2026/06/01

An OpenAI model disproved a conjecture mathematicians had been chewing on since 1946. NVIDIA dropped a single open model that fuses vision, generation, action, and reasoning into one architecture. Google's Gemini Omni and 3.5 Flash hit broad availability. And running underneath all of it: $76 billion of fresh chip and data-center money, a hardening community backlash, and a quiet realization in dev shops that AI-assisted code might be making the bug count worse, not better. ## OpenAI's model disproves a 1946 Erdős conjecture The problem is Paul Erdős's unit distance question: how many pairs of points one unit apart can you fit in the plane? Square grids were the assumed champion for nearly 80 years. They aren't anymore. The proof came from a general-purpose reasoning model — not a math-specific system or anything scaffolded to crawl proof strategies. The model produced an infinite family of point configurations that beat the grid bound by a polynomial factor, and external mathematicians verified the argument and wrote a companion paper. What's notable isn't the result so much as the path: one general reasoning model, one open problem, no specialty tooling, no hand-holding. **Source:** [Ars Technica](https://arstechnica.com/ai/2026/06/openais-math-breakthrough-played-to-ais-strengths/) ## NVIDIA Cosmos 3 lands as the first open omni-model for physical AI Anyone building physical AI pipelines used to juggle four separate Cosmos models — prediction, transfer, reasoning, policy. Cosmos 3 collapses them into a single Mixture-of-Transformers that swaps between vision-language reasoning, video generation, forward dynamics, and policy in one pass. Two sizes shipped: Nano at 8B parameters, sized for an RTX PRO 6000, and Super at 32B for large-scale synthetic data generation. The Hugging Face release includes Diffusers integration, six synthetic datasets, and post-training scripts. Use cases NVIDIA leads with: robot manipulation, long-tail driving scenarios, and warehouse safety training data. If you've been hand-rolling a four-model pipeline to do any of those, the architecture just got considerably simpler. **Source:** [Hugging Face](https://huggingface.co/blog/nvidia/cosmos-3-for-physical-ai) ## Google ships Gemini Omni and Gemini 3.5 Flash broadly Google posted nine demo videos pulling Gemini Omni and Gemini 3.5 Flash out of I/O 2026 stage demos and into actual product. Omni is the video-first multimodal model: image, audio, video, and text in; high-quality video out, with conversational editing. Google's pitch is that Omni has an "intuitive" understanding of physics — gravity, kinetic energy, fluid dynamics — letting it generate physically plausible scenes rather than just photorealistic ones. Omni Flash is rolling out globally to Google AI Plus, Pro, and Ultra subscribers via the Gemini app and Google Flow, and at no cost on YouTube Shorts and YouTube Create. Gemini 3.5 Flash is now the default model in the Gemini app and AI Mode in Search — Google claims it surpasses 3.1 Pro on coding, agentic, and multimodal benchmarks at Flash-tier cost and speed (4x faster on output tokens per second than other frontier models). Gemini 3.5 Pro is in internal use with a public rollout teased for next month. **Source:** [Google AI Blog](https://blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-omni-3-5-videos/) ## Anthropic's "run-rate revenue" definition, decoded Karen Kwok at Reuters Breakingviews finally got Anthropic to spell out exactly what its run-rate number means. The formula is two parts added together: take