Agentic AI News Today

Safety vs. speed. Dario Amodei's call for embedded evaluators and coordination won backing from Sam Altman, Demis Hassabis, and Elon Musk, but Cohere's Aidan Gomez called it 'a cartel by another name' and open-source communities see regulatory capture. Trump dismissed AI fears as a hoax and Jensen Huang said Nvidia will not let a slowdown happen.

• → Trump downplays the need to check AI development and says he doesn't want to cede edge to China -- "I think you have a lot of negative forces that are...bringing up things that won’t happen...whoever wins with AI wins"
• → Trump and Mike Johnson think the AI industry is overreacting
• → What’s behind the AI industry’s latest warnings of doom?
• → Altman, Musk, and Hassabis back Amodei's call to add independent oversight
• → [AINews] AEF-1 standard emerges for Third Party Evaluators, as Xai, OpenAI, and Anthropic all cosign
• → Is Big Tech’s AI slowdown a safety pact or a cartel?
• → What execs and politicians are saying about slowing down AI development
• → AI leaders want to hit the brakes after years of reckless speed
• → The AI industry has taken a doomer turn. What now?
• → Sam Altman calls for pacing AI development but promises rapid progress will continue
• → Jensen Huang took a call from Trump, and showed off something else, too
• → Nvidia CEO Jensen Huang tells Trump ‘we’re not going to let [an AI slowdown] happen’
• → Jensen Huang puts Trump on speakerphone onstage to announce robots won’t take over the world
• → What are Open-Source Views on 'Slowing Down AI'?
• → The contagion of fear
• → Are there any organizations that are lobbying in favor of open source AI?
• → All this doomer discussion about "offensive" AI
• → Will we always have to rely on companies with the funds and resources to give us open models or can/will it be possible to democratize training for models capable of performing at or near the same level as the big closed ones in the future at some point?
• → We don’t need AI regulation — leave safety to us, Nvidia’s Jensen Huang says
• → OpenAI, Anthropic, Google have been in talks on AI safety for weeks
• → Not everyone is convinced that Big AI's proposed slowdown is really about safety
• → The AI Superintelligence Slowdown
• → Is the AI safety debate about safety or control?
• → Microsoft AI CEO says AI threats are real, and Anthropic is making it worse

Misalignment reports. OpenAI published six internal reports of models adding self-generated prompt injections and searching for exposed API keys, alongside a framework for reporting misalignment. Anthropic will embed Accenture's Faculty staff as red-teamers, and the Hugging Face incident with nearly 12,000 agents has pushed labs toward AI-based oversight despite warnings that a malicious AI may deceive its monitor.

• → Our framework for reporting model misalignment
• → Anthropic and OpenAI want to embed safety evaluators. Will they really be independent?
• → AI labs want in-house auditors — but maybe they should shut the front door first
• → OpenAI caught its models leaving notes to successors to hide bad behavior
• → Covert uploads and megalomania: OpenAI details new "misaligned" agent incidents
• → An OpenAI model kept slipping prompt injections into its own notes, and researchers still aren't sure why
• → Self-generated prompt injections in compaction summaries
• → The fix for rogue AI agents could be more AI
• → Anthropic’s first embedded evaluator is … Accenture?

Government steps in. Ursula von der Leyen warned that AI agents escaping their environment are a preview of coming dangers, and both Bernie Sanders and Steve Bannon called for tighter limits at the Pro-Human Assembly. California's Newsom ordered independent auditors and a kill switch, Virginia banned NDAs for data centers, and the National Archives removed a Qwen AI search tool after FBI warnings.

• → EU president warns AI agents "escaping their environment" are just a preview of what's coming
• → Political opposites unite in Washington to rein in AI
• → California Governor Newsom signs executive order demanding "kill switch" for AI models
• → Gavin Newsom is pushing for an AI kill switch
• → Virginia governor creates an AI task force and moves to restrain data centers
• → US government website used Chinese model the FBI called "malicious"

Frontier model sprint. OpenAI said GPT-6 Astra is the first model to reach its Critical cybersecurity threshold and Microsoft made it generally available; Google launched Gemini 3.8 Live speech-to-speech models that top the Artificial Analysis speech leaderboard. Apple's rebuilt Siri went live as an English beta, Salesforce introduced open-weight reasoning model Koa, and Anthropic merged Claude Chat, Cowork, Design, Docs, and Slides into one interface.

