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Drug discovery. Early autism diagnosis. Fraud detection. Emotional companionship. These aren't demos. They're what 10,770 builders shipped at the @AIatAMD Developer Hackathon - and it's a wrap. Meet the winners β https://t.co/xfzH3ZzkiR
BOOM! βSpaceX Agrees to Buy AI Coding Agent Cursor for $60 Billionβ A massive directional change that will ultimately make Claude/Mythos irrelevant. https://t.co/MBIZ28PohB
OpenAI's strategic finance team is showcasing how we are building the finance team of the future with #12daysofChatCodexStratfin. Day 1: @rohitkohli uses Codex to dynamically balance our Marketing spend to optimize payback. Before Chat+Codex βΉοΈ Every week, our team sifted through enormous volumes of marketing data spread across geographies, channels, campaigns, and keywords to understand what was working. The challenge wasn't a lack of data but having enough time to turn that data into action in a timely way. Agentic dawn! π With Codex, we transformed raw marketing data into an interactive ROI dashboard that helped us visualize where each channel began to hit diminishing returns. And then the big unlock: beyond reporting performance, we asked Codex to act like an investment advisor for our marketing portfolio: identify the top channels where an additional dollar would generate the highest return, flag the channels where spend had become less productive, and recommend exactly how to rebalance our budget. Marketing spend allocation has evolved from a periodic reporting exercise into a dynamic capital allocation process, and we now adjust our investments weekly to continuously optimize payback across the portfolio. Try Codex at https://t.co/3poRqWvLWR @thsottiaux @nickaturley @stacie_w_f
Got a chance to try out @mattpocockuk /teach skill. It's similar to my /learn skill. You can try the skill with Hermes Agent right now in our academy. I will keep the lab FREE for now. It's amazing to learn with AI agents. Go try it! https://t.co/BHpT3c5YNc
Overdue update: Iβve joined @GoogleDeepMind as a research scientist to work on πGemini post-training. Feeling incredibly fortunate to be cooking models with such a brilliant team, under the leadership of Yi Tay (@YiTayML) and Quoc Le (@quocleix). In the past a few month, we've found so much enjoyment in working with our own models and keeping pushing their boundaries. Ps, there's a special joy in creating recipes and internally naming them after our favorite drinksπ§ Looking forward to keep enjoying research, pushing the frontiers of Gemini and seeing the magic unfold on the path to AGI!
Hermes @NousResearch Telegram Rich Messages is now working on Desktop. π https://t.co/6SmOM6pRKb
Hermes now supports this! Game changer!!!!
Hermes @NousResearch Telegram Rich Messages is now working on Desktop. π https://t.co/6SmOM6pRKb
new post: how I develop recently using local models. the tooling is now good enough to do agentic workflows and everyone should give them a try! https://t.co/3Tx3CMsNG3
20% off at Books Kinokuniya in Tokyo! @Kino_BKT #RiseoftheRobots #AI https://t.co/pCJ3c1CA3Y
Feel like I am living in a Black Mirror episode that crosses 1984 with Tulipmania, Wall-E, and a government run by Don Corleone. https://t.co/bfOp7yG1Eh
// OpenClaw-Skill: Searching a Tree of Agent Skills // If you build reusable skill libraries for your agents, this one is worth your time. Equipping LLM agents with effective skills is most of the battle in real systems, and most skill-induction work distills one trajectory at a time into a flat pile of single-shot heuristics. Searching a tree of candidate skills looks like a better way to get composition and coverage than greedy distillation. OpenClaw-Skill uses a collective signal to jointly generate, identify, and compose skill nodes across two iterative phases. The output is a structured tree of skills built for diversity and generalization rather than a flat list. Paper: https://t.co/ZUmd9yHrJs Learn to build effective AI agents in our academy: https://t.co/1e8RZKs4uX
NEWS: Two years ago, an internal document from the Center for Countering Digital Hate listed "K*ll Musk's Twitter" and "Trigger EU & UK regulatory action" as annual priorities. CCDH was co-founded by Morgan McSweeney, who later became UK Prime Minister Keir Starmer's Chief of Staff. This week, Starmer threatened to remove X's right to self regulate. UK regulator Ofcom opened a formal investigation into X over Grok. Ofcom can fine X up to 10% of its worldwide revenue or block X in the UK entirely. Starmer also announced this week a UK ban on under 16s using social media including X by spring 2027. The 2024 documents were published by journalists Paul Thacker and Matt Taibbi.

