Let's start with announcing a new chapter for the AI NYC: AI Builders Milan. Roberto Stagihttps://www.linkedin.com/posts/rstagiaibuildersmilan-ainyc-ai-activity-7391882005266911233-CwGy?utmsource=soci

AI Dinner 15.0 New York Wednesday, November 12 AI NYChttps://lu.ma/ainy is hosting another AI Dinner 🍲🍕🍺 , we'll discuss news and updates using this blog post to run the Socratic dialogues. Event:

AI use is widespread, but mostly are at early stage experimenting with AI and AI agents. High performers redesign workflows. Only 39% report financial impact EBIT. Link: mckinsey.com/capabilities/quan

Extropic just released a new type of hardware called Thermodynamic Sampling Units TSUs. Their approach, called thermodynamic computing, flips traditional computing on its head. Instead of fighting aga

In the past few months we've seen a lot of new AI browser coming up. They're all chromium copy with extra AI features. Google has yet to upgrade Chrome with AI capabilities. Let's explore the new brow

| The best ChatGPT that $100 can buy. ⭐️ Andrej Karpathy, our AI legend, just dropped nanochat, a complete, end-to-end implementation of an LLM-based chat assistant like ChatGPT — but compact, clean,

DeepSeek AI has unveiled DeepSeek-OCR, a groundbreaking approach to compressing long contexts via optical 2D mapping. This innovative system demonstrates that vision-based compression can achieve rema

· Claim: Decoder‑only transformer LMs are almost‑surely injective: different prompts map to unique last‑token hidden states; this holds at initialization and is preserved under gradient descent. · Met

Instead of simulating clicks and scrolls, researchers let LLMs reason which playlist, feed, or product lineup you’d actually prefer. And it worked. Across Amazon, Spotify, MovieLens, and MIND datasets

This paper got top score at NeurIPS 2025. It aims at answering: does RL make LLM better reasoners? The authors study Reinforcement Learning with Verifiable Rewards RLVR and find that while it improves

Tencent + Tsinghua just dropped a paper called Continuous Autoregressive Language Models CALM and it basically kills the “next-token” paradigm every LLM is built on. Instead of predicting one token at

Perplexity in NLP measures how well a language model predicts text; lower means better.

https://www.youtube.com/watch?v=iO03t21xhdk&feature=youtu.be&themeRefresh=1 https://www.youtube.com/watch?v=29gkDpR2orc&t=890s

MLST — AI benchmarks are broken! \Prof Melanie Mitchell\ I really love this part of the MLST interview in which Prof Mitchell says the key LLM question is: what kind of “understanding,” if any, is rea

In search of Nothing | David Deutsch, Lee Smolin, Amanda Gefter https://www.youtube.com/watch?v=rMSEqJ\4EBk

MLST — Google Researcher Shows Life "Emerges from Code" Blaise Agüera y Arcas explores some mind-bending ideas about what intelligence and life really are—and why they might be more similar than we th