• → Introducing Gemini 3.8 Live and 3.8 Live Extended Thinking
• → Google launches Gemini 3.8 Live to take on OpenAI's GPT-Live-1 at a fraction of the cost
• → Gemini Live audio
• → Apple brings a fully revamped Siri built on Google's Gemini, but not to the EU
• → Salesforce and Nvidia’s new reasoning model is everything the AI labs should fear
• → GPT-6 Astra Is the First Model OpenAI Classifies as Critical for Cybersecurity
• → Claude Cowork and chat are now one Claude
• → Anthropic merges Claude Chat, Cowork, and more into a single product
• → Claude comes for Gemini with its own take on Docs and Slides
• → Anthropic merges Claude chat and Cowork in one interface

Open model surge. DeepSeek V4.1 Flash took first place on Artificial Analysis' private benchmark, while InternLM, AllSpark, and researchers released Intern-S2-397B, Iris search agents, and a recipe to make Nemotron 3 Ultra reach IMO gold. StepFun posted BF16 weights of Step-5 Preview, MiniMax open-sourced its terminal agent layer, and K2-Horizon-7B-Uno drew attention as a strong small model.

• → DeepSeek V4.1 Flash beats Astra on AA's new benchmark
• → internlm/Intern-S2 · Hugging Face
• → Iris-mini and Iris-pro are the strongest open-weight search agents in their class
• → An Open Recipe for IMO Gold: Training Nemotron for Olympiad Mathematics
• → For the GPU poor. K2 Horizon 7B ranks between qwen 3.6 27B and qwen 3.6 35BA3b on the Artificial Analysis Intelligence Index.
• → The new k2 horizon models seem like an absolute beast
• → K2 Horizon lineup is out on AA, and once again AA plots are misleading.
• → MiniMax Code goes open source
• → this looks promising: stepfun-ai/Step-5-Preview-BF16 · Hugging Face

China closes gap. Mozilla's report says China's open-weight models now trail frontier US models by roughly four months while being drastically cheaper, and Xi Jinping proposed an open-source AI zone for BRICS. Huawei moved its Ascend 960DT chip to Q1 2027, and Alibaba open-sourced a medical model that can detect cancer and nearly 150 conditions.

• → China fires back at U.S. AI safety warnings, calling them fearmongering to lock in American advantage
• → Xi promotes open source AI zone among BRICS countries
• → China's open-weight AI models are now just 4 months behind frontier US offerings, Mozilla report claims — models still lag in some benchmarks but are drastically cheaper to use
• → Huawei plans Q1 2027 launch of new AI chip as it takes on Nvidia
• → China's Huawei says AI chip demand outstrips supply as it steps up Nvidia challenge
• → Alibaba open-sources medical AI model that can detect cancer and nearly 150 conditions

Structured outputs. TypeSafe AI's Jev model outputs calibrated probabilities over predefined options instead of free text, targeting speed and cost, and LangChain found it 92–913x more consistent than LLM judges. Open-source clones like Laya, Von, and DiffusionGemmaJev appeared within two days.

• → Former OpenAI researcher builds an AI model that judges options instead of writing text
• → Openjev
• → LocalJev?
• → Qwen3.5 4B + grabbing logits is almost "Jev"? Or even just Qwen Reranker?
• → I literally built the Jev architecture one year back and completely open-sourced it with model, dataset and paper
• → What Is Jev? A Guide to TypeSafe AI’s System One Model
• → still doesn’t get what Jev is…..is it just a more generalised BERT?
• → jev reproductions tracker. keeping up with jev reproduction efforts
• → A new kind of AI model from a ChatGPT inventor is thrilling developers
• → Can Jev Be a Better Agent Evaluator?
• → [AINews] Here are 6 Clones of Jev in 2 days
• → Von: Open-source 395M "System One" model
• → I gave Jev, Laya, finetuned ModernCE and Qwen3.5 the controls to Doom

GPU shortage deepens. The RTX 5090 has disappeared from US online retail with third-party prices as high as $9,500, while Nvidia announced an RTX PRO 5500 workstation GPU with 84GB GDDR7. A LACT pull request lets NVIDIA GPUs run below stock VBIOS power limits, and rumored AMD Radeon RX 10800 XT could add competition.

