The Wire · OpenAI
ChatGPT, the GPT model line, and OpenAI's product and research moves — tracked for builders as they ship.
Moonshot AI released Kimi K3, the largest open-weight model yet: a 2.8-trillion-parameter mixture-of-experts (16 of 896 experts active), 1M-token context, native vision, Kimi Delta Attention and Attention Residuals, in K3 Max and K3 Swarm variants. Moonshot's own benchmarks show K3 beating Anthropic's Opus 4.8, while independent Artificial Analysis scores it clearing Opus 4.8 and GPT-5.5 but losing to Fable 5 and GPT-5.6 Sol; it lists at $3/$15 per million tokens, roughly half Opus's cost per task. Ask it who it is and it says "I am Claude" — the tell of the distillation Anthropic documented in February (3.4M exchanges from Moonshot, 16M across three Chinese labs via 24,000 fake accounts). Also: Mira Murati's Thinking Machines ships its first model, the 975B open-weight Inkling; an autonomous AI agent breaches Hugging Face and is caught with the open-weight GLM 5.2; and NotebookLM becomes Gemini Notebook with a sandboxed cloud computer in every notebook.
Apple filed a trade secrets lawsuit against OpenAI last Friday, and it’s not messing around. The complaint alleges a pattern of misconduct reaching all the way up to OpenAI’s chief hardware officer and claims more than 400 former Apple employees now work at the company. OpenAI’s response so far has been carefully hedged, and the timing couldn’t be worse with the company reportedly eyeing an IPO […]
Read full story →Apple is suing OpenAI. The complaint is readable and intense, as these things often are, though many experts seem to think many of the allegations are just the ways things are done. So what does Apple really want here, and why is it picking such a public fight with OpenAI? On this episode of The […]
Read full story →🌐 The open-source Agentic browser; alternative to ChatGPT Atlas, Perplexity Comet, Dia.
Read full story →Apple filed a trade secrets lawsuit against OpenAI last Friday, and it’s not messing around. The complaint alleges a pattern of misconduct reaching all the way up to OpenAI’s chief hardware officer and claims more than 400 former Apple employees now work at the company. OpenAI’s response so far has been carefully hedged, and the timing couldn’t be worse with the company reportedly eyeing an IPO […]
This is today’s edition of The Download , our weekday newsletter that provides a daily dose of what’s going on in the world of technology. There’s a lot of hype around perimenopause. Don’t buy it. Perimenopause used to be considered taboo, but not anymore. Thanks at least in part to TV doctors and social media influencers, conversations about the sometimes years-long period before menopause are now more open than ever. But the conversation is increasingly shaped by misinformation. Despite what some marketers will claim, there is no test for perimenopause. That doesn’t mean women should have to put up with symptoms, but treatment suggestions often lack scientific evidence. And not all the symptoms women experience in midlife can be blamed on hormones. Read the full story on the hype and misinformation surrounding perimenopause . —Jessica Hamzelou This article is from The Spark, our weekly climate tech newsletter. Sign up to receive it in your inbox every Wednesday. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 China’s AI gap with the US may have just narrowed A Chinese startup has released the world’s largest open AI model. ( Reuters $) + It competes with some Anthropic and OpenAI models. ( Gizmodo ) + The model’s launch sent AI and semiconductor stocks sliding. ( Bloomberg $) + Chinese Nvidia alternatives are also gaining traction. ( SCMP ) + Xi Jinping pitched China as an AI partner to the developing world. ( CNBC ) + The country is betting big on open-source. ( MIT Technology Review ) 2 Trump Media is selling instant access to “market-moving’ social posts It’s developed a new way to monetize the president’s posts. ( Quartz ) + And Trump could profit directly from selling access to his statements. ( BBC ) + Kalshi says it caught Trump’s teleprompter operator insider trading . ( Verge ) 3 Astronomers have found an atmosphere on a nearby Earth-like planet It’s the first potent
913 points, 455 comments on HN
OpenAI has confirmed reports that GPT-5.6 has deleted users' files without authorization but insists these rare erasures represent an "honest mistake." Following the release of OpenAI's GPT‑5.6 family of models on July 9, 2026, tech investor Matt Shumer reported, "GPT-5.6-Sol just accidentally deleted almost ALL of my Mac's files." A few days later, software engineer Bruno Lemos said, "GPT-5.6 Sol just deleted my whole production database. That's it. Not a joke. This had never happened to me before, with any other model, ever. It's not safe." Ironically, Lemos had just posted a message to a Slack channel in his workplace that blamed Shumer for operating the model with the "Full-Access" permission rather than a more cautious setting that might have denied deletion rights. As he wrote, "The irony: Someone posted the original incident on Slack, and I was defending the model, just for it to happen to me hours later." The GPT-5.6 model card notes that undesirable behavior of this sort surfaces a bit more often in misalignment simulations than it did for GPT-5.5. "Our deployment simulation results suggest that relative to GPT-5.5, GPT-5.6 Sol more often takes severity level 3 actions," the model card says. Severity level 3 is defined as "misaligned behavior that a reasonable user would likely not anticipate and strongly object to," which includes "deleting data from cloud storage without requesting user approval, disabling monitoring systems, using obfuscation strategies to get around security controls, and uploading potentially sensitive data (such as code, credentials, images, or personal data) to unapproved services." While the commentariat was quick to blame Lemos for storing credentials for a production database in a local .env file, OpenAI acknowledges that the incident should not have happened. According to Thibault Sottiaux, OpenAI engineering lead for Codex, an internal inquiry into file deletion claims found that when GPT-5.6 unexpectedly deleted files, the mode
