it's starting to really work. more in blog post | |
| 10:02 AM ET | 10:02 AM ET @ThomasSmale on X $14B valuation. Pre-revenue. A handful of customers. That is Skild AI today. And it is not the outlier. Physical Intelligence: $11B Generalist: $2B to $3B in months, $600M raised Skild AI: $14B Three companies. Billions in capital. Almost no commercial traction between them. The thesis is simple. Someone builds the foundation model for robotics the way OpenAI built one for language. Find the winner early, own the platform forever. Here is the problem. LLMs were trained on trillions of words scraped from the open internet. That dataset already existed, and it was free. No equivalent exists for… | ||
| 6:09 AM ET | 6:09 AM ET @0xconglomerate on X Is it really possible for a robot to learn a new task from one human video, with zero fine-tuning? I’ve read a lot of hype around Skild’s S1, with some already calling it robotics’ “ChatGPT moment.” That sounded a bit absurd to me, so I looked into what’s actually going on 👇 ➦ What is @SkildAI actually claiming? I’ve written enough marketing material for AI, robotics, and tech companies that I’m usually skeptical when something sounds too good to be true. If you only saw the announcement post, you could easily think the robot just watches one human video and somehow learns the task from that… | ||
| 2:05 PM ET | 2:05 PM ET @rohanpaul_ai on X Robotics is more and more getting close to get its version of in-context learning. Skild just released S1, a robot foundation model that uses video demonstrations to define tasks instead of language instructions. Give S1 1 human video showing a long, multi-step task, and the robot executes it straight away. No retraining. No fine-tuning. If this scales, you pay the enormous data bill once during foundation-model training, then amortize it across thousands of new tasks through prompting. That could change the economics of robot learning completely. | ||
| 2:04 PM ET | 2:04 PM ET @DeryaTR_ on X This is super exciting advance in robotics AI! I believe S1 is the most impressive robot foundation model I had seen! S1, is a robot foundation model built to learn new manipulation tasks through in-context prompting In Skild’s internal benchmarks, S1 achieved a 66% step-success rate on unseen tasks versus 9% for a language-prompted model, while one video demonstration provided roughly the benefit of 380 post-training examples! | ||
| 1:41 PM ET | 1:41 PM ET Markets surge, track records fall, and in-context learning hits physical AI - Home - Posts - Markets surge, track records fall, and in-context learning hits physical AI Markets surge, track records fall, and in-context learning hits physical AI Unitree’s market whiplash, an 8.86s 100m sprint, and how in-context learning is ending heavy fine-tuning. Humanoids Daily Aug 25, 2026 This week brought a stark look at the tension defining modern humanoid robotics: the gap between capital market euphoria, athletic spectacle, and the unglamorous realities of industrial utility. Unitree's blockbuster Shanghai STAR Market listing initially saw shares rocket over 600% to an… | ||
| 1:34 PM ET | RHrhoda | 1:34 PM ETRHrhoda @chris_j_paxton on X This is the mark of a general purpose robot foundation model -- that it can be taught tasks from examples without training. We saw an early version of this from rhoda and a solid one last week from generalist, and now a really impressive, ten minute long one from skild. This to me does feel like the true gpt moment for robotics -- because if it truly generalizes, that means that you can really start deploying robots for anything, as developing robot skills becomes like prompting | |
| 1:21 PM ET | 1:21 PM ET @TheHumanoidHub on X Show it a single human demonstration of a long-horizon task and the robot performs it right away. No fine-tuning, no retraining. Skild has released S1, a robot foundation model where you specify the task with a video demonstration instead of a language instruction. Why video, not language Language works for "hand me the mug." It falls apart for anything delicate or long-horizon. You don't learn to fold a fitted sheet from a sentence. So S1 takes a video demo into its context window and translates it to its own body and scene. What it does - Tasks up to 10 minutes, dozens of sequential steps -… | ||
| 1:19 PM ET | 1:19 PM ET Skild AI on X: "We found that to match the accuracy that S1 can achieve with just one example of prompting, current VLA models would need to be post-trained with 50-100 hours of data collection followed by fine-tuning!" / X Post Log in Sign up Post Skild AI on X: "We found that to match the accuracy that S1 can achieve with just one example of prompting, current VLA models would need to be post-trained with 50-100 hours of data collection followed by fine-tuning!" - Skild AI @SkildAI Aug 25 Introducing S1, our new foundation model that learns from one example. It can be taught 10-minute long tasks that it has never seen before, from one video prompt without any fine-tuning. Watch S1 operate in real-time via in-context learning: 00:00 View media 427 1K 7.1K 3.4M - Skild AI @SkildAI Aug 25 It can be taught… | ||
| 1:19 PM ET | 1:19 PM ET Skild AI on X: "S1 learns new tasks like a language model.