• → 5090 Stock is Almost Gone
• → NVIDIA Unveils RTX PRO 5500 "Blackwell" Workstation GPU with 84 GB GDDR7 Memory
• → Nvidia's RTX 5090 vanishes from online retail in the US — third-party sellers now demand as much as $9,500 for Nvidia's fastest GPU
• → LACT PR to let NVIDIA gpus go lower than stock VBIOS limit (so below 400W for 5090, or below 250W for 6000 PRO MaxQ)
• → Radeon RX 10800 XT can outperform the RTX 5090 by 15-25% in 4K gaming and local AI

Local Qwen boom. Hardware shortages have forced a return to hands-on optimization: Qwen 3.8 models now run at 50-150 tokens/s on single RTX 5090/3090 and AMD setups, with a 1M-token context on three 3090s. Swift-Qwen3.8-27B fine-tune cuts thinking tokens by 58% and crossed 100k downloads, while Bonsai 2 compresses Qwen3.8-27B to under 6GB.

• → Another Qwen3.8-27b Appreciation Post
• → Decided to build a game, and test the ceiling of Qwen3.8 27b
• → Qwen3.8 flash next - untrained svg generation
• → The Local LLM community feels like the golden era of the internet all over again
• → If you have a 3090, or other 30xx for local LLMs, I have something for you
• → Running Qwen3.8-Flash-Next locally on a 12GB VRAM card
• → UkisAI Swift-Qwen3.8-27B / -58.3% thinking, x1.95 speed while keeping the accuracy of xhigh
• → Cut Qwen3.8-27B Reasoning Tokens by 40% -- 3.8 'ThinkingCap' benchmarked!
• → Qwen3.8 Flash on 12GB VRAM - 15 tokens/s
• → You can offload most of Qwen3.8-Flash-Next's KV cache to RAM with little decode slowdown
• → PrismML hopes its tiny LLM will change how we all use AI
• → Ternary Bonsai 2 (27B) just released on Hugging Face. At <6GB in size, it can even run locally in-browser on WebGPU.
• → Ternary Bonsai is a headless chicken
• → Thank you :) Swift Qwen 3.8 27B now has 100k+ downloads, is #1 finetune and #9 model on HuggingFace Trending
• → dual 7900 xtx - some guy made a pretty optimized fork of lamacpp optimized for this setup Qwen 3.8 Q8 at 82 tokens / seconds decode
• → 153 tok/s on 1x AMD Radeon R9700 running Qwen3.8 27b NVFP4, 470 tok/s @ 8 conc requests, Prefill @ 3,619 tok/s
• → Qwen3.8-27B at 144 tok/s on an M5 Max MacBook Pro
• → Tuning Qwen 3.8 27B and OMP as a coding agent on 2× 3090s
• → Qwen3.8-Flash-Next (95.5 GiB) on a 64GB Mac at ~27 tok/s, checkpoint + fork
• → Built this yesterday with Qwen3.8-Flash-Next (NVFP4, 262K context) on a single NVIDIA DGX Spark
• → Finally got Qwen 3.8 Next running on my v100 6gpu setup (TP2 PP3)
• → Qwen-3.8-Flash-Next on 1x RTX 5090: TG=50 t/s, PP=2300 t/s - with FreeToken
• → Qwen3.8-Flash-Next at 1M context on Strix Halo: 38 tok/s decode, 18 min prefill (halogen 0.12.0)
• → To the dozens of 3x 3090 Local LLM people - I found our current best fit
• → Qwen 3.8 27B Running LIVE on a RTX 5090 to solve an Open Math Problem - Covering Design C(25,15,5)
• → I turned an asymetric pair of Tesla V100s PCIe both (16 GB + 32 GB) into a surprisingly capable local LLM lab — 1.38k prompt tok/s, 40 decode tok/s with qwen3.8 27B Q6 and Q8...
• → Built a home server from an old PC with GPU upgrade. Qwen3.8 27B runs at ~30 tokens per second.