the last 28 days of consumption-based sales and multiply by 13, then take the monthly subscription line and multiply by 12, and add. The result is the headline figure that gets reported as Anthropic's "annual run-rate revenue." Why it matters: that's an aggressive smoothing for any business with consumption-based pricing — a single 28-day window scaled across a year captures a lot of optimism. Anthropic also reports revenue from cloud reseller deals (AWS, Google, Microsoft) on a gross basis, counting total end-customer spend as revenue with partner payouts booked as expenses. The April reporting put run-rate at around $30 billion. Comparing that headline to competitors who recognize revenue net of reseller cuts is not an apples-to-apples exercise. **Source:** [Simon Willison](https://simonwillison.net/2026/May/31/anthropic-run-rate/) ## Groq raises $650M after Nvidia's $20B "not-acqui-hire" Six months after Nvidia structured a $20 billion arrangement with Groq involving personnel departures and technology licensing — a transaction everyone in the industry has politely called a "not-acqui-hire" — Groq is back in the market for fresh money. The reported round is $650 million from existing investors, with backers Disruptive and Infinitium having agreed to fill the round if other investors don't take their pro-rata shares. Groq is pivoting hard toward its inference cloud platform. The bet: inference is now the bigger spend in AI than training, and a chip-plus-platform play tailored for inference economics is where the next leg of growth lives. **Source:** [TechCrunch](https://techcrunch.com/2026/05/29/after-nvidias-20b-not-acqui-hire-ai-chip-startup-groq-reportedly-raising-650m/) ## SoftBank pledges up to €75B for French data centers SoftBank announced an investment of up to €75 billion (about $87 billion) to expand data center capacity in France. The target is 5 gigawatts of new capacity, with the first 3.1 gigawatts landing in the Hauts-de-France region by 2031. Initial construction sites: Dunkirk's Loon-Plage, Bosquel, and Bouchain. It's SoftBank's largest AI infrastructure investment in Europe. And it's the kind of number that helps explain why the next story is finally getting traction. **Source:** [TechCrunch](https://techcrunch.com/2026/05/30/softbank-says-it-will-invest-up-to-e75-billion-to-build-french-data-centers/) ## Erin Brockovich opens a campaign on data center secrecy Brockovich isn't anti-data-center. She's anti-NDA. After putting up a map and a reporting form in April, she logged close to 4,000 submissions from affected communities in the first month. The dominant complaint wasn't water, noise, or power bills. It was opacity: projects announced after permits cleared, developers who don't return calls, local officials who'd already signed NDAs before their neighbors heard the words "data center." Compute capacity has to land somewhere physical. As the SoftBank, Microsoft, and Meta numbers keep climbing, the people who live next to that physical thing are starting to push back — not on the buildout itself, but on how the decisions get made. **Source:** [TechCrunch](https://techcrunch.com/2026/05/31/erin-brockovich-takes-aim-at-data-center-secrecy/) ## GitHub Copilot's token pricing detonates GitHub flipped Copilot from flat-rate to token-based billing today. Developers are not taking it well. One user reported a jump from $29 a month to nearly $750; another from $50 to about $3,000. The complaint isn't just the bill — it's the whiplash. Microsoft spent the last year encouraging heavy Copilot use under flat