Inside the Model Factory — Eiso Kant, Poolside AI

Inside the Model Factory — Eiso Kant, Poolside AI 图片 1

In recent months, the open vs closed, and US vs China discussions on model ownership and sovereign/local AI have heated up to a fever pitch. So it is very very good news that Poolside AI are finally emerging with new models, like Laguna S 2.1, that are beating Thinking Machines’ recent release nearly 10 times their size.Poolside’s recent tech report got a lot of praise due to their level of detail, and Vibhu first covered Laguna’s recent technical report on our paper club:

@latentspacepod breakdown of our Laguna M.1/XS.2 Technical Report! The Latent Space paper club just did a deep dive, and their takeaways perfectly capture what we set out to build with our Model Factory. A few quotes from the video 🧵👇 (1/6)\n youtu.be/QLfZamyMls0 ","username":"eisokant","name":"Eiso Kant","profile_image_url":"https://pbs.substack.com/profile_images/1842230143965675520/j6mVG2Py_normal.jpg","date":"2026-05-28T20:34:07.000Z","photos":[],"quoted_tweet":{},"reply_count":1,"retweet_count":8,"like_count":47,"impression_count":11267,"expanded_url":null,"video_url":null,"video_preview_media_key":null,"belowTheFold":false}" data-component-name="Twitter2ToDOM">

From spending $12 million building language models for code before the world cared to creating a Model Factory that can take a model from pre-training to release in eight weeks, Eiso Kant has spent more than a decade betting that code is the path to AGI. In this episode, the Poolside co-founder joins swyx and Vibhu to explain why ChatGPT felt like vindication, why Poolside embraced open weights and open research, and why he would rather live in a world with 100 foundation model companies than five even if Poolside were one of the five.

We go deep on Poolside’s Model Factory: the engineering systems behind 10,000–20,000 experiments per month, streaming data directly into training, reproducible experimentation, low-precision compute, and agents that increasingly write code, launch jobs, evaluate results, and modify the pipelines u…

添加评论
点赞收藏
点踩分享查看原文
评论
?
参与讨论