34 Photos and videos
Language as a training signal has a structural flaw that scale can't fix — the data isn't the world, it's humanity's filtered description of the world. Most LLM criticism stays behavioral: hallucinations, reasoning failures. @sainingxie 's critique cuts deeper.
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"去中心化联盟对抗LLM霸权"这个叙事觉得有点过于整洁。现实中数据拥有者的动机是复杂的，有人想要回报，有人怕竞争对手拿到自己的数据，有人根本不知道自己的数据有什么价值。这些摩擦在访谈里没涉及但却是实操时最现实的问题。
Mar 16
和@sainingxie 一起挑战7小时播客！他刚和Yann LeCun踏上“世界模型”的创业旅程（AMI Labs）。这是他第一次Podcast、第一次访谈。
2026年2月雪后的一天，我们在纽约布鲁克林，从下午2点，开启了一场始料未及的马拉松式访谈，直到凌晨时分散去。
这篇访谈的中文标题叫做《逃出硅谷》，但他又不厌其烦地枚举了影响他学术生涯的每一个人，并反反复复口头描摹这些人的人物特征（侯晓迪、何恺明、杨立昆、李飞飞…）正是这些，让这篇“逃出硅谷”的对话充斥着人性的温度。
By the way, 下面是访谈的YouTube版本，我们提供了中英字幕。
And yes, 我们是在用播客给这个世界建模😎
A 7-hour podcast with Saining Xie. He has just begun a new journey on world models with Yann LeCun at AMI Labs.
This was his first podcast appearance and his first long-form interview.
A day after the snowfall in February 2026, in Brooklyn, New York, we started recording at 2 p.m. What followed became an unexpected marathon conversation that lasted until the early hours of the morning.
The Chinese title of the interview is “Escaping Silicon Valley.” Yet throughout the conversation, he patiently listed the people who shaped his academic life, repeatedly sketching their personalities in vivid detail: Hou Xiaodi, Kaiming He, Yann LeCun, Fei-Fei Li, and others. These portraits are what give this “escape from Silicon Valley” conversation its human warmth.
By the way, the YouTube version of the interview is below, with Chinese and English subtitles.
And yes, we are using podcasts to model the world 😎
A 7-hour marathon interview with Saining Xie: World Models, AMI Labs, Ya... youtu.be/rIwgZWzUKm8?si=edxa… 来自 @YouTube
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Thanks for the invitation and looking fwd to the discussion~
Building the future of decentralized data.
Kevin Wang (@qiw), Co-founder & CPO of @codatta_io, brings experience from Alibaba, Ant Group, and Oracle to shape the next generation of AI x Web3 infrastructure.
Meet him at #TBW2025.
📍 Songshan Cultural and Creative Park | Sep 4–6th, 2025
🎟️ bit.ly/tbw2025
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Honor to make our contributions to open source AI Training data sets, more to come~ stay turned
15 Aug 2025
See a million plates from every corner of the world, named, tagged, and verified by thousands, and trace each one back to its source... That's MM-Food-100K. Built with 87,000 contributors over six weeks, every entry is linked to a wallet and refined through a hybrid workflow of AI drafts human experts.
The full corpus holds 1.2M quality-accepted samples; 100K (a curated 10%) is on @huggingface for non-commercial use, with the remaining 90% reserved for commercial licensing and royalties to contributors.
Why does it matter? Robotics can recognize your plate, smart kitchens know what you cook, supply chains track what moves, and health apps turn images into nutrition insights.
Powered by the @Binance community, you turned individual submissions into a living map of global food knowledge. So if you're in health & nutrition — think @MyFitnessPal, @noom, @Lifesum — let's talk! Your apps deserve food data with traceable provenance.
Food data with provenance: open for experimentation, and protected where it drives value.
Built with the crowd, and for the world.
📄 More on the dataset: arxiv.org/abs/2508.10429
📂 Access it here: huggingface.co/datasets/Coda…
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As part of the @GoKiteAI ecosystem incubation program, @codatta_io received funding from the @AvalancheFDN ’s InfraBUIDL (AI) initiative, a $15 million grant program in which Kite AI serves as a joint selection committee member.
The InfraBUIDL (AI) program is designed to accelerate innovation at the intersection of AI and decentralized infrastructure. This funding not only provided critical resources but also connected Codatta to Kite AI’s broader ecosystem, accelerating both technical deployment and ecosystem collaboration.
With this support, Codatta achieved key milestones such as launching the first autonomous medical data annotation workflow, combining blockchain’s auditability with AI’s problem-solving capabilities and highlighting the strong demand for high-value AI assets.🌐
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Lower development costs, higher capital efficiency, and faster profitability. Seed-Strapping: Secure $100K-$1M in seed funding from investors focused on early revenue generation and strong returns. Ideal for startups leveraging AI for growth. #SeedStrapping
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The data annotation market is undergoing a huge transformation. It used to rely on the crowdsourcing model with low - to mid - skilled workers. Now, it's shifting to "filtering" high - level Q&A, seeking the world's top talents to push the boundaries of model capabilities. #evals
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Previously, most evaluation tasks were "zero - shot" tests. But what we truly need to assess is "work valuable in results." In the future, Agents will take on various roles currently performed by employees, working with human staff, who will also help build these evaluation tasks
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A vast eval ecosystem for assessment tasks will emerge to customize Agents for every enterprise. #DataAnnotation #AI #FutureOfWork
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