The Wire · Microsoft
Copilot, Azure AI, and Microsoft's AI across its stack — what's shipping and what it means for builders.
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.
The software engine underpinning GitHub Copilot and a growing number of Microsoft products is now written entirely in Rust, with AI agents doing most of the porting work. The migration cost about $120,000 in AI token usage plus about three weeks of a developer's time. However, managers also had to grapple with a few dozen regressions in the resulting code, pointing to AI’s ongoing challenges in understanding Rust. The effort updated the runtime module-by-module until the job was completed, spanning over 135 releases across a 14.5-week time period. Roughly 1.3 port pull requests were opened per day. Overall, agents converted 430,000 lines of TypeScript into 800,000 lines of production Rust. To keep the port as simple as possible, the port only replaced TypeScript modules on a case-by-case basis. It didn’t look to optimize the structure of the runtime itself. That work is next. And Rust, known for its lean performance, did not disappoint. One benchmark measured how quickly the runtime could complete 1,000 one-turn session lifecycles, using a shared client and 100 concurrent pipelines. The original TypeScript implementation completed 7.55 of those lifecycles per second, while Rust running in-process managed 120 per second - representing a 15.9x speedup on that particular workload. In terms of memory, a 10-client batch of agents consumed 1,383 MB with TypeScript while the Rust rewrite consumed only 126 MB serving the same swarm. Within Rust, the work remained in-process instead of spawning external background processes for completion, a requirement for TypeScript. Copilot from VS Code to Microsoft Office At first glance, most users may not know how pervasive the Copilot runtime is. It backs the GitHub Copilot command-line interface (CLI), the Copilot app, the SDK and the GitHub Copilot cloud agent. It shows up in VS Code, Visual Studio, Excel, Outlook, PowerPoint, and innumerable other Microsoft cloud services. Originally, the runtime was written in TypeScript and used
Read full story →Recently unsealed court documents in the New York Times' case against OpenAI and Microsoft are pretty damning. The companies' own documentation warned that it was starting a "doom loop" that would damage the web, characterized its scraping of data to train its models as the "largest theft of labor in human history," and that it […]
Read full story →Microsoft has reminded administrators that Internet Explorer mode in Edge is guaranteed support only through 2029, so it is time to get those legacy migrations moving. Internet Explorer mode lets enterprises continue using legacy websites within Edge rather than relying on the retired Internet Explorer browser. It uses the Trident MSHTML engine from Internet Explorer 11 and permits elements such as ActiveX controls, although other Internet Explorer functionality, such as custom toolbars, is not supported. Microsoft has promised to support IE mode until at least the end of 2029 and to provide one year's notice before retiring it. The feature is unlikely to stop working immediately after support ends, but organizations that depend on it could face security, compatibility, and compliance risks. A message in the Microsoft 365 admin center urges customers to begin modernizing legacy systems that still depend on Internet Explorer technology. The company wrote: "Application modernization projects can take years to complete depending on the number and complexity of dependencies, so early planning reduces the risk of disruption later." Microsoft has been banging this particular drum for some time. It announced in 2021 that IE mode would be supported until at least the end of 2029, but its latest reminder suggests some customers still have substantial migration work ahead of them. Administrators do not need to act immediately, but migrations involving old and heavily dependent applications can take years to complete. Internet Explorer debuted with the Plus! Pack for Windows 95 in 1995, but traces of it will survive for years yet. Internet Explorer 11 is included with Windows 10 IoT Enterprise LTSC 2021, which remains supported until 2032, although Microsoft could retire Edge's IE mode considerably sooner. The end of 2029 might feel distant, but not to an enterprise facing a lengthy and potentially expensive migration from systems implemented decades ago. ®