You prompt it with a video demonstration, and it outputs robot actions to complete the task in any environment and in any embodiment." / X Post Log in Sign up Post Skild AI on X: "S1 learns new tasks like a language model. You prompt it with a video demonstration, and it outputs robot actions to complete the task in any environment and in any embodiment." - Skild AI @SkildAI Aug 25 Introducing S1, our new foundation model that learns from one example. It can be taught 10-minute long tasks that it has never seen before, from one video prompt without any fine-tuning. Watch S1 operate in real-time via in-context learning: 00:00 View media 427 1K 7.1K 3.4M - Skild AI @SkildAI Aug 25 It can be taught extremely long-horizon tasks,… | ||
| 1:19 PM ET | 1:19 PM ET Skild AI on X: "The first time S1 flipped a pancake, we assumed pancake flipping must have been in its pre-training data.
We searched our whole pre-training data and found no examples of flipping.
S1 inferred the out-of-distribution task from one video prompt." / X Post Log in Sign up Post Skild AI on X: "The first time S1 flipped a pancake, we assumed pancake flipping must have been in its pre-training data. We searched our whole pre-training data and found no examples of flipping. S1 inferred the out-of-distribution task from one video prompt." - Skild AI @SkildAI Aug 25 Introducing S1, our new foundation model that learns from one example. It can be taught 10-minute long tasks that it has never seen before, from one video prompt without any fine-tuning. Watch S1 operate in real-time via in-context learning: 00:00 View media 427 1K 7.1K 3.4M - Skild… | ||
| 1:19 PM ET | 1:19 PM ET Skild AI on X: "Introducing S1, our new foundation model that learns from one example.
It can be taught 10-minute long tasks that it has never seen before, from one video prompt without any fine-tuning.
Watch S1 operate in real-time via in-context learning:" / X Post Log in Sign up Post Skild AI on X: "Introducing S1, our new foundation model that learns from one example. It can be taught 10-minute long tasks that it has never seen before, from one video prompt without any fine-tuning. Watch S1 operate in real-time via in-context learning:" - Skild AI @SkildAI Introducing S1, our new foundation model that learns from one example. It can be taught 10-minute long tasks that it has never seen before, from one video prompt without any fine-tuning. Watch S1 operate in real-time via in-context learning: 00:00 View media 1:19 PM · Aug 25, 20263.4MViews 427… | ||
| 1:19 PM ET | 1:19 PM ET Skild AI on X: "Introducing S1, our new foundation model that learns from one example.
It can be taught 10-minute long tasks that it has never seen before, from one video prompt without any fine-tuning.
Watch S1 operate in real-time via in-context learning:" / X Post Log in Sign up Post Skild AI on X: "Introducing S1, our new foundation model that learns from one example. It can be taught 10-minute long tasks that it has never seen before, from one video prompt without any fine-tuning. Watch S1 operate in real-time via in-context learning:" - Skild AI @SkildAI Introducing S1, our new foundation model that learns from one example. It can be taught 10-minute long tasks that it has never seen before, from one video prompt without any fine-tuning. Watch S1 operate in real-time via in-context learning: 00:00 View media 1:19 PM · Aug 25, 20263.4MViews 427… | ||
| 1:18 PM ET | 1:18 PM ET @humanoidsdaily on X Skild AI's S1 takes a video demonstration as its prompt. No language instruction, no fine-tuning. Show it a task it has never seen, and it gets 66% of the steps right. Describe that same task in words instead, and you get 9%. Prompting a robot with video isn't new. Generalist AI showed it earlier this month, but those runs last seconds. Skild claims S1 is the first to work on 10-minute tasks outside the training distribution. A new task used to mean a hundred hours of teleoperation and a training run. Skild set up a plant potting task at 8:54pm and had the robot running it autonomously 11… | ||
| 2:41 AM ET | XPXPeng | 2:41 AM ETXPXPeng @RobotFightMMA on X 🤖 Major robotics funding news! XPeng's humanoid robot unit Dogotix raises $900M at $6.3B valuation - setting record for China's embodied AI sector. Meanwhile Skild AI hits $14B valuation with $1.4B Series C for "universal brain" for robots. | |
| 8:00 PM ET | 8:00 PM ET Introducing S1: In-Context Learning for Robotics | Skild AI 0:00 / 0:00 1× Introducing S1: In-Context Learning for Robotics Unseen tasks10-minute horizonsOne video promptNo post-training 13-minute read Contents Introduction Why In-Context Learning for Robotics? S1: An In-Context Learner What does S1 learn from context? The Data Engine S1 In Action Seen tasks Long-horizon unseen tasks ICL scaling laws Emergent Properties Robustness and common-sense behavior Quantifying ICL robustness to distribution shifts ICL demonstration efficiency Closing Remarks References Citation Introduction The evolution of language modeling provides a blueprint for turning… | ||
| 3:57 PM ET | 3:57 PM ET Skild AI on X: "We built a robot brain that nothing can stop.