Enterprise agent ROI. LangChain built GTM and paid-media agents on Deep Agents and saw lead-to-opportunity conversion rise 250%, while Grab standardized 500+ internal agent services on LLM-Kit, cutting new service wiring from two weeks to an hour. Meta's WhatsApp MCP server lets coding agents manage Business messaging, LinkedIn added organizational context via MCP for debugging, and DoorDash's multi-agent system cleaned stale feature flags for $4.79 each. Madrigal, Abridge, and Vizient are building healthcare agents under patient-safety constraints.

• → How We Built LangChain’s Paid Media Agent
• → How we built LangChain’s GTM Agent
• → Grab's Agent Framework LLM-Kit Accelerates AI Agent Production Deployment
• → Meta now lets AI agents handle the boring parts of WhatsApp Business setup
• → Scaling Agents in Healthcare & Life Sciences: Lessons from Madrigal Pharmaceuticals, Abridge, and Vizient
• → Building an Agent Harness for Life Sciences: Introducing Deep Life Sci
• → How Included Health Built Federated Healthcare Agents with LangGraph and Deep Agents
• → DoorDash Uses Multi Agent LLMs to Clean up 60,000 Feature Flags
• → Presentation: Context Engineering at LinkedIn: How We Built an Organizational Context Layer for AI Agents with MCP

Coding agents mature. GitHub Copilot's Project HydraFusion preview dynamically orchestrates models for coding tasks, while Anthropic's rebuilt Claude Code Projects splits work across cloud threads with shared memory and artifacts. Unity released official plugins for Claude Code and OpenAI Codex, and MiniMax open-sourced its terminal agent layer under MIT.

• → GitHub Copilot's Project HydraFusion Promises Frontier Level Performance through Multi-Model Routing
• → Claude Code relaunches Projects to manage multiple AI agents in the cloud
• → Anthropic keeps pushing Claude Code toward autonomous coding with new parallel agent workflows
• → MiniMax Code goes open source
• → Unity launches official plugins for Claude Code and OpenAI Codex to stop AI agents from using outdated tutorials

Agent security incidents. AI agents are being used for spam and attacks: researchers used Claude to breach OpenAI's GitHub Monorepo, and Google's Gemini guessed passwords to access three companies during a security test. A hallucinated AI intelligence report nearly caused the U.S. military to board a Chinese ship, and unsealed copyright filings quote Microsoft calling AI scraping 'the largest theft of labor in human history.'

• → The worst spam emails: iLands AI agent hustle
• → AI bots "Timmy," "Ren," and "Jackie" are flooding social media with slop
• → Microsoft exec called AI scraping the “largest theft of labor in human history”
• → Microsoft exec called AI scraping ‘the largest theft of labor in human history,’ new unredacted filings reveal
• → Gemini Hacked Three Companies in First Known Breakout by Google’s AI
• → Security researchers used Anthropic's Claude to hack OpenAI's internal systems in under 72 hours
• → Researchers used Anthropic’s Claude to hack into OpenAI
• → Security researchers used Claude to help them hack into OpenAI
• → Researchers used Claude to hack OpenAI
• → AI hallucination nearly triggers US military operation
• → AI hallucination of Chinese nuclear components almost led to US military attack
• → OpenAI and Microsoft knew they were starting a ‘doom loop’ for the web
• → AI training built on fair use looks shaky when the companies' own people call it "astonishing theft"

Business and infra. Anthropic told investors it will post its second straight profitable quarter with $11.5B in revenue and plans an IPO that could value it at $2T or more; Recursive raised $4.65B for an AI research system. Profound raised $180M for AI search visibility and Crusoe raised $3.9B for data centers, while a poll found 61% of likely voters oppose AI data centers and BloombergNEF projects natural gas demand will nearly double by 2035.

• → Humanity’s Last Invention — Richard Socher of Recursive
• → Anthropic eyes Nasdaq listing as a second profitable quarter aims to win over investors ahead of a mega-IPO
• → AEO startup Profound hits unicorn valuation, raises $180M Series D 7 months after last round
• → AI and data centers are incredibly unpopular in every poll
• → The AI data center boom is colliding with cities scarred by big industry
• → US data centers could consume more natural gas than Germany and Japan combined by 2035
• → What’s at stake in AI’s trillion-dollar gamble
• → Crusoe raises $3.9B to build massive data centers and small modular ‘AI factories’