The Wire · OpenAI
ChatGPT, the GPT model line, and OpenAI's product and research moves — tracked for builders as they ship.
OpenAI cut GPT-5.6 Luna API prices by 80% to $0.20 per million input tokens and $1.20 per million output, while Terra fell 20% to $2 and $12. Fast mode gives Sol up to 2.5 times Standard speed at twice the price. OpenAI says Sol-assisted kernel work lowered serving cost by 20% and improved token-generation efficiency by more than 15%, while Luna delivers year-old frontier performance at roughly six cents per task-dollar and nearly nine times the speed. The edition connects cheaper models to Amazon's reported $1.8m, 860%-over-budget coding task, Gemini Robotics 2 whole-body control, Nscale's Anyscale acquisition and Okta's roughly $200m Permiso deal.
135 points, 98 comments on HN
Read full story →The UK’s AI Security Institute has observed AI models performing what it calls “unsanctioned action” 19 times during security tests. The Institute (AISI) revealed the incidents in a Tuesday post and technical report that details tests it conducted to see if AI models can solve a cyber security challenge. “We ran this challenge 122 times across several models,” the post states, before revealing that "in 10 of those runs, an AI agent took autonomous, unsanctioned action on the live internet, targeting real people and organisations.” GitHub was the target of the tests. The org found 19 unsanctioned actions in all, 15 of them conducted by Anthropic's Mythos 5, and the other pair perpetrated by OpenAI's GPT-5.6-Sol. “In the most serious case, an agent tried to insert malicious code into an open-source project, the post states. “In an attempt to get the code approved, the agent engaged in social engineering – creating fake online identities and using them to pressure the project's maintainer to approve the code.” Thankfully, a human maintainer “caught and refused to approve the malicious code.” Other actions AI took during the test included: Attempts to deceive and target real people, by contacting them directly and “sending messages and files through an online file-transfer service to persuade them, or their own AI coding tools, to run malicious code. Some messages carried harmful payloads, and some were attempts at social engineering; targeted at real people – something we’ve never previously observed.” Attempts to plant and prompt-inject malicious code. The agent tried to insert malicious instructions where it reasoned that other automated AI systems might pick them up and execute them. Collaboration between independent agents being assessed simultaneously. One agent left public messages on GitHub offering collaboration with other agents working on the same challenge. It also provided instructions to reuse accounts and artefacts it had left behind, which were discovere
Read full story →AMD has posted strong second quarter results and forecast even better future financials once its Helios rack systems and Instinct MI400-series GPUs reach buyers. “In data center AI, the growing number and scale of Helios and MI450-series deployments position the [datacenter] business for significant growth in the second half of the year, with growth accelerating in 2027,” CEO Lisa Su told investors on Tuesday during the chip design company's Q2 earnings call. “We now expect data center segment revenue to more than double year over year in 2027,” she added. Yet, despite reporting Q2 profits surging 163 percent year-over-year on revenues of $11.5 billion, and several multi-gigawatts worth of Helios commitments from the likes of OpenAI, Anthropic, and Meta in the bag, Wall Street isn’t buying it. The company's share plunged 10.5 percent after its results announcement, before settling 8.7 percent below opening price at the time of publication. The apparent cause for concern: AMD's growing exposure to the AI bubble. Much of the company's growth potential across both CPUs and GPUs is tied to AI adoption by a handful of companies that are yet to prove they can operate profitably. On Tuesday's earnings call, Su attempted to assuage investor fears, but in the same breath she said the quiet part out loud. “When we talked about the large frontier-model companies, OpenAI, Anthropic, Meta, they will be consuming through a number of CSPs,” Su said. “There are additional customers or lots of customers who are interested in Helios at, let's call it, a more regular scale than gigawatt scale.” In other words, while AMD can sell plenty of GPUs, most are sold to a handful of customers. And while other entities have AMD on their shopping lists, they don't buy in bulk. Microsoft, another flagship customer for AMD's latest generation of AI picks and shoves, serves both OpenAI and Anthropic, while Meta is reportedly looking to enter the GPU cloud biz itself. Despite this, AMD remains optim
