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Nemoclaw is now released π€ Sandboxes and policy controls to run OpenClaw safely. Leverages local GPU if available Itβs still in alpha, but check it out https://t.co/WWFR43a6Qi https://t.co/UJ4dphlkZP
Lobster has entered the building π¦ππ€ @steipete @NVIDIAAIDev https://t.co/O4O78V4tA2
π¨URGENT MENTAL HEALTH UPDATEπ¨ Klaus Kinski Explosive Rage Fancam π€¬sound onπ€¬ https://t.co/X45Bq5OPLl
π¨URGENT MENTAL HEALTH UPDATEπ¨ Klaus Kinski Explosive Rage Fancam π€¬sound onπ€¬ https://t.co/X45Bq5OPLl
Nemoclaw is now out π€ Sandboxes and policy controls to run OpenClaw safely. Leverages local GPU if available Itβs still in alpha, but check it out https://t.co/WWFR43a6Qi https://t.co/dPmG283TlH
Lobster has entered the building π¦ππ€ @steipete @NVIDIAAIDev https://t.co/O4O78V4tA2
State lawmakers introduced over 1,200 AI bills in 2025. They cover everything from deepfakes to autonomous weaponsβbut they're all just lumped together as "AI policy." @ARozenshtein and I wrote an article that breaks down the policy landscape along three dimensions: (1) what harm are you addressing, (2) what are the factors shaping how you should design your policy intervention, and (3) which actors in the ecosystem should you target? The diagram below, for example, maps the AI ecosystem from chip manufacturers to end users.
#NVIDIAGTC news: NVIDIA announces NemoClaw for the OpenClaw agent platform. NVIDIA NemoClaw installs NVIDIA Nemotron models and the NVIDIA OpenShell runtime in a single command, adding privacy and security controls to run secure, always-on AI assistants. https://t.co/v1LtP3c8ZW
NEWS: NVIDIA has announced that BYD, Geely, Isuzu and Nissan will use the company's DRIVE Hyperion platform to develop level 4 autonomous vehicle programs. Nvidia also introduced Alpamayo 1.5, "an upgrade that expands NVIDIA Alpamayo β an open portfolio of AI models, simulation frameworks and physical AI datasets for building safe, transparent, reasoning-based AVs β with an interactive, steerable reasoning model." Jensen Huang: The autonomous vehicle revolution is here, the first multitrillion-dollar robotics industry. Everything that moves will eventually be autonomous. The NVIDIA Hyperion platform and our Alpamayo open reasoning models give vehicles the ability to perceive their surroundings, reason through complex situations and act safely, making scalable, level 4 autonomy possible.β
Your AI agents can now learn entire skill trees from the web. Meet the new HyperSkill Give it a topic. It reads the docs and builds a skill tree your agent can navigate.Browse the graph. Download. Drop into your project. Open source. Powered by Hyperbrowser. https://t.co/9OC8e8urgH
The most anticipated announcement of the keynote: NVIDIA is announcing a new LPU, the @NVIDIA @GroqInc 3 LPU, that pairs with Vera Rubin NVL72 via a dedicated LPX rack connected over Direct C2C. Claims are 35x inference throughput over Blackwell for trillion-parameter models. The idea is to combine GPU throughput with LPU latency to push the Pareto curve on high-interactivity workloads. Lots of questions still on cost, capacity tradeoffs, and real-world deployment, but the architecture concept is fascinating.

OmniForcing unlocks real-time joint audio-visual generation Achieves ~25 FPS with 0.7s latencyβa 35Γ speedup over offline diffusion modelsβby distilling bidirectional LTX-2 into a causal streaming generator with maintained multi-modal fidelity. https://t.co/UGYGMyTQOs
We're live at @NVIDIAGTC! π Find us at Booth #3004, San Jose Convention Center. We'll be here all week running live GPU demos on NVIDIA Blackwell. Come see MAX + Mojo π₯ in action. #NVIDIAGTC https://t.co/klsRp0dnlT

Subagents are now available in Codex. You can accelerate your workflow by spinning up specialized agents to: β’ Keep your main context window clean β’ Tackle different parts of a task in parallel β’ Steer individual agents as work unfolds https://t.co/QJC2ZYtYcA
But how do we turn this record growth into healthy communities? Here is how open source scales in a global era. π https://t.co/6Ai1U64zCs
The online community of Tesla believers has grown more zealously defensive of the company and CEO Elon Musk, even as flashy promises fizzle and Musk grows more politically radioactive. But some Tesla owners have tired of this "cult" mentalityβand are voicing their dissent. https://t.co/5KVEVFJygS