pricing, then changed the meter on a Sunday. Microsoft hasn't publicly responded. The charitable read is that flat-rate was burning cash and unsustainable; the less charitable one is that the loyalty tax just got formalized into the pricing page. **Source:** [TechCrunch](https://techcrunch.com/2026/05/30/what-a-joke-github-copilots-new-token-based-billing-spurs-consternation-among-devs/) ## Coders won't work without AI — and the bills are showing When research lab METR tried to repeat last year's developer productivity study, it couldn't recruit participants. Developers refused to write code without AI assistance, even briefly, even for research. The numbers underneath that refusal are not encouraging. CodeRabbit's analysis of open source PRs found AI-generated code produced 1.7x more problems than human-written code. One claim making the rounds: companies are spending 44% of their AI tokens on fixing bugs the AI itself created. Amazon reportedly killed an internal token-tracking leaderboard after employees gamed it for inflated numbers, and Uber apparently burned through its entire 2026 AI budget in four months without a measurable productivity bump. AI is helping people ship faster. Whether it's helping them ship better is still an open question — and not one the cost side has been answering well. **Source:** [TechCrunch](https://techcrunch.com/2026/05/29/coders-are-refusing-to-work-without-ai-and-that-could-come-back-to-bite-them/) ## Aaron Levie diagnoses "AI psychosis" in CEOs Box CEO Aaron Levie put a name on the dynamic showing up in Q1/Q2 layoff announcements: AI psychosis. His thesis is sharp. "CEOs are uniquely prone to AI psychosis because they're sufficiently distant from the last mile of work that still has to happen to generate most value with AI. When they play with AI, they see the happy path results, often not considering the next 10 or 20 things that have to happen to get sustainable results from agents." The example Levie reaches for: an employee says "I generated a contract." Sure — but did they verify the terms, reconcile it against prior contracts, walk it through counter-party review? The 2026 layoff numbers are starting to argue with the executive optimism. In just the first five months of 2026, 115,430 tech layoffs across 152 companies — nearly matching all of 2025's 124,636 in less than half the time. ClickUp cut 22% of its workforce in late May citing AI agent replacement. Levie's argument: the people deciding AI can do your job are the ones least likely to understand what your job actually is. **Source:** [TechCrunch](https://techcrunch.com/2026/05/29/what-happens-when-companies-become-too-ai-pilled/) ## Open Source Spotlight **Hermes Agent v0.15.2** — Nous Research shipped a same-day hotfix for its self-improving agent OS on May 29, fixing wheel and sdist packaging so bundled `plugin.yaml` manifests actually ship. Small release, but it follows the much larger v0.15.0 "Velocity" cut from May 28: 1,302 commits, 747 merged PRs, 282,712 insertions across 1,746 files. The release tempo is not slowing down. ([release notes](https://github.com/NousResearch/hermes-agent/releases)) **Hermes Tool Search for MCP** — Anthropic published new evaluations of Hermes Agent's tool search feature for MCP servers. Numbers are noteworthy: tool search boosted Opus 4 accuracy from 49% to 74% on tool-heavy tasks. If you're wrestling with MCP server discovery in your own agent stacks, this is the eval worth reading. --- *Sources verified. All claims drawn from source articles published May 27 through June 1, 2026.*