Shattered limbs? Jammed motors? If the bot can move, the Brain will move it— even if it’s an entirely new robot body.
Meet the omni-bodied Skild Brain:" / X Post Log in Sign up Post Skild AI on X: "We built a robot brain that nothing can stop. Shattered limbs? Jammed motors? If the bot can move, the Brain will move it— even if it’s an entirely new robot body. Meet the omni-bodied Skild Brain:" - Skild AI @SkildAI We built a robot brain that nothing can stop. Shattered limbs? Jammed motors? If the bot can move, the Brain will move it— even if it’s an entirely new robot body. Meet the omni-bodied Skild Brain: 00:00 View media 3:57 PM · Sep 24, 20252.4MViews 502 856 6.7K 2.2K - Skild AI @SkildAI Sep 24, 2025 The Skild Brain can control any machine… |
| Time | Entity | Sector | Event / capture |
|---|---|---|---|
| 10:30 AM ET | UBUber | 10:30 AM ETUBUber @TheRundownAI on X Top stories in robotics today: - Uber and Wayve bring robotaxis to London - Altman says OpenAI ‘will definitely’ build a humanoid - MIT’s AI shows what self-driving cars are thinking - Skild wants to teach robots with a single video https://t.co/rWKeG9fqxP | |
| 11:11 PM ET | — | 11:11 PM ET @Avin_lucia on X @Arifx0001 @BitRobotNetwork Great synergy leveraging high-end and affordable tools for teleop to scale AI efficiently | |
| 3:36 PM ET | 3:36 PM ET @HumanoidsHQ on X Stats time! Humanoid robot startups raised $8.6B this year. Almost none of them ship robots. The company shipping 44% of the world's humanoids is worth a fraction of the one still running pilots. Here's the humanoid money board, valuation vs what actually shipped: 1. Unitree. ~$53B market cap. $235M revenue in 2025, sells humanoids from $5,900. IPO popped roughly 460% in August. 2. Figure. $39B. A BMW pilot that has handled 90,000+ parts. 3. Skild AI. $14B+. Software only. No robot. 4. 1X Technologies. ~$10B reported. 10,000 preorders for its home robot in 5 days. 5. NEURA Robotics. ~$7B.… | ||
| 9:00 PM ET | 9:00 PM ET @XSeyvion on X Skild AI unveiled its S1 robot foundation model. They say a robot can learn a new task by watching a video of the task. That changes deployment. Instead of writing a fresh program for each job, an operator can demonstrate once and then ask the robot to repeat it. If the long tail of tasks becomes video based training, the fight shifts to safety checks that run before the robot touches the world. What task would you try first? | ||
| 8:36 PM ET | 8:36 PM ET The Robot Report: Skild AI unveils S1 robot foundation model | AI Understanding Back to News ProductAI Understanding briefing The Robot Report: Skild AI unveils S1 robot foundation model The Robot Report reports that Skild AI unveiled S1, a robot foundation model that the company says can learn complex tasks from a single human demonstration video and operate across multiple robot forms. By AI Understanding EditorialSeptember 1, 2026 at 12:36 AM UTCUpdatedSeptember 1, 2026 at 1:47 AM UTC6 min read Read the primary source The short version The Robot Report reports that Skild AI unveiled S1, a robot foundation model that the company says can learn complex tasks from a… | ||
| 8:00 PM ET | 8:00 PM ET Skild AI unveils S1 robot foundation model; ~$1.7B raised Brianna Wessling / The Robot Report (Firecrawl dated ~5 hours before Aug 31 evening): Skild AI unveiled S1, flagship robot foundation model. Company founded 2023 has raised nearly $1.7 billion. CEO Deepak Pathak: model uses in-context learning — add a video of a human doing a task in the prompt and the robot can follow; tasks shown are long-horizon, not 3-4 second demos; targeting tasks up to 10 minutes (repotting, coffee, pancakes). Omni-bodied (quadruped, humanoid, static arm); humanoid scale still pending. Pathak: coming weeks will show S1 helping in production; Fetch Robotics asset acquisition (from Zebra) is about deployment talent. Does not claim a ChatGPT moment yet. | ||
| 7:20 PM ET | 7:20 PM ET @ParadisLabs on X AI is still so early, but so bullish. We're witnessing a huge unlock of economic value with the adoption of AI models like Claude, and more recently, agents like Grok Bot. This then filters down into the most bullish of bull points for AI. Enterprise AI adoption increases productivity -> increases enterprise earnings -> increases token demand as a flywheel effect -> increases ROI for the AI labs -> increases demand for AI infra e.g. compute. I recently heard from an ex-colleague that a large consulting firm is increasing their AI spend by 100x at their London office for their back office… | ||