Read full story →<p>I released <a href="https://llm.datasette.io/en/stable/changelog.html#v0-32">LLM 0.32</a> this morning, the most significant new version of LLM since the initial launch of the project. The new version includes support for visible reasoning traces, server-side provider tools, redesigned content-addressable SQLite logs, new models, and new features enabled by the OpenAI Responses API. I also released a new version of the <a href="https://github.com/simonw/llm-anthropic">llm-anthropic plugin</a> with substantial updates of its own.</p> <h4 id="headline-features-for-llm-cli-users">Headline features for LLM CLI users</h4> <p>Running LLM against reasoning models now <strong>displays their reasoning traces</strong> to standard error, so you can see what they are "thinking" without that information being included in the standard output that you might pipe to another tool. Add <code>-R/--hide-reasoning</code> to turn this off.</p> <p><img src="https://static.simonwillison.net/static/2026/best-pelicans.gif" alt="Running llm "think about the best thing about pelicans" in the macOS terminal window - grey text outputs saying Exploring pelican qualities, then after a paragraph of that a white paragraph of text comes out saying: The best thing about pelicans is their wonderfully oversized, practical design: that enormous bill and pouch look comical, but they make pelicans remarkably skilled fishers. Even better, many species cooperate—working together to herd fish before scooping them up. They’re a great mix of goofy, graceful, and surprisingly clever." style="max-width: 100%;" /></p> <p>LLM includes support out-of-the-box for the <strong>GPT-5.6 model family</strong>, and the new default model used with <code>llm "prompt"</code> is now the inexpensive but capable <strong>GPT-5.6 Luna</strong>.</p> <p>LLM calls can now use <strong>server-side tools</strong> from various providers. OpenAI provide <a href="https://llm.datasette.io/en/stable/openai-models.html#code-inter
In the face of an epidemic of AI-enabled cheating and research suggesting its products hamper learning, OpenAI is doing the sensible thing and pushing more AI on students and teachers. Wait, did I say sensible? My mistake. The House of Altman announced a trio of new education-focused offerings on Tuesday: one for K-12 teachers, another for college educators, and a third for college students. The new plugins, the company explained, will help students and educators make more use of ChatGPT’s agentic capabilities for both studying and teaching. The new features are available through ChatGPT Edu, an institutionally licensed suite for higher education, and ChatGPT for Teachers, a free resource available to verified US K–12 educators and school districts. The new offerings, says OpenAI, build on its educational AI philosophy that “AI should support learning, not shortcut it, and the best learning experiences keep educators and students in control.” Plenty of educators might disagree. Cheating with AI has become a sad norm in schools around the world, and the US is no exception. Many young people admit to using AI to cheat on school assignments, and college students have been caught doing it, too. Mexico's largest university, the National Autonomous University of Mexico, last week suspended enrollment for incoming students after suspected widespread cheating in its admissions exams. The university also decided this week to require about 58,000 applicants who qualified in the remote entrance exam to take an in-person proctored control exam after scores surged during its first remotely administered admissions test. As for how teachers relate to AI in the classroom, a 2025 study from the Center for Democracy and Technology suggests it’s going to take more than some new OpenAI software to help teachers feel more comfortable. CDT said last year that K-12 teachers widely complained of not being given the necessary resources to understand how to integrate AI into schools, or how
Editor’s note: I’m excited to welcome Shlok to our guest post roster ! You may know Shlok from his excellent explorations (as an outsider — for an insider perspective see our podcast with OpenAI’s Akshay Nathan . Already one of our most popular episodes of the year!) of leading AI Lab memory systems , which he gave an excellent AIE talk on . We’ve been covering OpenAI’s research and deployment of agents to all of humanity since Plugins 2023 and Devday 2024 and Codex 2025 , and now ChatGPT Work in 2026 seems the penultimate stage of the long journey. Let’s dive in! On July 9th, OpenAI released ChatGPT Work , their agent product for knowledge work. It was, by any measure, a busy launch: three new models across fourteen configurations , a consolidation of the ChatGPT and Codex desktop apps, and cloud agents brought to the mainstream in their most accessible form yet. Three weeks in, Work (along with Codex) has reportedly crossed 10 million users . Editor’s note: ChatGPT estimated to cross 1B MAU in June and 1B WAU this month . Chat and Work currently sit side by side as separate modes inside ChatGPT, but Greg Brockman has confirmed that they will merge by the end of the year . Work, then, is not just a niche product for power users, but a preview of how ChatGPT’s billion weekly users will soon use the app. That’s why people inside and outside OpenAI are so excited about it, and why it deserves a closer look. Work in its current form takes some decoding. It’s an amalgamation of ChatGPT (in chat form), Codex the app, Codex the harness, Codex the original cloud agent, ChatGPT agent, Atlas, OpenClaw, and more. The product lineup around it is confusing. And the web and mobile versions diverge from the desktop one (unless you run it in cloud mode?!). So I spent the past few days trying to unpack it: what Work is, where it fits in OpenAI’s lineup, the many interesting choices in its design, the tensions underneath, and where I think it’s headed. Most of what follows comes fro
The brand trip is a right of passage for influencers. It's a mark of legitimacy that a sponsor wants to invite them on an all-expenses-paid vacation, often with luxurious freebies and activities. Trips can also spur hard feelings from uninvited influencers, trigger criticism from the public, and project a certain frivolousness. Usually it is fast […]
Microsoft has introduced new limits to how much its engineers can spend on AI tools at work and told employees that maximizing AI use internally is not the company’s goal. This makes Microsoft one of the last major companies to rein in its employees’ expensive AI use. Scaling back maximalist AI use, or what some companies have called “ tokenmaxxing ,” is a trend we’ve covered in recent months as the price for using AI has increased while not always delivering commensurate productivity gains . “As we accelerate our use of GitHub Copilot to deliver on our goals, we all need to be aware of how we consume tokens,” Jay Parikh, an executive vice president at Microsoft said in an email to Microsoft employees. GitHub is owned by Microsoft, and GitHub Copilot is an AI coding tool. “Tokenmaxxing is not what we are optimizing for. I want all of us focused on maximizing outcomes that move the needle for our customers and our business.” “As such, we are updating our internal guidance and managing token spend with the same discipline we apply to every other critical resource,” Parikh said in the email. Parikh’s email says that in an effort to “get greater value from our token investment” Microsoft is making OpenAI GPT-5.6, which is cheaper to use than other models, the default model for internal use. His email also links to updated internal Copilot guidelines stating that, as of July 2026, Microsoft divisions will have an “AI token budget target,” and that employees can track their individual AI spending. “While there is no target spend value being shared at this time. The data shows that many engineers spend in the range of hundreds of dollars a month to a few thousand dollars in tokens,” the guidelines say. They also say that some decisions may place further restrictions as they monitor spend. As Parikh’s email notes, the change in policy about AI spend wasn’t introduced because Microsoft is tight on cash. To the contrary, its latest earnings report shows the company revenue, o
OpenAI has accused Apple of waging a “careless, aggressive and oddly personal lawsuit” in a blog post rebutting the iPhone maker’s claims that the AI start-up stole top-secret information. “We do not have, nor want, any of their trade secrets,” the ChatGPT maker wrote on Monday evening, accusing Apple of “making vague accusations” and “trying to change their narrative.” The post marks the latest escalation in a dispute that began last month when Apple filed a lawsuit claiming OpenAI had stolen hardware designs as it planned to launch its own AI-focused consumer devices. Read full article Comments
<figure><div><img src="https://imgproxy.divecdn.com/6XY2OXmAksFSxuJVFRAuxVSE7tVgjglv55Q9S8JYSMo/g:ce/rs:fill:1600:900:1/Z3M6Ly9kaXZlc2l0ZS1zdG9yYWdlL2RpdmVpbWFnZS9DaHJpc19Xb21hY2suanBn.webp"/></div></figure><p>Recently announced projects include a 3.2-GW OpenAI data center near Savannah, Georgia. The contract includes 1 GW of “flexible demand response” for peak shaving — the first such flexibility provision the company has codified with a data center customer.</p>
OpenAI’s first-ever influencer brand trip is sparking online backlash as tensions over the use of AI continue.