Story: https://t.co/2NkLqNzB5t
Monday morning shitposting: let's teach kids ancient history with METR-style plots https://t.co/7a1NEJR6GQ
This, but for real* Hereβs METR-style graph of labor displacement from Roman aqueducts, doubling time of CDDII years. Lesson: 1) Displacing terrible work is good 2) All exponentials become s-curves in the end * I had GPT-5.4 Pro do the research, spot checks seemed accurate. https://t.co/9XZTwmDQxP
Monday morning shitposting: let's teach kids ancient history with METR-style plots https://t.co/7a1NEJR6GQ
Grok's Text to Speech API is now available. Start building with natural voices and expressive controls to bring your apps to life. https://t.co/SMxWTB9m6N https://t.co/UtHT0uN148
Are you ready Palo Alto??? Genspark Claw is live, and we're getting together next Monday (Mar 23, 5β8pm). β Live founder talk β Genspark Claw setup β Leave with a workflow you can use the next day + fun prizes! Every attendee gets 1 week free + 5,000 credits. Best use case wins 12 months of Genspark Claw. Spots are limited, so RSVP soon. See you there! https://t.co/5xra8tW07j
NVIDIA now selling Groq chips https://t.co/zebuQokHSz
The gates of Pancake Town are OFFICIALLY OPEN π°π₯ The first-ever interactive AI-agent world powered by PancakeSwap AI Skills. πEnter here: https://t.co/WDkUgqO1ZB https://t.co/qIzLS5qL2W
Jensen is proud of being a SemiAnalysis InferenceX King π€£ https://t.co/V86K28OKg6
F Cancer Why has AI had so little impact on Cancer? New essay, link below. https://t.co/cLsoh7c7do
Jensen's summary of the AI progress in the past 2-3 years https://t.co/72LI1HMl4H
Jensen expects over $1T in revenue through 2027... https://t.co/70O1T0F177
not to be pedantic but imo not a single one of these are AI for healthcare companies (from GTC slides) https://t.co/STugiTTxvO
Covo Audio πA end-to-end audio language model from @TencentAI_News https://t.co/tic5cH1A39 β¨ 7B β¨ Audio β Audio in one model β¨ Multi-speaker + voice transfer β¨ Real-time full duplex conversations https://t.co/hFrsxQgzkT

Covo Audio πA end-to-end audio language model from @TencentAI_News https://t.co/tic5cH1A39 β¨ 7B β¨ Audio β Audio in one model β¨ Multi-speaker + voice transfer β¨ Real-time full duplex conversations https://t.co/hFrsxQgzkT
π€―BREAKING: Alibaba just proved that AI Coding isn't taking your job, it's just writing the legacy code that will keep you employed fixing it for the next decade. π€£ Passing a coding test once is easy. Maintaining that code for 8 months without it exploding? Apparently, itβs nearly impossible for AI. Alibaba tested 18 AI agents on 100 real codebases over 233-day cycles. They didn't just look for "quick fixes"βthey looked for long-term survival. The results were a bloodbath: 75% of models broke previously working code during maintenance. Only Claude Opus 4.5/4.6 maintained a >50% zero-regression rate. Every other model accumulated technical debt that compounded until the codebase collapsed. Weβve been using "snapshot" benchmarks like HumanEval that only ask "Does it work right now?" The new SWE-CI benchmark asks: "Does it still work after 8 months of evolution?" Most AI agents are "Quick-Fix Artists." They write brittle code that passes tests today but becomes a maintenance nightmare tomorrow. They aren't building software; they're building a house of cards. The narrative just got honest: Most models can write code. Almost none can maintain it.
π¨ Want to parse complex PDFs with SOTA accuracy, 100% locally? ππ At just 0.9B parameters, you can drop GLM-OCR straight into LM Studio and run it on almost any machine! π₯ π§ 0.9B total parameters πΎ Runs on < 1.5GB VRAM (or ~1GB quantized!) πΈ Zero API costs π Total data privacy Desktop document AI is officially here. π»β‘
Yann LeCun is pumping out papers recently βTemporal Straightening for Latent Planningβ This paper shows that by straightening latent trajectories in a world model, Euclidean distance starts to reflect true reachable progress, so it's closer to geodesic/minimum-step distance. This makes gradient-based planning far more stable and effective without relying as heavily on expensive search.
7 emerging memory architectures for AI agents βͺοΈ Agentic Memory (AgeMem) βͺοΈ Memex βͺοΈ MemRL βͺοΈ UMA (Unified Memory Agent) βͺοΈ Pancake βͺοΈ Conditional memory βͺοΈ Multi-Agent Memory from a Computer Architecture Perspective https://t.co/5X5LxirSEx https://t.co/5Hi0Gn3aA4
