No Taxation Without Annihilation The Anti-Antimatter-Tax Party fights for our freedom. AATP LFG! https://t.co/fJMpnMmb3x

Happy Father’s Day to all the incredible dads out there ❤️ https://t.co/ZZURvmfEWj

Happy Father’s Day to my wonderful sons, my fantastic father and all fathers. 🥰🥰 https://t.co/pkpNiYStwv

As India builds frontier AI rooted in its own languages and knowledge, IIT Bombay and BharatGen are proud to support and participate in Project Tapestry: an open, global consortium for nations to advance frontier AI together. BharatGen, supported by the IndiaAI Mission and the Department of Science and Technology, joins as a founding contributor with multilingual AI infrastructure built natively for India's diverse languages. A Letter of Intent was signed on June 18th by IIT Bombay Director Prof. Shireesh Kedare, in the presence of both Deputy Directors Prof. Milind Atrey and Prof. Ravindra Gudi, and Prof. Ganesh Ramakrishnan, Founding Director at BharatGen. Project Tapestry was represented by Dr. Christopher Nguyễn, Chief Architect of Project Tapestry and AI Alliance Board Member. What India has built for its own people, it now brings to the world. @EduMinOfIndia @BharatGen_Com @ganramkr @OfficialINDIAai @IndiaDST @ylecun @kb_bha @pentagoniac @kb_bhatta

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Same page, two captures. https://t.co/BQWx8PIy2M as PNG: 431 KB https://t.co/BQWx8PIy2M as WebP: 74 KB One flag: --format webp. 83% smaller. If your agent stores thousands of grabs, this is the cheapest optimization you will ship today. https://t.co/UoBINkAZ9i

Same page, two captures. https://t.co/BQWx8PIy2M as PNG: 431 KB https://t.co/BQWx8PIy2M as WebP: 74 KB One flag: --format webp. 83% smaller. If your agent stores thousands of grabs, this is the cheapest optimization you will ship today. https://t.co/UoBINkAZ9i

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What literatures have developed since the paper that are in dialog or tension with its themes or findings? (This is something that is very hard for academics, ensconced in a field, to do on their own) https://t.co/TX3gdVqnbP

🚨 New DeepMind’s Category Error on Transformer “State” (Mozer et al. 2026) Paper correctly flags transformers’ sequential consistency limits and offers a useful recurrent taxonomy. Core claim: “depth exhaustion” from pushing state deeper, misreads the transformer architecture. The residual stream isn’t a persistent state structure or evolving “mental model”. It’s an intermediate calculation within the single pass forward based on token isomorphism and training corpus regularities devoid of any system-wide coherent meaning but context dependent and fragile per inference: h0 = prefill(prompt) - - - - - - - - - h1 = h0 + layer0 h2 = h1 + layer1 . . . / layer_i = Attn(i) + FFN(i) / . . . - - - - - - - - - A running sum across layers (not time). The full stack computes hL once, then last_FFN + unembed → logits → one token. - - - - - - - - - t = unembed(last_FFN) - - - - - - - - - That token alone seeds the next auto-regressive step. - - - - - - - - - input = input + t - - - - - - - - - No internal carry-over. No “beliefs.” Just partial aggregates overwritten in the next pass. “Depth exhaustion” is an artifact: treating mid-layer partial sums as final outputs. Reading tea leaves without tasting. Intermediates at layer 6 aren’t disambiguated interpretations, they’re provisional values further refined by remaining layers. Many paths can converge to the same final token. Only the emitted token is causally decisive. Chain-of-thought isn’t a hack. It’s the only state mechanism: tokens are the architecture’s persistent memory. Proposing hidden recurrent dynamics just buries state in unauditable vectors while ignoring the real bottleneck, training data for trajectory coherence. The math hasn’t changed since Vaswani 2017. The field has: rewarding narratives of “interpretable belief states” over the simpler truth of ephemeral partial sums in a fixed approximator. Incentives > clarity Non-anthropomorphic Terminology refresh for precision: • “State tracking” → trajectory coherence across autoregressive steps not single pass layers • “Belief at layer N” → intermediate residual stream calculation sum reachable by many paths •“Depth exhaustion” → attention softmax competition under pretraining density •“Implicit reasoning” → unobservable vector transforms Mechanistic Interpretation unfalsified anthropomorphic assumptions are leading the whole field astray.