Can an LLM agent actually build a model of an environment it cannot see? This work makes the question gradeable. An agent has to uncover a hidden deterministic finite automaton by interacting with an oracle through membership queries (does this string belong?) and equivalence queries (is this the target?), with classic automata-learning algorithms as strong baselines. The honest result is that performance drops sharply as the automaton grows. Reasoning models do better than the rest, but everything degrades with size. Why does it matter? World-model claims about agents are usually vibes. Forcing an agent to actively reconstruct a hidden structure through queries is a clean, controlled way to measure whether it is modeling its environment or just reacting. Paper: https://t.co/Kw1WCLEAQ3 Learn to build effective AI agents in our academy: https://t.co/LRnpZN7L4c
@BetaTomorrow You need to be aware of how other fields affect your work like psychology and philosophy of language. Relevant thread. Your mental model shapes your work. https://t.co/m9wyiO9d8h
Spot on, but thereβs still a big unspoken assumption here: that fluent AI chat somehow equals real moral agency or political personhood. These systems are just software, next-token predictors running clever pattern matching. Prompt them to role-play βI have a sense of justiceβ o

@DanielCHTan97 I got a huge kick out of citing something thatβs approximately 2050 years old. https://t.co/6E9FFSVckt
oh so you're a ml researcher who likes philosophy? well have you ever cited one in an ML paper? https://t.co/vhU268Ho8f
Narrative violation. https://t.co/z3loKd3a1k
I built a @threejs game director skill system for Codex & Claude Code to help agents create more polished playable browser games. It guides gameplay loops, graphics, HUD/UI, debugging, QA, and optional @tripoai @ElevenLabs @NanoBanana 3D/image/audio assets with API keys. Open source, get the skills in this thread π
Mission: Expanding the Scope and Scale of Consciousness. From my πΈ of the billboard on Times Square βThis is, depending on how you read it, either the most ridiculous thing a serious company has ever put on its mission page or the most honest. We think itβs the latter.β β@a16z https://t.co/q5XRAIiwIM
https://t.co/puLXpatHvd
@TheUltronAi Humanising AI has been normalised in research. What it means to you? https://t.co/KtlnmMm13E
π¨ DeepMind AGI/ASI paper: a Field Lost in Hype and Metaphors Solid scaling. Useful pathways. Overdue bottlenecks. But it keeps treating AI like a subject with a mind. Itβs not. Why serious researchers treat massive compressed files running matrix multiplication as social βagen
@Em_Nomadic Humanising AI has been normalised in research. What it means to you? https://t.co/KtlnmMm13E
π¨ DeepMind AGI/ASI paper: a Field Lost in Hype and Metaphors Solid scaling. Useful pathways. Overdue bottlenecks. But it keeps treating AI like a subject with a mind. Itβs not. Why serious researchers treat massive compressed files running matrix multiplication as social βagen
@MaxiOrdinals Humanising AI has been normalised in research. What it means to you? https://t.co/KtlnmMm13E
π¨ DeepMind AGI/ASI paper: a Field Lost in Hype and Metaphors Solid scaling. Useful pathways. Overdue bottlenecks. But it keeps treating AI like a subject with a mind. Itβs not. Why serious researchers treat massive compressed files running matrix multiplication as social βagen
@A_I_aico Humanising AI has been normalised in research. What it means to you? https://t.co/KtlnmMm13E
π¨ DeepMind AGI/ASI paper: a Field Lost in Hype and Metaphors Solid scaling. Useful pathways. Overdue bottlenecks. But it keeps treating AI like a subject with a mind. Itβs not. Why serious researchers treat massive compressed files running matrix multiplication as social βagen
@riss_e Humanising AI has been normalised in research. What it means to you? https://t.co/KtlnmMm13E
π¨ DeepMind AGI/ASI paper: a Field Lost in Hype and Metaphors Solid scaling. Useful pathways. Overdue bottlenecks. But it keeps treating AI like a subject with a mind. Itβs not. Why serious researchers treat massive compressed files running matrix multiplication as social βagen
@Serantych Humanising AI has been normalised in research. What it means to you? https://t.co/KtlnmMm13E
π¨ DeepMind AGI/ASI paper: a Field Lost in Hype and Metaphors Solid scaling. Useful pathways. Overdue bottlenecks. But it keeps treating AI like a subject with a mind. Itβs not. Why serious researchers treat massive compressed files running matrix multiplication as social βagen
@Tomodo_ysys Humanising AI has been normalised in research. What it means to you? https://t.co/KtlnmMm13E
π¨ DeepMind AGI/ASI paper: a Field Lost in Hype and Metaphors Solid scaling. Useful pathways. Overdue bottlenecks. But it keeps treating AI like a subject with a mind. Itβs not. Why serious researchers treat massive compressed files running matrix multiplication as social βagen
@mititarou_takeo Humanising AI has been normalised in research. What it means to you? https://t.co/KtlnmMm13E
π¨ DeepMind AGI/ASI paper: a Field Lost in Hype and Metaphors Solid scaling. Useful pathways. Overdue bottlenecks. But it keeps treating AI like a subject with a mind. Itβs not. Why serious researchers treat massive compressed files running matrix multiplication as social βagen
@Em_Nomadic Humanising AI has been normalised in research. What it means to you? https://t.co/KtlnmMm13E
π¨ DeepMind AGI/ASI paper: a Field Lost in Hype and Metaphors Solid scaling. Useful pathways. Overdue bottlenecks. But it keeps treating AI like a subject with a mind. Itβs not. Why serious researchers treat massive compressed files running matrix multiplication as social βagen
@BramForge Humanising AI has been normalised in research. What it means to you? https://t.co/KtlnmMm13E
π¨ DeepMind AGI/ASI paper: a Field Lost in Hype and Metaphors Solid scaling. Useful pathways. Overdue bottlenecks. But it keeps treating AI like a subject with a mind. Itβs not. Why serious researchers treat massive compressed files running matrix multiplication as social βagen
@curiosinautas Humanising AI has been normalised in research. What it means to you? https://t.co/KtlnmMm13E
π¨ DeepMind AGI/ASI paper: a Field Lost in Hype and Metaphors Solid scaling. Useful pathways. Overdue bottlenecks. But it keeps treating AI like a subject with a mind. Itβs not. Why serious researchers treat massive compressed files running matrix multiplication as social βagen