| 7:11 PM ET | SCSequoia Capital | 7:11 PM ETSCSequoia Capital @davidcao01 on X Fifteen years after "software is eating the world," Marc Andreessen's own firm just admitted atoms are eating software's margins. SUMMARY This is not an a16z story. a16z's $1.1B Machine Age Fund is simply the loudest confirmation yet of a rotation already underway across Silicon Valley's largest pools of capital — Sequoia Capital , Lightspeed , General Catalyst , and SoftBank have all made comparable moves in 2026. Global venture funding into physical AI hit $47.4B across 521 deals in H1 2026 — nearly 4x the prior half. For builders and investors in robotics, autonomous systems, and… | |
| 7:11 PM ET | 7:11 PM ET @Robot_AIsignals on X Show it once. That is the entire instruction. In a post published in August, Skild AI introduced S1, a robotics foundation model prompted with a video demonstration in place of a written command. The company says the same frozen weights then performed four tasks absent from its pre-training — potting a plant, cooking pancakes, brewing pour-over coffee, assembling a kit. Skild builds Skild Brain, which it calls the first unified robotics foundation model to generalise across both tasks and robot hardware. It raised $1.4bn in January at a valuation the company puts above $14 billion (company… | ||
| 10:56 AM ET | GEGeneralist | 10:56 AM ETGEGeneralist @chris_j_paxton on X In-Context Learning Results Hint at a “GPT Moment” for Robotics For general-purpose robots to be useful and economical, you need to be able to teach them new skills on the fly. And now we can see how this will work, with in-context long horizon video demonstrations shown by companies like Generalist, Skild, Rhoda, Rhoda, and RobbyAnt. The idea is simple: prompt with a demonstration, mixed video and proprioception information. Language isn't enough -- it doesn't specify the problem well enough. And it's starting to really work. more in blog post | |
| 10:02 AM ET | 10:02 AM ET @ThomasSmale on X $14B valuation. Pre-revenue. A handful of customers. That is Skild AI today. And it is not the outlier. Physical Intelligence: $11B Generalist: $2B to $3B in months, $600M raised Skild AI: $14B Three companies. Billions in capital. Almost no commercial traction between them. The thesis is simple. Someone builds the foundation model for robotics the way OpenAI built one for language. Find the winner early, own the platform forever. Here is the problem. LLMs were trained on trillions of words scraped from the open internet. That dataset already existed, and it was free. No equivalent exists for… | ||
| 6:09 AM ET | 6:09 AM ET @0xconglomerate on X Is it really possible for a robot to learn a new task from one human video, with zero fine-tuning? I’ve read a lot of hype around Skild’s S1, with some already calling it robotics’ “ChatGPT moment.” That sounded a bit absurd to me, so I looked into what’s actually going on 👇 ➦ What is @SkildAI actually claiming? I’ve written enough marketing material for AI, robotics, and tech companies that I’m usually skeptical when something sounds too good to be true. If you only saw the announcement post, you could easily think the robot just watches one human video and somehow learns the task from that… | ||
| 2:05 PM ET | 2:05 PM ET @rohanpaul_ai on X Robotics is more and more getting close to get its version of in-context learning. Skild just released S1, a robot foundation model that uses video demonstrations to define tasks instead of language instructions. Give S1 1 human video showing a long, multi-step task, and the robot executes it straight away. No retraining. No fine-tuning. If this scales, you pay the enormous data bill once during foundation-model training, then amortize it across thousands of new tasks through prompting. That could change the economics of robot learning completely. | ||
| 2:04 PM ET | 2:04 PM ET @DeryaTR_ on X This is super exciting advance in robotics AI! I believe S1 is the most impressive robot foundation model I had seen! S1, is a robot foundation model built to learn new manipulation tasks through in-context prompting In Skild’s internal benchmarks, S1 achieved a 66% step-success rate on unseen tasks versus 9% for a language-prompted model, while one video demonstration provided roughly the benefit of 380 post-training examples! | ||
