#2 across all new releases in Canada. https://t.co/dvPbneSOx2

An early beta of Grok Build, an agentic CLI for coding, building apps, and automating workflows is now available for SuperGrok Heavy subscribers. Through this early beta, we will improve the model and product based on your feedback. Try it at https://t.co/bpTHpjivWD https://t.co/Rlg4qMLkrv

https://t.co/l9OZrEYGAL

https://t.co/l9OZrEYGAL

The MAX-LLM book just made it even easier to build an LLM from scratch. The new notebook format lets you run the GPT-2 components interactively, inspect real tensor shapes, and generate text from pretrained weights. Prefer to browse first? The pre-rendered version shows all outputs without running a cell: https://t.co/V3tysngguO

Aleph, our fully autonomous AI agent system for formal verification, aced all major theorem proving benchmarks including PutnamBench, VeriSoftBench, and Verina https://t.co/spIql8Pf4g

Interesting position paper on agentic AI as a foreseeable pathway to AGI. (bookmark it) There has been strong debate on whether a larger single model get us there or a multi-agent system. The authors argue that agentic AI systems, not bigger foundation models on their own, are the most foreseeable route to AGI. Formalizes what "agentic" actually contributes beyond the base model: memory, reasoning, tool use, self-improvement, alignment. Each is a separable axis with its own bottlenecks (long-horizon coherence, credit assignment, safety auditing). They argues that none of those bottlenecks get solved by another order of magnitude on pretraining compute. Paper: https://t.co/ppz4mh7kde Learn to build effective AI agents in our academy: https://t.co/1e8RZKs4uX

Boston, we're coming for you. May 29 we're hosting Engineers Day as part of the first ever Boston Tech Week. Our team will be on the ground sharing what actually works (and what breaks) when you're building agent swarms. Food, drinks + real talk with people actually shipping. https://t.co/y8ixt9e8Q6

@Techweek_ RSVP 👇 https://t.co/0DTHyv6MEE https://t.co/jx7qRc0uPp

Video: https://t.co/0uGlly09wx Vid has results but also some thoughts on how fun + easy this was! Hopefully inspires you to try some things too :) https://t.co/jUCXarg9NV

// Harnessing Agentic Evolution // Pay attention to this one if you run iterative agentic search loops. (bookmark it) AEvo splits the self-improvement loop into two jobs: > One proposes the next candidate. > The other watches what worked, what failed, and edits the procedure that proposes future candidates. Past runs (candidates, feedback, traces, failures) become memory the meta-agent reads from. Achieves 26% relative gain over the strongest evolution baseline on agentic and reasoning benchmarks. SOTA on three open-ended optimization tasks under the same iteration budget. If you are accumulating agentic search logs you never use, this is how to feed them back into the search procedure itself. Paper: https://t.co/eWFO4rI4iA Learn to build effective AI agents in our academy: https://t.co/LRnpZN7L4c

🚀 Ring-2.6-1T is now open source. A trillion-scale flagship thinking model built for real-world complex tasks: Agent workflows, coding & engineering, long-horizon tasks, complex reasoning, research, and enterprise automation. It is designed to move beyond “answering” toward execution: understanding context, planning steps, calling tools, and staying stable across long task chains. Highlights： - Advanced agentic workflow support. - Reasoning effort levels: high for agentic tasks, xhigh for complex reasoning. - Scalable asynchronous RL via the IcePop algorithm, enabling stable, trillion-scale training for long-horizon agentic RL.

we built the first sane way to debug your agent locally. you can see your traces. codex/claude code can too. this lets them write evals and test your agents automatically. best part: it's completely free and open source. install with 1 line. (github below) https://t.co/ln5LEZzEHu

Thanks pydantic. https://t.co/Syt1wj0UJL

Are scaling laws finally working for time series foundation models? Today, @datadoghq is releasing Toto 2.0 weights in Apache 2.0 on @huggingface. It's a family of open-weights TSFMs from 4M to 2.5B parameters, where every size beats the last from a single hyperparameter config. First across the leading benchmarks: BOOM, GIFT-Eval, and TIME. Most TSFM families ship multiple sizes that all perform roughly the same. This one doesn't. Why it matters: scaling laws gave language and vision a predictable relationship between compute, data, parameters, and downstream performance. Time series hasn't had that curve until now. Once you have it, you can scale data and compute with confidence, and start asking which new capabilities emerge at the next order of magnitude. 2.5B open-source weights: https://t.co/prpcGoCw0U 4M open-source weights: https://t.co/5d6rw5NYL2 Blogpost: https://t.co/xKazgTMh1I

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This one blew my mind back in the day! From "Learning Invariant Features through Topographic Filter Maps" (2009) by @koraykv, @MarcRanzato, @rob_fergus and @ylecun https://t.co/IjzRi4R9X6

We're releasing a whole new category of voice models. Introducing DramaBox — our state-of-the-art, open source voice model built for cinematic use cases. Traditional TTS gives you a voice. DramaBox by @resembleai gives you a performance. For too long, Voice AI has been stuck in "robotic assistant" mode. If you wanted dramatic emotion, sighs, or a voice cracking with grief, you had to hire an actor or spend hours editing. We fixed that.

introducing Parafield, the spatial sound intelligence. the FIRST agentic platform that combines voice, music, and sound effect, to create a personalized 3D sound experience for you. if you're interested in sci-fi, arts, and/or spirituality experience, this is for you. comment "sound" to access early beta. watch it with 🎧

We've published a paper that explains our views on AI competition between the US and China. The US and democratic allies hold the lead in frontier AI today. Read more on what it’ll take to keep that lead: https://t.co/TgJBeodWYK

More info at https://t.co/enHVCyIz53

Introducing Vesta The AI for your closet Vesta gives you daily outfits based on your wardrobe, your schedule, the weather, and your style. The days of having “nothing to wear” are over. https://t.co/x8IJiUv78V

NEWS: OpenAI hit with Class-Action Privacy Lawsuit for Sharing ChatGPT Data with Google and Meta. Sam Altman's OpenAI secretly embedded Meta’s Facebook Pixel and Google Analytics into ChatGPT, turning your most private conversations about health, finances, legal issues, and confidential company data into ad-targeting data sent straight to Meta and Google without consent. This violates federal wiretap laws. OpenAI enabled surveillance for profit.

Sanders and AOC introduced a bill to pause ALL AI data center construction. 300+ local bills filed. Half of planned 2026 data centers facing delays or cancellation. Each one brings billions to local economies. The people who say they want American jobs are trying to block the biggest job creation engine since the interstate highway system.

Check it - can fill in erased bits and denoise partially noised images! https://t.co/1ujiBMsK8v

Some repair snapshots https://t.co/6zs685DcWT

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Dream Air SE combines lightweight design, micro-OLED visuals, and eye tracking into an accessible next-gen VR headset starting at $899. Pre-order now to receive exclusive pre-order benefits: https://t.co/iv4ySczJWi https://t.co/GJd6fHLLW3

Dang I love this new world of hand-waving software into existence https://t.co/JOTYY1LUwJ

OpenClaw users who bought a Mac Mini right now: https://t.co/CYTSVPOfY3

me 10 mins into looking at agentic/harness benchmarks. https://t.co/CLkItyCwLy

me 10 mins into looking at agentic/harness benchmarks. https://t.co/CLkItyCwLy

OK may as well try the obvious one: can NCA learn to denoise? Can they generate images? We'll find out :) https://t.co/WNA2FdnJUf

I'm also training them to infill-noise, for the sole reason that it'll make a killer demo later :) https://t.co/bfWL0QVZAT