Read full story →The U.S. House of Representatives just passed a bill that creates a federal standard requiring data centers to pay for grid upgrades made in their favor. H.R. 9340, also known as the Ratepayer Protection Act , amends the Public Utility Regulatory Policies Act of 1978, which would require each State regulatory authority and each non-regulated electric utility to consider the adoption of the bill within two years of its passing, if it is signed into law. Go deeper with TH Premium: AI and data centers (Image credit: Microsoft) The data center cooling state of play The custom AI ASIC state of play America’s AI chip rules keep changing — and the rest of the world is paying the price GTC 2026: Ian Buck press Q&A transcript — VP of Hyperscale and HPC speaks out on shelving CPX and shipping LPU decode this year Demand for data center CPUs has surged, and AI agents are responsible This bill would ensure that data centers with a capacity of 100 megawatts or more would have to pay “the full, incremental cost of any generation, transmission, or distribution upgrade necessary to serve the load of such large-load customer, including in the event of such large-load customer terminating a contract or other agreement with the electric utility pertaining to the sale of electric energy, or otherwise ceasing the purchase of electric energy from the electric utility.” This bill closely follows President Donald Trump’s “Ratepayer Protection Pledge,” where he made AI hyperscalers, utility providers, and state governors promise that they will pay their own way when it comes to their electricity demands. All this stemmed from the surprise price hikes that many residential users and small businesses suffered from because of the massive demand by AI data centers and has become one of the primary reasons why the majority of Americans now oppose data center developments in their communities. Oregon is actually one of the first states to have taken concrete steps in controlling the utility price
Microsoft has issued a partial fix for the Excel bug that causes paste operations to fail. The hotfix applies only to Excel 2016, and Microsoft warns that pasting may still fail in workbooks containing conditional formatting. Earlier in September, Microsoft released a security update for Excel to address remote code execution and information disclosure vulnerabilities. It later acknowledged that the update had introduced another problem: "In Microsoft Excel 2024, 2021, 2019, and 2016, the paste operation might fail silently. "Although users try to paste content, the source remains selected and the destination is unmodified. When this issue occurs, users receive no indication of the failure, such as a beep or error message." Some users could work around the problem with Paste Special, but others had to wait for Microsoft to act. A fix has now arrived – for Excel 2016 only – and it continues to hover rather nervously in the doorway. September has not been kind to Microsoft, its updates, or the emergency updates needed to repair them. The September Windows security update required an out-of-band release to address several problems, but even that left some work unfinished. Certain USB audio devices, for example, could remain silent after the emergency update. Microsoft has since added another problem involving domain-joined devices to its known issues list. While users of newer Excel releases continue to wait, Microsoft has at least repaired another problem introduced by an August update. A bug that caused Windows Security to incorrectly report that Microsoft Defender Antivirus was disabled was resolved in a Defender update released on September 17. Kudos to the team, although the best fix remains not breaking things in the first place. ®
better agentic engineering
Executives working on AI at Microsoft and OpenAI admitted what its critics have been saying all along: Large language models are predatory pieces of technology that have been built on what a Microsoft executive called “an astonishing theft of unprecedented proportions,” and the “largest theft of labor in human history.” An internal Microsoft document said generative AI products have created a “doom loop” that is killing “the entire web.” Those statements and a series of other mask-off moments feature heavily in an unredacted court filing that was unsealed Thursday in the behemoth New York Times vs OpenAI copyright lawsuit that has been winding its way through the court system for years. In a filing asking for summary judgment (basically, a filing with the court asking it to rule), lawyers for the New York Times laid out a series of admissions made by Microsoft and OpenAI executives in documents and depositions that until now had remained either sealed or redacted at the request of Microsoft and OpenAI. It’s easy to see why the AI companies wanted to hide this from the public. The statements, taken together, are some of the most damning indictments of the ways LLMs were trained, how they worked, and the immediate threat they pose to human labor. It is a reminder that even as AI becomes more powerful and companies try to shift the narrative to the supposed existential risk of “superintelligent” AI, the tools they have already built were created by stealing from human creativity and labor and are by definition existential threats to the human labor market. “Millions of people around the world will soon consider large models ‘hoovering up’ all their work to be an astonishing theft of unprecedented proportions,” an internal Microsoft document cited in the case read, adding “almost no one intended for content they created to be used in this fashion, nor are they compensated for its use.” The filing was written by lawyers for the New York Times but is largely comprised of