| 1:41 PM ET | 1:41 PM ET Markets surge, track records fall, and in-context learning hits physical AI - Home - Posts - Markets surge, track records fall, and in-context learning hits physical AI Markets surge, track records fall, and in-context learning hits physical AI Unitree’s market whiplash, an 8.86s 100m sprint, and how in-context learning is ending heavy fine-tuning. Humanoids Daily Aug 25, 2026 This week brought a stark look at the tension defining modern humanoid robotics: the gap between capital market euphoria, athletic spectacle, and the unglamorous realities of industrial utility. Unitree's blockbuster Shanghai STAR Market listing initially saw shares rocket over 600% to an… | ||
| 1:34 PM ET | RHrhoda | 1:34 PM ETRHrhoda @chris_j_paxton on X This is the mark of a general purpose robot foundation model -- that it can be taught tasks from examples without training. We saw an early version of this from rhoda and a solid one last week from generalist, and now a really impressive, ten minute long one from skild. This to me does feel like the true gpt moment for robotics -- because if it truly generalizes, that means that you can really start deploying robots for anything, as developing robot skills becomes like prompting | |
| 1:21 PM ET | 1:21 PM ET @TheHumanoidHub on X Show it a single human demonstration of a long-horizon task and the robot performs it right away. No fine-tuning, no retraining. Skild has released S1, a robot foundation model where you specify the task with a video demonstration instead of a language instruction. Why video, not language Language works for "hand me the mug." It falls apart for anything delicate or long-horizon. You don't learn to fold a fitted sheet from a sentence. So S1 takes a video demo into its context window and translates it to its own body and scene. What it does - Tasks up to 10 minutes, dozens of sequential steps -… | ||
| 1:19 PM ET | 1:19 PM ET Skild AI on X: "We found that to match the accuracy that S1 can achieve with just one example of prompting, current VLA models would need to be post-trained with 50-100 hours of data collection followed by fine-tuning!" / X Post Log in Sign up Post Skild AI on X: "We found that to match the accuracy that S1 can achieve with just one example of prompting, current VLA models would need to be post-trained with 50-100 hours of data collection followed by fine-tuning!" - Skild AI @SkildAI Aug 25 Introducing S1, our new foundation model that learns from one example. It can be taught 10-minute long tasks that it has never seen before, from one video prompt without any fine-tuning. Watch S1 operate in real-time via in-context learning: 00:00 View media 427 1K 7.1K 3.4M - Skild AI @SkildAI Aug 25 It can be taught… | ||
| 1:19 PM ET | 1:19 PM ET Skild AI on X: "S1 learns new tasks like a language model.
You prompt it with a video demonstration, and it outputs robot actions to complete the task in any environment and in any embodiment." / X Post Log in Sign up Post Skild AI on X: "S1 learns new tasks like a language model. You prompt it with a video demonstration, and it outputs robot actions to complete the task in any environment and in any embodiment." - Skild AI @SkildAI Aug 25 Introducing S1, our new foundation model that learns from one example. It can be taught 10-minute long tasks that it has never seen before, from one video prompt without any fine-tuning. Watch S1 operate in real-time via in-context learning: 00:00 View media 427 1K 7.1K 3.4M - Skild AI @SkildAI Aug 25 It can be taught extremely long-horizon tasks,… | ||
| 1:19 PM ET | 1:19 PM ET Skild AI on X: "The first time S1 flipped a pancake, we assumed pancake flipping must have been in its pre-training data.
We searched our whole pre-training data and found no examples of flipping.
S1 inferred the out-of-distribution task from one video prompt." / X Post Log in Sign up Post Skild AI on X: "The first time S1 flipped a pancake, we assumed pancake flipping must have been in its pre-training data. We searched our whole pre-training data and found no examples of flipping. S1 inferred the out-of-distribution task from one video prompt." - Skild AI @SkildAI Aug 25 Introducing S1, our new foundation model that learns from one example. It can be taught 10-minute long tasks that it has never seen before, from one video prompt without any fine-tuning. Watch S1 operate in real-time via in-context learning: 00:00 View media 427 1K 7.1K 3.4M - Skild… | ||
| 1:19 PM ET | 1:19 PM ET Skild AI on X: "Introducing S1, our new foundation model that learns from one example.
