Episode

ThursdAI - Jan 8 - Vera Rubin's 5x Jump, Ralph Wiggum Goes Viral, GPT Health Launches & XAI Raises $20B Mid-Controversy

Podcast
ThursdAI - The top AI news from the past week
Published
Jan 8, 2026
Duration seconds
6417
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not_requested
Canonical source
https://sub.thursdai.news/p/thursdai-jan-8-nvidias-vera-rubin
Audio
https://prfx.byspotify.com/e/api.substack.com/feed/podcast/183956296/b1af7c2151ba30e29f969e75038269dc.mp3
JSON
/v1/public/podcasts/thursdai-the-top-ai-news-from-the-past-week-6519604/episodes/thursdai-jan-8-vera-rubin-s-5x-jump-ralph-wiggum-goes-viral-gpt-health-launches-xai-raises-20b-mid-controversy
Markdown
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Summary

Hey folks, Alex here from Weights & Biases, with your weekly AI update (and a first live show of this year!) For the first time, we had a co-host of the show also be a guest on the show, Ryan Carson (from Amp) went supernova viral this week with an X article (1.5M views) about Ralph Wiggum (yeah, from Simpsons) and he broke down that agentic coding technique at the end of the show. LDJ and Nisten helped cover NVIDIA’s incredible announcements during CES with their Vera Rubin upcoming platform (4-5X improvements) and we all got excited about AI medicine with ChatGPT going into Health officially! Plus, a bunch of Open Source news, let’s get into this: ThursdAI - Recaps of the most high signal AI weekly spaces is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Open Source: The “Small” Models Are Winning We often talk about the massive frontier models, but this week, Open Source came largely from unexpected places and focused on efficiency, agents, and specific domains. Solar Open 100B: A Data Masterclass Upstage released Solar Open 100B, and it’s a beast. It’s a 102B parameter Mixture-of-Experts (MoE) model, but thanks to MoE magic, it only uses about 12B active parameters during inference. This means it punches incredibly high but runs fast. What I really appreciated here wasn’t just the weights, but the transparency. They released a technical report detailing their “Data Factory” approach. They trained on nearly 20 trillion tokens, with a huge chunk being synthetic. They also used a dynamic curriculum that adjusted the difficulty and the ratio of synthetic data as training progressed. This transparency is what pushes the whole open source community forward. Technically, it hits 88.2 on MMLU and compe…