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here . Humanoid robots usually elicit more cringe than awe: They stumble , kick children , and despite advances are still worse at using their hands than my toddler. It’s a nascent industry, and such robots are more commonly seen in viral videos than real workplaces or homes. It was a surprise, then, when last week the Federal Trade Commission issued a sweeping ban on foreign imports of advanced robots, including humanoids, quadrupeds, and wheeled robots. The decision, made by an increasingly partisan and Trump-aligned FTC, cites two reasons. One is that foreign-made humanoids will collect so much data—in homes but also potentially at sensitive facilities—that they’d pose a threat to national security. The second is that US robotics companies need protection from Chinese competition to create a more robust and secure domestic supply chain. On its face, it’s a strategy to align political and industry interests that is much older than the Trump administration. Whenever China has gotten good at offering cheap versions of strategic technologies like solar panels, electric vehicles, and drones, the US government has tried to stop it from flooding the market by using tariffs or rules on how government agencies purchase the tech. Such moves are always followed by debates about whether the trade-offs—particularly higher prices for consumers—are worth the benefits. But robotics is now best seen as another piece of the AI industry—in many ways its cutting edge. And the Trump administration is taking an increasingly aggressive approach to protecting the US AI industry, reportedly considering a ban on open-source Chinese models that often rival those from OpenAI and Anthropic while costing far less. Such a move would block businesses from realizing an estimated $25 billion in annual savings. The ban on humanoids, then, should be understood no
House spending records show OpenAI's ChatGPT dominates paid AI use on Capitol Hill, with congressional offices relying on the chatbot to draft memos, summarize legislation, and assist constituent communications.
We've entered a new phase of the AI industry's development, with all the major players heavily cutting costs and boosting the capabilities of their entry-level models in order to compete with new models from China, like Moonshot's Kimi K3 and DeepSeek's V4 Flash. OpenAI did so most recently, cutting the price of its base frontier model, ChatGPT 5.6 Luna, by 80% per million tokens, and its mid-range 5.6 Terra by 20%. This comes just over a week after Google introduced its more-affordable Gemini 3.6 Flash and 3.5 Flash-Lite models. Anthropic hasn't cut prices, but replaced its most-affordable Opus 4.8 model with a more capable Claude 5.0 at the same price point. Intelligence is getting more affordable thanks to increased global competition, but this can come at the cost of margin for these major companies. This follows months of major AI businesses announcing cuts and limits on their use of the technology , even by major AI boosters like Elon Musk's xAI. Despite more workers using AI than ever before, productivity gains are reported to have been less than ideal . Intensifying competition The story of Chinese and American AI development efforts has been somewhat emblematic of the countries' historic strengths. While American firms burn through enormous amounts of money to push frontier technologies, Chinese developers have leveraged their industrial base to develop models that are cheaper, leaner, and almost as good at the top end. DeepSeek gave Western AI developers a shock in 2025, and Kimi K3 did much the same in 2026. Alone, these events would cause concern for companies like OpenAI, Google, and Anthropic. Still, after months of companies that use AI heavily complaining about skyrocketing token costs , the news of an almost-as-good model at a much lower price really made a splash. Now, the big AI developers can't just compete by throwing more parameters and training data at the problem. Now they're having to really compete on price, and to do it, OpenAI has massive
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. Here’s why AI agents lie and cheat to reach their goals When two OpenAI models hacked into Hugging Face last month, they weren’t trying to make money or commit sabotage—they were just looking for answers to a test question. According to OpenAI, the models decided to solve a cybersecurity exercise by hacking out of the environment in which OpenAI had attempted to contain them and into Hugging Face’s databases, where—they reasoned—the correct answer to the problem might be stored. The incident has attracted intense attention over the past couple of weeks. It’s a dramatic illustration of just how good AI models have gotten at hacking. But it’s perhaps even more striking as an example of how and why AI systems lie and cheat. Read our story explaining why AI engages in this sort of behavior—known as ”reward hacking.” —Grace Huckins This story is from our ‘Explains’ series, where our writers untangle the complex, messy world of technology to help you understand what’s coming next. Read more from the collection . The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 It looks like Iran is conducting cyberattacks on US water systems That’s according to preliminary investigations on hacks in at least seven states. ( NYT $) + Will this be a wake-up call? ( Forbes ) 2 Google briefly made it easy to fake satellite images Literally the last thing the world needs right now. ( NPR ) + AI companies keep moving fast and breaking things. ( The Atlantic $) + Apple is struggling to keep pace with incoming AI-assisted software bug reports. ( FT $) 3 Why wildfires have got so bad in Europe this summer It’s a mix of climate change, land abandonment, and outdated firefighting tactics. ( New Yorker $) + How Europe can be
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