It can be taught 10-minute long tasks that it has never seen before, from one video prompt without any fine-tuning.
Watch S1 operate in real-time via in-context learning:" / X Post Log in Sign up Post Skild AI on X: "Introducing S1, our new foundation model that learns from one example. It can be taught 10-minute long tasks that it has never seen before, from one video prompt without any fine-tuning. Watch S1 operate in real-time via in-context learning:" - Skild AI @SkildAI Introducing S1, our new foundation model that learns from one example. It can be taught 10-minute long tasks that it has never seen before, from one video prompt without any fine-tuning. Watch S1 operate in real-time via in-context learning: 00:00 View media 1:19 PM · Aug 25, 20263.4MViews 427… | ||
| 1:19 PM ET | 1:19 PM ET Skild AI on X: "Introducing S1, our new foundation model that learns from one example.
It can be taught 10-minute long tasks that it has never seen before, from one video prompt without any fine-tuning.
Watch S1 operate in real-time via in-context learning:" / X Post Log in Sign up Post Skild AI on X: "Introducing S1, our new foundation model that learns from one example. It can be taught 10-minute long tasks that it has never seen before, from one video prompt without any fine-tuning. Watch S1 operate in real-time via in-context learning:" - Skild AI @SkildAI Introducing S1, our new foundation model that learns from one example. It can be taught 10-minute long tasks that it has never seen before, from one video prompt without any fine-tuning. Watch S1 operate in real-time via in-context learning: 00:00 View media 1:19 PM · Aug 25, 20263.4MViews 427… | ||
| 1:18 PM ET | 1:18 PM ET @humanoidsdaily on X Skild AI's S1 takes a video demonstration as its prompt. No language instruction, no fine-tuning. Show it a task it has never seen, and it gets 66% of the steps right. Describe that same task in words instead, and you get 9%. Prompting a robot with video isn't new. Generalist AI showed it earlier this month, but those runs last seconds. Skild claims S1 is the first to work on 10-minute tasks outside the training distribution. A new task used to mean a hundred hours of teleoperation and a training run. Skild set up a plant potting task at 8:54pm and had the robot running it autonomously 11… | ||
| 2:41 AM ET | XPXPeng | 2:41 AM ETXPXPeng @RobotFightMMA on X 🤖 Major robotics funding news! XPeng's humanoid robot unit Dogotix raises $900M at $6.3B valuation - setting record for China's embodied AI sector. Meanwhile Skild AI hits $14B valuation with $1.4B Series C for "universal brain" for robots. | |
| 8:00 PM ET | 8:00 PM ET Introducing S1: In-Context Learning for Robotics | Skild AI 0:00 / 0:00 1× Introducing S1: In-Context Learning for Robotics Unseen tasks10-minute horizonsOne video promptNo post-training 13-minute read Contents Introduction Why In-Context Learning for Robotics? S1: An In-Context Learner What does S1 learn from context? The Data Engine S1 In Action Seen tasks Long-horizon unseen tasks ICL scaling laws Emergent Properties Robustness and common-sense behavior Quantifying ICL robustness to distribution shifts ICL demonstration efficiency Closing Remarks References Citation Introduction The evolution of language modeling provides a blueprint for turning… | ||
| 3:57 PM ET | 3:57 PM ET Skild AI on X: "We built a robot brain that nothing can stop.
Shattered limbs? Jammed motors? If the bot can move, the Brain will move it— even if it’s an entirely new robot body.
Meet the omni-bodied Skild Brain:" / X Post Log in Sign up Post Skild AI on X: "We built a robot brain that nothing can stop. Shattered limbs? Jammed motors? If the bot can move, the Brain will move it— even if it’s an entirely new robot body. Meet the omni-bodied Skild Brain:" - Skild AI @SkildAI We built a robot brain that nothing can stop. Shattered limbs? Jammed motors? If the bot can move, the Brain will move it— even if it’s an entirely new robot body. Meet the omni-bodied Skild Brain: 00:00 View media 3:57 PM · Sep 24, 20252.4MViews 502 856 6.7K 2.2K - Skild AI @SkildAI Sep 24, 2025 The Skild Brain can control any machine… |