For years, Microsoft and OpenAI have fought to keep certain information out of the public eye in their fight with news organizations that have accused the AI firms of teaming up to violate copyright laws by stealing tons of news content to train AI. However, now the details that should never have been marked confidential are starting to leak. In a motion for summary judgment that was unsealed Thursday from news plaintiffs led by The New York Times, internal documents are exposed that news groups alleged show exactly how Microsoft and OpenAI viewed the threat to news before unleashing new AI products like ChatGPT and Copilot. Perhaps most explosively, Microsoft Director of Applied Science Brent Hecht repeatedly warned in documents that scraping news for AI training was “an astonishing theft of unprecedented proportions,” calling it perhaps the “largest theft of labor in human history,” news orgs said. In another document, Hecht contradicted Microsoft and OpenAI’s argument that training AI on news content is fair use, suggesting that the plan to widely scrape news made “a complete mockery of the idea of ‘fair use.’” Read full article Comments
Today, I’m talking with Mustafa Suleyman, the CEO of Microsoft AI. As you’re no doubt aware, the biggest story in tech right now is the spiraling debate about AI safety and regulation. It should come as no surprise that Mustafa has strong opinions on how AI should be built and regulated. Microsoft just published a […]
New York State Governor Kathy Hochul has just announced the Community Investment Framework (CIF), which serves as a negotiation guide for towns and municipalities in the state when they’re dealing with data center developers, recommending that communities demand $1 million per megawatt for the privilege of housing data centers. According to Empire State Development [ PDF ], the state’s economic development agency, the CIF offers “a structured approach to identifying, negotiating, and documenting investments from data center developers/operators/owners that address local priorities and create lasting community benefits.” Go deeper with TH Premium: AI and data centers (Image credit: Microsoft) The data center cooling state of play The custom AI ASIC state of play America’s AI chip rules keep changing — and the rest of the world is paying the price GTC 2026: Ian Buck press Q&A transcript — VP of Hyperscale and HPC speaks out on shelving CPX and shipping LPU decode this year Demand for data center CPUs has surged, and AI agents are responsible The document recommends six principles during data center negotiations: an investment benchmark of $1 million per megawatt of utility demand; long-term planning, including plans for when the data center leaves the facility; a roadmap to manage ongoing costs for projects funded through the CIF; a list of local priority investment areas to address the needs of the community; local ownership confirmation of projects receiving funding from data centers; and clear timelines for any program, especially those that require phased, multi-year investments. Aside from these, it also gave several recommendations, such as focusing on community engagement, engaging decision-makers and counsel, incentivizing good faith and timely negotiations, and maintaining flexibility, among others. While data centers have been around for decades now, AI data centers are relatively new and are putting more pressure on electricity and water supplies. They also
Over the past few days, a lot of people who stand to make a lot of money from AI all publicly agreed that it's time to make everyone slow down before we lose control - including OpenAI CEO Sam Altman, Anthropic CEO Dario Amodei, Google DeepMind cofounder Demis Hassabis, Microsoft CEO Satya Nadella, and X […]
The estimated natural gas consumption of data centers in the U.S. is expected to massively increase as these facilities increasingly rely on gas turbine generators for their power. According to Bloomberg , data centers are projected to use up to 15 billion cubic feet per day by 2035, a 117% increase from the previous forecast of 6.9 billion cubic feet. This number tracks with other data center forecasts, which suggest that data centers will use 20% of U.S. power by 2035, amounting to about 194 gigawatts. Go deeper with TH Premium: AI and data centers (Image credit: Microsoft) The data center cooling state of play The custom AI ASIC state of play America’s AI chip rules keep changing — and the rest of the world is paying the price GTC 2026: Ian Buck press Q&A transcript — VP of Hyperscale and