Happy Father’s Day to all the dads and grandfathers out there helping inspire and prepare the explorers, builders, and dreamers of tomorrow. The future Starfleet is going to need a lot of recruits! https://t.co/jyM4SgkofC

Great opportunity to learn :) https://t.co/voMmZLqNRc @sh_reya @HamelHusain

Great opportunity to learn :) https://t.co/voMmZLqNRc @sh_reya @HamelHusain

🚨 LMAO!! JD VANCE: "Joy Behar is way tougher than the Iranians — and she and I are best friends now!" "I've seen some progressive criticisms of me personally saying what experience does the VP have in hostile high stakes negotiations?" "I would point those progressive critics to the fact that just two days ago I spent over an HOUR on THE VIEW." "So I actually have a great experience in very hostile negotiations." 😭😭

Will the GitHub Copilot app run Doom? 👀 Yes, yes it will. https://t.co/VOJhebXVKD

@SabriMjd Updated https://t.co/CqKqY9U6ay

@clairevo Impeccable timing! https://t.co/1kmxX6xv11

We just passed 1500 Contributors to Hermes Agent's repo! Thank you to all the contributors and developers! https://t.co/YhSyseIGJl

Come join the developer crew by resolving issues, submitting PRs or creating feature requests on the GitHub repo here: https://t.co/EiLSJJCkGb

To all the newcomers excited to try Opus 4.8-level models at home: welcome to OpenWeightLand! Things work a little differently here than in ClosedSourcistan. Might seem strange at first but you'll quickly get used to it: - there are many providers for the same model and they compete on price and features. - as a result intelligence is abundant and typically much cheaper - you can run the model on-prem, in your region, locally, or with the provider of your choice - you can fine-tune it, modify it, and build businesses on top of it without asking anyone for permission Turns out open weights create markets, not kingdoms. A good central train station to start exploring is the Hugging Face page for GLM-5.2 under "Use this model": -> https://t.co/qOt7qbnBZa And if you just want to chat with it, it's free on HuggingChat: -> https://t.co/54mcbEoEUm

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There's a new rust client for Storage Buckets 🦀 OpenDAL is awesome https://t.co/rYp5VAyfNS

There's a new rust client for Storage Buckets 🦀 OpenDAL is awesome https://t.co/rYp5VAyfNS

Holy moly almost 1000 followers on Huggingface https://t.co/gjUI5LVXWJ

GLM 5.2 continues to impress me. Here's its result on Vending Bench, which measures an AI's performance on running a business over a long time. GLM 5.2 came in second, while costing less than HALF of Opus. https://t.co/IXOgXyQMJM

Most people see a billionaire and assume the hard part is over. What interests me is the willingness to become a beginner again. That mindset may be the common thread behind many of the world's most successful entrepreneurs. https://t.co/wd3m2BrtvK

@0xBassey @DarioAmodei https://t.co/7tkTpYaa9r

🚨 Claude Mythos: Is Claude-ception a Safety Risk? Deeper into the instructions we find the most intriguing feature: “Claudeception”. AI inside AI. No safeguards. Only a payload limit. No user in the loop. Agentic OS > Chat Nested loops running unattended at scale!? Yep 🕳️🐇 https://t.co/C06065ZfAE

This is one of the coolest open-source AI agent projects I've seen in a while: 'Understand Anything' It's a plugin for Claude Code, Codex, OpenCode etc. that analyzes your codebase and turns it into a knowledge base that you can interact with. It explains the codebase to you, rather than showing you the structure. It seems like it's designed for code but I opened my Obsidian vault of podcast highlights in Claude Code, then ran /understand. The result is a knowledge graph that I can search of highlights from 888 podcast episodes and 144K lines of markdown text.

Dodged a kid crossing a red light on a bike hit a utility pole dead straight in my @cybertruck The inertia of the impact was completely absorbed, felt not like a typical impact at all, industry leading crumple zones ftw. My family and the red light runner are all safe, even the pole was not damaged @elonmusk @Tesla

We have the first full-sized humanoid robot on campus in the Greater Bay Area! This guy is so tall and heavy... #EmbodiedAI #Humanoid #AI #HKUST #HKUSTGZ https://t.co/FXplCbb2NK

COMPANY BEHIND TIKTOK JUST OPEN SOURCED AN AI AGENT THAT DOES YOUR WHOLE JOB FOR YOU China doesn't miss 😳 everyone's been crowning hermes the #1 agent then bytedance dropped deerflow 72,000+ github stars. 9,700+ forks. FREE. MIT it doesn't just run tools like hermes. it does the entire task you give it one job and it plans the steps, spins up a team of sub-agents, writes the code, tests it, fixes its own errors, and hands you finished work in its own sandbox research, full websites, dashboards, slide decks, reports. done, not drafts full beginner setup: easiest way (if you use claude code, cursor or codex): paste this to your agent and it installs everything for you: "clone deerflow and set it up for local dev using https://t.co/jPhzWtcHwr" manual way (about 5 min): 1. install the basics: git, docker, node 22+, uv, pnpm (deerflow's "make check" flags anything missing) 2. clone the repo: git clone https://t.co/VdMJHx0YOu cd deer-flow 3. run the setup wizard: make setup it asks which model you want and saves your key. point it at openrouter, groq or nvidia nim to run it free 4. check it works: make doctor 5. start it with docker: make docker-init make docker-start 6. open it in your browser and give it your first task now the part that'll start a fight: hermes is the most used agent on openrouter (224B tokens a day) and i've been all in on it but hermes runs your tools. deerflow runs your whole project end to end i'm actually tempted to switch and i did not expect that so which one wins right now? - hermes: american, lean, lives on your laptop - deerflow: chinese, bytedance muscle, replaces a whole team bookmark this and tell me which agent you're running

The next movie studio might be just one storyboard away. https://t.co/Xk08sOTzkq