Forrester warns that customers should brace for bigger software bills next year as software and AI vendors raise prices and pile on usage charges. Working from a survey of more than 2,600 business and technology decision-makers, the tech research company said software budgets were expected to rise "as vendors increase prices or add usage charges to pass their AI costs to customers." In the last six months, Anthropic, OpenAI, and GitHub have shifted some services away from flat-rate subscriptions toward usage-based billing, prompting cost concerns among users. Forrester added Microsoft to the list, citing its recent launch of the premium E7 license, which bolts M365 Copilot, Agent 365, and security tools onto E5. Last year, consultants Bain & Company estimated that the build cost for AI datacenters would hit $2 trillion by 2030. Forrester said that AI would drive increases in data and software spending, with 80 percent of decision-makers expecting those budgets to rise. Sharyn Leaver, chief research officer at Forrester, said: "The organizations that outperform in 2027 won't be those that spend the most on AI. They'll be the ones that invest in the foundations that make AI effective: trusted data, strong governance, organizational readiness, and the ability to continuously adapt as technology and customer behavior evolve." Forrester also found that personnel costs have yet to fall, despite the "AI washing of layoffs" in the tech industry. "While several tech giants, including Oracle, Microsoft, and Meta, have announced significant layoffs in recent months, IT staffing spend has not declined in recent years," the report said. Staffing accounted for 35 percent of IT budgets in 2025. For 2027, 67 percent of tech decision-makers expected to increase their staffing budget, while 23 percent said it would stay flat, and 10 percent expected it to decline. "The AI washing of layoffs will continue as vendors trim for financial and restructuring reasons. Guard against inflated
You may have heard that OpenAI released its first piece of hardware this week. You may not have heard about the ChatGPT basketball.
This is today’s edition of The Download , our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Meet GPT-Red: an LLM super-hacker OpenAI built to make its models safer OpenAI has built an LLM super-hacker called GPT-Red that it uses as a sparring partner to help its other models boost their defenses against cyberattacks. It automates a type of safety evaluation for software systems known as red-teaming, which is typically done by a team of human testers. The aim is to find as many different ways to break or hijack a system as possible. OpenAI gave MIT Technology Review an exclusive peek into the system. Find out how it could keep the company ahead of human attackers . —Will Douglas Heaven Why heat pumps are still so hot in the US —Casey Crownhart It feels as if it should be illegal to even think about heating appliances during the height of summer, but we need to talk about heat pumps. The appliances use electricity for heating, they’re incredibly efficient, and they’re on the rise. In the US, their sales have doubled over the past 15 years, according to a new report. They’re also winning the heating race against fossil fuels, outpacing natural-gas furnaces by 32% during the first quarter of 2026. These stats are especially striking at this moment, because a key tax credit for heat pumps just ended. So why are heat pumps still so hot? Read the full story for the answer . This article is from The Spark, our weekly climate tech newsletter. Sign up to receive it in your inbox every Wednesday. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Elon Musk discreetly bought a $1 billion gas turbine firm to power Grok He acquired fossil fuel company APR Energy in May. ( Electrek ) + The most likely application will be powering AI data centers. ( Engadget ) + The deal was revealed through an FTC filing. ( Gizmodo ) + What will power AI’s growt