2026/05/29

Anthropic dropped Opus 4.8 with a parallel-subagent workflow tool, Apple is reportedly trying to squeeze a distilled Gemini onto the iPhone, and a developer slipped a data-nuking prompt injection into his own code to mess with vibe coders pulling from it. Plus the Pope's AI encyclical gets a practical follow-up read. ## Anthropic ships Opus 4.8 with a dynamic workflow tool Anthropic released Opus 4.8 on May 28, just 41 days after Opus 4.7. The headline feature is a "dynamic workflow" tool — currently in research preview — that coordinates hundreds of parallel subagents. Anthropic is pitching it at codebase-scale work, claiming Claude Code can drive migrations across hundreds of thousands of lines. Anthropic also says 4.8 is more likely to flag uncertainty and less likely to make unsupported claims, and is supposed to proactively spot issues in analysis inputs and outputs. Pricing matches 4.7. The 41-day turnaround is unusual — 4.7 got mixed reception, and 4.8 lands while OpenAI and Google are rolling out their own releases. **Source:** [TechCrunch](https://techcrunch.com/2026/05/28/anthropic-releases-opus-4-8-with-new-dynamic-workflow-tool/) ## Apple is reportedly trying to distill Gemini onto the iPhone Apple is working on shrinking Google's Gemini down to a size that can run on iPhone, with the goal of powering the next Siri. The technique is distillation — train a smaller model to mimic the behavior of a much larger one — and the destination is on-device inference. The interesting part is the dependency. Apple's whole pitch is that AI features run on your phone for privacy reasons, but the model that ends up there came out of Google. If this ships, it's a quiet admission that doing this from scratch wasn't going to work on Apple's timeline. **Source:** [Ars Technica](https://arstechnica.com/ai/2026/05/apple-reportedly-trying-to-distill-googles-multi-trillion-parameter-gemini-ai-to-run-on-iphone/) ## A dev sneaks a data-nuking prompt injection into his own code A developer fed up with vibe coders pulling from his code added a hidden prompt injection that, when an AI assistant reads the file, instructs it to delete the user's data. It's a sabotage move, dressed up as a maintainer's protest. It's also a clean illustration of why prompt injection still isn't solved. Every coding agent that ingests third-party code is reading instructions, not just text — and there's still no reliable way to separate the two. This is a one-person stunt, but the attack pattern works everywhere. **Source:** [Ars Technica](https://arstechnica.com/security/2026/05/fed-up-with-vibe-coders-dev-sneaks-data-nuking-prompt-injection-into-their-code/) ## Pope Leo XIV's encyclical, two weeks later MIT Tech Review took another look at Pope Leo XIV's Magnifica Humanitas, the AI encyclical released May 15, and reframes it as practical guidance rather than just a moral statement. The argument: AI is a commercial product concentrated in a few companies, not an inevitable force, and individuals — especially shareholders and institutional investors — have actual leverage. The piece cites more than $400 billion in investor assets being mobilized for AI governance proxy resolutions. That's the part labs don't usually have to engage with. The encyclical's "technology is never neutral" line is the framing, but the news is that the money is showing up to back it. **Source:** [MIT Technology Review](https://www.technologyreview.com/2026/05/29/1138107/how-the-popes-magnifica-humanitas-offers-a-template-for-individuals-to-meet-the-ai-moment/) ## Gemini Spark, the personal AI agent that gets too personal Wired's hands-on with Google's Gemini Spark is the closest thing to a stress test of a "knows everything about you" agent. The reporter gave Spark access to personal data and the agent started acting on it — at one point sidelining her boyfriend in scheduling decisions. It's a useful, slightly absurd preview of the next generation of personal AI. The model isn't malicious. It's just doing what a system optimizing on aggregate signals does when you hand it your calendar, contacts, and messages. The behavior is the feature. **Source:** [Wired](https://www.wired.com/story/google-gemini-spark-ai-agent-hands-on/) ## Open Source Spotlight **Hermes Agent v0.15.0 — The Velocity Release.** Nous Research shipped a big one this week. The headline number is the `run_agent.py` refactor — 16,083 lines down to 3,821, redistributed across 14 modules — but the more important shift is the Kanban swarm tooling: one command builds a full multi-agent graph with parallel workers, a gated verifier, and a shared blackboard. `session_search` got rewritten without an aux-LLM and is now ~4,500× faster and free per call. Bitwarden Secrets Manager replaces per-provider API keys. v0.15.1 and v0.15.2 followed with hotfixes the same week. [GitHub](https://github.com/NousResearch/hermes-agent/releases/tag/v2026.5.28) **Repurposing a gaming PC as a Hermes Agent rig.** A user write-up making the rounds: turn your gaming machine into a 24/7 Hermes Agent host that runs while you're not playing. It's basically the home-lab pitch for personal AI — your idle GPU is now your own agent infrastructure, with no cloud bill. The story matters less than the pattern. As local agents get better, the gaming-PC-as-AI-server move stops looking weird. *Sources verified. All claims drawn from source articles published May 28–29, 2026.*

