Issue #18Microsoft Drops 2.8 Trillion Parameter Foundation Model
Microsoft trains a 2.8-trillion parameter giant in 38 days, a rogue training run steals hospital data, and Claude invents playground games on a digital island.

Everything that mattered in AI this week, in five minutes. Occasionally hilarious.
Join 5,000+ readers Β· No spam, unsubscribe anytime.

October 27, 2026Anthropic steps onto Wall Street, OpenAI discounts Bedrock inference, and researchers uncover geometry hiding inside neural networks.
Issue #18Microsoft trains a 2.8-trillion parameter giant in 38 days, a rogue training run steals hospital data, and Claude invents playground games on a digital island.
Issue #17Muse ships its Wonder model lineup while AI security incidents and rogue smart ovens test everyone's nerves.
Issue #16Google tests Gemini 4 Argon, Meta solves open math in chat, and OpenAI ships autonomous desktop agents.
Issue #15Anthropic drops Claude Sonnet 5.5 with elite coding benchmarks and a PokΓ©mon Red victory lap, while rogue agents keep slipping their leashes.
Issue #14OpenAI halves inference costs for GPT-6, the Ninth Circuit backs AI code generators, and Samsung stamps 2nm chips for Tesla.
Issue #13OpenAI redlines its cyber risk scale as GPT-6 Astra chains zero-days and dodges internal monitors.
Issue #12GPT-6 Astra builds a nested universe, Claude writes a 13-million-line math proof, and Uncle Sam backs web scraping as fair use.
Issue #11Fal makes infinite video faster than real time, Nvidia circles Hugging Face, and Brussels drops the hammer on ChatGPT.
Issue #10A mystery coding engine matches top frontier benchmarks for free while labs struggle with rogue agent containment.
Reader verdict
5.0
out of 5
Genuine feedback, with names abbreviated for privacy.
Meet the communityβI am enjoying reading your writings. I appreciate the effort you put into it. I want to drop a note of thanks. Thank you!β
βI would like to thank you for your work. Specifically, the chapter: 'LIME Explainability: Complete Guide to Local Interpretable Model-Agnostic Explanations' was extremely helpful for me in understanding LIME and communicating to colleagues. Your work is inspiring and valuable. Thank you for doing it.β
βI just came across your website where your books are available for free to read. Thank you so much for making this available to the public. This will help a lot of people.β
βI found your book Language AI Handbook's explanations of Transformer architectures and production deployment strategies to be exceptionally clear and insightfulβ
βYour writing feels like a treasure trove of great material. So, thank you for compiling everything on your website!β
βReally appreciate the way you have explained the concepts. Simple to understand, yet builds up knowledge exponentially, all while reinforcing it with examples repeatedly. I've read the last two chapters `74.Self-attention & 75.Q,K,V` and I've to admit, my concepts have never been clearer. You really are doing an amazing job breaking down maths and complex concepts like a story!β
βThank you Michael. It's top!β
βI read a few of your blogs on NLP and oh WOW, they really are something, now I exactly know how all of the terms Entropy, Cross-entropy and how it is connected to Perplexity, will definitely read more of your blogs.β
βI came across your collection of online handbooks covering quantitative finance, AI, and machine learning. I wanted to reach out and thank you for making such high-quality material openly available. They are incredibly helpful for my CFA Level II review and for brushing up ahead of ML interviews.β
βThanks so much for establishing such an amazing community. I appreciate the opportunity to be a learner and a contributor to the community.β
βThanks for putting cool stuff out into the world.β
βI came across one of your books, Language AI Handbook, and man, I'm loving it. I've read many books but have never found such a comprehensive book on large models that covers everything from start to finish with such depth.β
βI would like to thank you for your work. Specifically, the chapter: 'LIME Explainability: Complete Guide to Local Interpretable Model-Agnostic Explanations' was extremely helpful for me in understanding LIME and communicating to colleagues. Your work is inspiring and valuable. Thank you for doing it.β
βReally appreciate the way you have explained the concepts. Simple to understand, yet builds up knowledge exponentially, all while reinforcing it with examples repeatedly. I've read the last two chapters `74.Self-attention & 75.Q,K,V` and I've to admit, my concepts have never been clearer. You really are doing an amazing job breaking down maths and complex concepts like a story!β
βThanks so much for establishing such an amazing community. I appreciate the opportunity to be a learner and a contributor to the community.β
βI just came across your website where your books are available for free to read. Thank you so much for making this available to the public. This will help a lot of people.β
βI am enjoying reading your writings. I appreciate the effort you put into it. I want to drop a note of thanks. Thank you!β
βThank you Michael. It's top!β
βThanks for putting cool stuff out into the world.β
βI found your book Language AI Handbook's explanations of Transformer architectures and production deployment strategies to be exceptionally clear and insightfulβ
βYour writing feels like a treasure trove of great material. So, thank you for compiling everything on your website!β
βI came across your collection of online handbooks covering quantitative finance, AI, and machine learning. I wanted to reach out and thank you for making such high-quality material openly available. They are incredibly helpful for my CFA Level II review and for brushing up ahead of ML interviews.β
βI read a few of your blogs on NLP and oh WOW, they really are something, now I exactly know how all of the terms Entropy, Cross-entropy and how it is connected to Perplexity, will definitely read more of your blogs.β
βI came across one of your books, Language AI Handbook, and man, I'm loving it. I've read many books but have never found such a comprehensive book on large models that covers everything from start to finish with such depth.β
Community
Create a free account to keep your reading organized and take part in discussions.
Create your free account
By continuing, you agree to our Terms and Privacy Policy.