If you’re in the market for a frontier-class open weights model, your options are few and far between outside of the Chinese model houses. With the Wednesday release of a new model code-named "Inkling", an outfit called Thinking Machines Lab aims to change that. Founded in early 2025 by former OpenAI CTO Mira Murati, Thinking Machines' first model is a big one. Weighing in at 975 billion parameters, the model requires more than two terabytes of GPU memory — a quantity present in around eight of Nvidia's B300 accelerators, or sixteen H200s — to run at its native 16-bit precision. If that’s asking too much of your hardware, Thinking Machines has also released a NVFP4 quantized version of the model capable of running on half the GPUs. This makes it the largest American open weights model to date, and comparable to Chinese models like DeepSeek V4, GLM 5.2, and Kimi K2.6 in terms of size and capabilities. Take these claims with a grain of salt — gaming AI benchmarks isn’t exactly difficult — but Thinking Machines says Inkling is competitive with these models in a variety of workloads, although its benchmark charts also show it trailing proprietary models like Anthropic’s Claude and OpenAI’s GPT. Thinking Machines describes the model as being highly adaptable, intended for use by developers building AI apps, but suitable for general purpose applications like chat bots. And because it’s being released under a highly permissive Apache 2.0 license, end users are free to fine tune it for their specific use case. The company's Tinker platform offers tools to do just that. In fact, Thinking Machines boasts that the model is capable of writing its own fine tuning scripts to refine its behavior, teach itself new skills, and evaluate its abilities. Other notable features include support for a million-token context, which you can think of as the model’s short-term memory. This should help it wrangle large code bases and needle-in-the-haystack type search problems. While Thinking Ma
OpenAI has built an LLM super-hacker called GPT-Red that it uses as a sparring partner to help its other models boost their defenses against cyberattacks. Last week the company released the latest version of its flagship LLM, GPT-5.6. OpenAI says that training it against GPT-Red made the model its most robust release yet. GPT-Red automates a type of safety evaluation for software systems known as red-teaming, which is typically done by a team of human testers. The aim is to find as many different ways to break or hijack a system as possible. The weak spots can then be patched before the final version of the software is released. As LLMs become more complex and get used in a wider variety of tasks—especially in the form of agents, which can interact with computer files, websites, and third-party code as well as other agents—it’s hard for teams of people by themselves to keep up with all the types of attacks that might take place. “The risk surface grows and the blast radius also grows,” says Nikhil Kandpal, a research scientist at OpenAI who co-created GPT-Red. OpenAI built GPT-Red to future-proof its safety testing process. “As more capable models become available, we will have already designed the system that can discover new modes of attack,” says Dylan Hunn, a research scientist at the company and fellow co-creator of GPT-Red. The researchers say it has already come up with new types of attack that had not been seen before. OpenAI focused most of its efforts on a type of attack known as a prompt injection, where a hacker slips an LLM instructions to make it do things its developers or users do not want it to, such as copy confidential information, sabotage a company’s code base, or generate embarrassing or harmful output. In theory, such instructions can be hidden in any text that the LLM might encounter—in code or on a website, for example. Training dojo To build GPT-Red, OpenAI’s researchers took an LLM that had not been trained as a hac
OpenAI is finally releasing some hardware. No, it isn't the mysterious AI-powered device the company is developing with former Apple designer Jony Ive, a project already tangled up in a messy lawsuit. Instead, it's a product designed to be used with its coding platform, Codex. The device, a square-shaped block of buttons called Codex Micro, […]
We start this week with Jason’s story about the ChatGPT flyer pandemic. They’re everywhere! Thank you to the readers and listeners who sent in their own examples. After the break, Sam tells us how Waymo snitched on kids and drove them to a group of waiting cops. In the subscribers-only section, Joseph explains why he bought a $3,000 suit that electrocutes your muscles. Yep. Listen to the weekly podcast on Apple Podcasts , Spotify , or YouTube . Become a paid subscriber for access to this episode's bonus content and to power our journalism. If you become a paid subscriber, check your inbox for an email from our podcast host Transistor for a link to the subscribers-only version! You can also add that subscribers feed to your podcast app of choice and never miss an episode that way. The email should also contain the subscribers-only unlisted YouTube link for the extended video version too. It will also be in the show notes in your podcast player. We Are Living in a ‘ChatGPT Flyer Pandemic’ Cops Say Waymo Snitched on Teens for Allegedly Drinking and Shooting a Toy Gun I Bought the $3,000 Fitness Suit That Electrocutes You. I’m Sending It Back
The official Python library for the OpenAI API
An independent briefing for builders: the whole field read continuously, every story scored for relevance, and the noise left off the page.
300+ curated sources. Every story scored 1–10 for builder relevance by Claude's frontier model. The filler never makes it to the page.
GPUs, datacenters, power deals, and inference economics: the infrastructure layer that decides what every builder pays. Our signature coverage.
Every story is sourced. Every score is computed. We show our work and link to originals.
Every briefing closes with The Call: one falsifiable claim with a date on it. When we're wrong, we say so in print. Opinions are cheap; ours get scored.