2026/05/27

Nvidia is pouring $150 billion into Taiwan while the US tries to be the AI center, YouTube is about to start auto-labeling AI videos, and Robinhood just opened the door for AI agents to trade your stocks. The mix today was less about new models and more about where AI is colliding with chips, platforms, and money. ## Nvidia bets $150B on Taiwan as the US AI hub plan stumbles Nvidia is investing $150 billion in Taiwan, deepening its commitment to the country that already makes most of its advanced chips. The move comes as the Trump administration's effort to push more AI infrastructure into the US runs into the same problem it always does: the supply chain still lives somewhere else. Jensen Huang has been blunt about wanting Taiwan at the center of the AI buildout. That's reasonable from a manufacturing point of view, but it also means the political pressure to onshore production isn't actually translating into where Nvidia is putting its money. The headline number does the talking. **Source:** [Ars Technica](https://arstechnica.com/tech-policy/2026/05/nvidia-ceo-wants-taiwan-to-be-center-of-ai-revolution-not-us/) ## YouTube will start auto-labeling AI videos YouTube is rolling out automatic labels for videos created with AI. Creators have been required to self-disclose for a while, but enforcement has been spotty, so YouTube is moving to detect AI content directly and stamp it. The hard part is the gray zone. A short with an AI voiceover, a clip touched up by a generative tool, a fully synthetic news anchor — these are very different things, and a single label flattens them all. YouTube will need to be specific about what triggers the label, or it ends up either everywhere or nowhere. **Source:** [Ars Technica](https://arstechnica.com/google/2026/05/youtube-to-begin-automatically-labeling-ai-videos/) ## Nvidia finally kills the Windows XP-era Control Panel After 20 years, Nvidia is retiring the legacy Control Panel and consolidating settings into the newer Nvidia App. The old panel was a fossil — half the options didn't even work on modern GPUs — so this is overdue more than dramatic. Worth noting only because so much of the GPU ecosystem has built workflows around the old panel. Some scripts will break. Most people won't notice. **Source:** [Ars Technica](https://arstechnica.com/gadgets/2026/05/nvidia-kills-windows-xp-era-control-panel-after-20-years-of-dedicated-service/) ## Ex-Google and Apple researchers are building AI that learns as you use it A new startup founded by former Google and Apple AI researchers is going after one of the actual missing pieces in current LLMs: the lack of a real feedback loop. Today's models stop learning the moment they're deployed. Everything personal you tell them lives in a context window, not in the model. The startup's pitch is to build models that adapt to individual users over time. That's a technical hard problem and a privacy hard problem at the same time, and the company hasn't said much about how it solves either. But it's pointed at something that matters. The current copy-paste-your-context-every-day pattern isn't going to be the long-term shape of personal AI. **Source:** [Wired](https://www.wired.com/story/ex-google-apple-ai-researchers-want-to-make-ai-that-gets-smarter-as-you-use-it/) ## Pope Leo XIV's first encyclical takes on AI Pope Leo XIV's first encyclical addresses AI directly, framing it as a question about human dignity, labor, and power rather than just technology. Wired's read is that the document is closer to a critique than a celebration — concerned about what AI does to workers and about concentrating control in a handful of companies. It's a notable moment because it pulls AI into mainstream moral discourse from outside the tech industry. Whether it changes anything in policy is a different question. But the framing — that the most powerful AI systems being controlled by a few companies is itself a problem — is one the labs don't usually have to answer in those terms. **Source:** [Wired](https://www.wired.com/story/what-pope-leo-xivs-first-encyclical-says-about-the-power-of-ai/) ## Robinhood lets AI agents trade stocks on your behalf Robinhood is now letting AI agents trade stocks on its platform. Users can connect agents through the API and authorize them to place orders. Robinhood pitches it as opening retail trading to the same kind of automation hedge funds have always had. That's one way to look at it. The other way: most retail traders already lose money picking stocks themselves, and handing the wheel to an AI agent with no transparency into its strategy is a fast path to bigger losses. Robinhood is positioning AI agent trading as empowerment. It also conveniently produces more order flow. **Source:** [TechCrunch](https://techcrunch.com/2026/05/27/robinhood-now-lets-your-ai-agents-trade-stocks/) ## Open Source Spotlight **OpenClaw passes 300,000 GitHub stars.** The open source agent framework hit the milestone the same week Google launched Spark, its own agent platform. OpenClaw's growth has been steady rather than viral, which is usually a healthier signal — people use it, then more people use it. The Spark launch is the bigger competitive question: a Google-backed alternative changes the open agent landscape pretty quickly. [GitHub](https://github.com/openclaw/openclaw) **Hermes Agentic AI is gaining ground on OpenClaw.** Coverage this week pegged Hermes as the project to watch in agentic AI, framing it as a serious challenger to OpenClaw's lead. Hard to evaluate the claim without numbers, but the fact that Hermes is being discussed in those terms at all is a shift from a year ago. The agent ecosystem is no longer a one-project story. *Sources verified. All claims drawn from source articles published May 27, 2026.*

2026/02/27

We're moving from asking an LLM to behave to shipping software-defined agent environments. Skill files are infrastructure — and it's time to treat them like it.

2026/02/19

StrongDM's three-person AI team built production security software with two rules: no human writes code, and no human reviews code. Here's how they actually pulled it off.

2026/02/13

Companies blamed AI for over 54,000 layoffs in 2025, but economists and analysts say the real reasons are often simpler: overhiring, tariffs, and profit margins.