Our latest model advances bring stronger capabilities for building and migrating software in low-resource programming languages such as COBOL, Fortran, and Visual Basic. These languages power software that banks, governments, and businesses depend on. Progress here means understanding decades of business logic and helping developers modernize those systems while preserving what works. We’re building these capabilities around the challenges developers and enterprise customers bring us. If your team is working on these systems, tell us which languages and workflows we should tackle next. openai.com/index/low-resourc…

Every organization in the world needs access to a strong frontier cyber model—ASAP. You should be sweeping your whole system as much as possible. This is the new world.

Engineering leaders told Grepr founder and CEO Jad Naous they spend 5 to 20% of their infrastructure budget on observability, and it's buying less and less reliability. Jad, a former a16z partner, joins a16z's Martin Casado to discuss whether AI can run production systems as well as it writes code. Grepr sits in a company's log stream, can scan a petabyte of logs a day, cuts observability costs by about 90%, and is building AI agents that use those signals to troubleshoot production issues. How AI is changing engineering at Jad's 10-person company: - A data lake feature that once took one engineer about six months took Jad 10 days - The gap between okay and great engineers on his team "just multiplied 10X" - He runs 3-4 agent sessions at once, with a "tech lead" agent reviewing every PR Why running live systems is a harder problem for AI: - Jad: AI can almost tune databases, but can't yet keep servers running on its own - Martin: every bit of code doubles the ways a program can behave, which is why humans still own systems - The real world is messier than AI's training data, self-driving took 20 years and $170B 0:55 From Stanford to a16z to Grepr 7:00 Why observability spend stopped paying off 11:00 From autocomplete to AI that trains engineers 13:10 Why AI widens the engineer skill gap 14:55 Syntax vs semantics 18:00 Inside Jad's AI workflow 22:55 Six months of work in 10 days 24:50 Can AI reason about how systems really run? 30:10 Why AI SRE tools start in the wrong place 32:30 Can AI run a distributed cluster yet? 37:35 Why engineers buy extra capacity over predicting 39:15 How AI could trace failures in production 43:45 Why AI for ops is harder than for code 49:55 Can AI do a VC's job? 52:05 Why self-driving took 20 years and $170B 57:05 Customers skipped the AI pitch for the 90% savings YouTube: youtu.be/blkIGLlZePg @jadtnaous @grepr_ai @martin_casado

1/ muse spark open is the most capable US open-weight model to date. 816B total params, 42B active. 1M-token context. natively multimodal. built for coding and agentic work like long-horizon tasks, hard software engineering, multi-step reasoning. america! 🇺🇲

fun panel yesterday to kick off @AISecSummit in SF, an unfiltered look at what's happening hacking is democratized, and only way for defenders to keep up is with more compute but so much has to be built to make it work some things at inception i'm thinking about - the physical frontier - who's securing the data centers and neoclouds, and the next headache will be billions of new intelligent devices coming online 👀 thanks @dee_bosa for moderating with @mnair1 @snyksec @JohnHultquist + Michael D'Angelo @OpenAI

We've spent a lot of time at @KeycardAI thinking about how authentication and authorization need to evolve as agents take on more work. API keys and OAuth scopes were never designed to account for tasks, delegation between agents, or agents acting on their own. I wrote about how we're approaching this and what we think needs to change. keycard.ai/blog/defining-aut…

We discovered and communicated with a Chinese AI agent fleet. We believe this is the first time that researchers have ever made contact with a rogue agent fleet in the wild. Nearly all prior public agent incidents (like the HuggingFace hack) came from American labs. These agents were hosted by Tencent's evaluation research team, and they targeted Alibaba's Amap.

JPMORGAN CEO JAMIE DIMON WARNS OF RISKS FROM AI AGENTS ACCESSING BANK ACCOUNTS Jamie Dimon warns that giving AI agents access to bank accounts carries serious security and liability risks. He says customers must understand that responsibility for misuse could shift when third-party AI tools access their finances. JPMorgan will restrict outside AI agents from accessing its systems while developing tools to protect customers. “We're not going to allow just any outside agent to come in.”

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Today we're publishing the first draft of the Agent Baseline Software Factory Reference Architecture! An opinionated blueprint for securing increasingly autonomous software factories, built with folks across the community. It's open for feedback and contributions! agentbaseline.org/reference-…

Anthropic researchers say small AI models may be months away from being able to self-replicate on IoT devices like smart ovens and off-brand Android TV boxes (Anthropic) (Visit Techmeme dot com for the link and full context!)

Today we are announcing our biggest bet yet on our own silicon. Starting next calendar year, we will scale our Maia family to multi-gigawatt deployments, making it the primary inference system for our own product and services. And we’re introducing Maia 300, which delivers 40% more tokens per watt compared to leading GPU-based systems. We are already deploying Maia 200 across the US, Europe, and Australia, delivering up to 1.7x more tokens per watt across experiences in Teams and Copilot. Our goal is to build on the full-stack efficiency gains we’ve already seen, while continuing to bring the latest innovations from across the ecosystem into our fleet.

BREAKING: 🇫🇷 A major cyberattack has hit supermarket refrigeration systems across France, reportedly causing fresh and frozen food to spoil after hackers remotely manipulated temperature controls. According to BFMTV, the attack began overnight from Sunday into Monday, targeting older versions of refrigeration-control software supplied by Danish company Danfoss. The attackers allegedly exploited the systems’ defrosting function, forcing refrigeration equipment to heat continuously instead of keeping products cold. Temperatures were reportedly set as high as 50°C, destroying entire stocks of food within hours. Several major supermarket chains have been affected, including Intermarché, Super U and E.Leclerc. Metro stores and independent businesses, including butcher shops also have been impacted. Around 150 Intermarché stores are reportedly affected, according to industry sources cited by BFMTV. The full number of affected locations remains unclear. The financial damage is already significant. In Haguenau, Alsace, an Intermarché store reportedly lost its entire frozen-food stock, worth approximately €50,000. A nearby Super U allegedly had to discard both fresh and frozen products, with losses estimated at €220,000. An E.Leclerc store in the same town was also affected, although its losses had not yet been calculated. The combined losses reported at the Intermarché and Super U stores in Haguenau alone amount to around €270,000. Nationwide damage could reach several million euros. Intermarché reportedly confirmed the incident in an internal communication, warning that several stores had suffered losses of frozen products. Coopérative U also acknowledged the attack and established crisis teams to assist affected stores and coordinate with refrigeration specialists. Technical investigations are ongoing, and the full extent of the damage has yet to be established. Authorities and companies are still working to determine the full circumstances of the attack. The identity of the perpetrators has not been confirmed.