HPC speaks out on shelving CPX and shipping LPU decode this year Demand for data center CPUs has surged, and AI agents are responsible Many data center projects have already been delayed by the lack of available power infrastructure , with power plants expected to take so much longer before they come online. It’s for this reason that many developments have turned towards onsite generators , so much so that AI demand is now compounding the jet engine shortage already plaguing the aviation industry. Elon Musk was among the first to use gas turbines to power a data center when he deployed them at the Memphis Supercluster in 2024 , even though he didn’t have permits for some of them . Now, it seems that the world’s richest man has seen this trend and has invested a billion dollars to buy a portable gas and diesel turbine leasing company . He even announced that SpaceX will start in-house turbine blade manufacturing to help cut down on the manufacturing bottleneck plaguing the jet engine industry. New technologies like small modular reactors are currently being developed as an answer to AI data centers’ insatiable demand for power, like Ampera’s 3D-printed modular thorium nuclear rea
Last year Ruxandra Teslo, a policy analyst who focuses on clinical trials, posted an idea for supercharging medical AI systems: Use data from failed biotech companies. By bidding at their bankruptcy proceedings, she proposed, it might be possible to obtain detailed regulatory filings, manufacturing strategies, and safety data—types of information usually considered trade secrets. She called these documents “ biotech’s lost archive ” and said they could be used to help train AIs that would act as powerful copilots in the often opaque drug approval process. Today the OpenAI Foundation, the nonprofit parent of OpenAI , said it would fund her idea as part of a new effort it calls Public Data for Health, which aims to help artificial intelligence make big leaps in medicine by paying to create “high-quality scientific datasets.” The basic idea is that AI isn’t going to be capable of making important breakthroughs in curing disease unless researchers can feed the models much more information than they have so far. “Everyone is recognizing that data is the biggest bottleneck in successfully applying AI to biology,” says Morgan Levine, a former vice president for computation at Altos Labs, a longevity company. In its initial round of data grants, the OpenAI Foundation also announced that it would give $40 million to a program to collect data about novel cancer vaccines at the University of North Carolina, Chapel Hill, and support OpenAdmet, a group that runs competitions in which researchers try to predict drug effects. Teslo’s idea for a biotech archive received $500,000 and will be pursued by 1Day Sooner, an advocacy group representing clinical trial volunteers, which she advises. “We expect many remaining breakthroughs in preventing and curing disease to come from pairing the intelligence of new models with more observations of the world—in other words, more data,” the OpenAI Foundation said in a statement. OpenAI started as a nonprofit, but leader Sam Altman
For years now, the major frontier AI labs have all been acting as if they're in an all-out, winner-take-all race with control of world-changing machine superintelligence (or at least market-changing artificial general intelligence ) at the finish line. This weekend, the industry as a whole rapidly started turning away from that posture, urging coordination on slowing down the development of frontier AI that they say could soon be too dangerous and unknowable to control. Anthropic's Dario Amodei was at the forefront of this change in tone, arguing in a nearly 4,000-word essay this weekend that "we must slow the pace at which we improve the capabilities of AI models" to avoid "a race to the bottom, spurred by commercial incentives, [that] can make [catastrophic] risks more acute." Within hours, other AI leaders were echoing the same call. OpenAI co-founder and CEO Sam Altman posted his agreement on social media and said similar pacing discussions had been taking place at OpenAI. Alphabet Chief Scientist and Google DeepMind cofounder and chair Demis Hassabis said that Amodei's essay "points towards the right path forward," and renewed his own recent call for an industry-wide standards body . Microsoft CEO Satya Nadella posted that the company "welcome[s] the research, focus, and deliberate pacing needed to get alignment right as the design goal," ahead of the release of a lengthy "humanist AI" code of conduct for its models . Read full article Comments
The code of conduct lays out general principles that Microsoft AI models should uphold — supporting humans rather than replacing them, for instance, and accelerating human flourishing — as well as specific safety constraints meant to implement those principles.
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.