Summary: The Pentagon has narrowed its Advanced Nuclear Power for Installations (ANPI) programme from eight companies to three, advancing microreactor deployment at Buckley Space Force Base (Colorado) and Malmstrom Air Force Base (Montana) by 2030. The original eight vendors included BWXT, Oklo, X-energy, Kairos Power, Radiant, General Atomics, Westinghouse, and Antares. The commercially owned reactor model, backed by Executive Order 14299 and $125 million in Congressional funding, addresses military grid vulnerability while serving as a proving ground for reactors that could also power AI data centres.

The Pentagon has narrowed the field for its programme to install microreactors at US Air Force bases, selecting three companies from an original pool of eight to advance toward deployment, Bloomberg reported on Tuesday. The down-selection is the most concrete step yet in the Advanced Nuclear Power for Installations programme, known as ANPI, a joint effort between the Defense Innovation Unit, the Air Force, and the Army that aims to make military bases energy-independent by replacing their reliance on a civilian power grid that is increasingly vulnerable to cyberattacks, extreme weather, and the cascading demands of AI-driven energy consumption.

The programme began in April 2025, when the DIU selected eight companies to develop microreactor proposals: Antares Nuclear Energy, BWXT Advanced Technologies, General Atomics Electromagnetic Systems, Kairos Power, Oklo, Radiant Industries, Westinghouse Electric Company, and X-energy. Each was tasked with designing commercially owned and operated reactors that could be built on military land, licensed through the Nuclear Regulatory Commission, and maintained by the vendor throughout their operational life. The military would buy the electricity without owning the reactor, a model designed to accelerate deployment by sidestepping the decades-long procurement cycles that have historically paralysed defence infrastructure projects.

Why Air Force bases need their own power plants

The Department of Defense consumes more than 30 terawatt-hours of electricity annually across more than 500 installations, making it the single largest energy consumer in the US government. The overwhelming majority of that power comes from the civilian grid. That dependence is now treated as a strategic vulnerability. Cyberattacks on US energy infrastructure have increased by roughly 70% in recent years. The grid itself is under growing strain from data centre construction, with the International Energy Agency projecting that data centre electricity consumption will exceed 1,000 terawatt-hours globally by the end of 2026. Military bases that host missile fields, space surveillance operations, and nuclear command infrastructure cannot afford to compete with AI training clusters for grid capacity.

Two Air Force installations have been selected as the first deployment sites. Buckley Space Force Base in Aurora, Colorado, hosts the Aerospace Data Facility, one of the Department of Defense’s primary satellite ground stations. Malmstrom Air Force Base in Great Falls, Montana, oversees 150 Minuteman III intercontinental ballistic missiles spread across 13,800 square miles of Montana prairie. Both bases require uninterrupted power for operations that are, by definition, existential. Nancy Balkus, the Deputy Assistant Secretary of the Air Force for operational energy, has said that energy security at these installations is not an efficiency question but a readiness question. The target is operational microreactors at both sites by 2030.

The technology

Microreactors are nuclear fission reactors that typically produce between one and 20 megawatts of electrical power, small enough to fit on a few truck trailers and large enough to power a military base or a small data centre. They use advanced fuel forms, most commonly TRISO (tristructural isotropic) particles encased in ceramic and graphite shells that can withstand extreme temperatures without melting down. Several of the ANPI candidates use high-assay low-enriched uranium, or HALEU, which is enriched to between 5% and 20% uranium-235, higher than conventional reactor fuel but well below weapons grade.

The designs vary significantly. BWXT’s Project Pele, developed separately for the Army, is a 1.5-megawatt transportable reactor that completed initial testing at Idaho National Laboratory and uses TRISO fuel with a gas-cooled design. In February 2026, the Pentagon airlifted a five-megawatt microreactor prototype from California to Utah, the first military nuclear airlift, demonstrating the transportability that makes these systems attractive for expeditionary and remote base operations. Oklo, whose chairman is OpenAI chief executive Sam Altman, designs a compact fast reactor called the Aurora that uses metallic fuel and targets both military and commercial applications. X-energy, which went public with Amazon’s backing, is developing the Xe-100, an 80-megawatt high-temperature gas-cooled reactor that uses TRISO-X fuel pebbles. Kairos Power is building a fluoride salt-cooled reactor. Radiant Industries, founded by former SpaceX engineers, is developing a portable one-megawatt reactor designed for rapid deployment.

Only NuScale Power has received full design certification from the Nuclear Regulatory Commission for a small modular reactor, but NuScale’s design is a 77-megawatt light-water reactor, far larger than what ANPI requires. The ANPI programme’s commercially owned model means that vendors will need to secure their own NRC licences for reactors sited on military land, a regulatory path that has not been tested at this scale. The Atomic Energy Act provides a military exemption for reactors operated by the armed forces, but the ANPI model explicitly uses commercial operators, which means NRC jurisdiction applies.

The policy architecture

The programme sits within a broader policy push that has acquired unusual bipartisan momentum. Executive Order 14299 explicitly links nuclear power to AI infrastructure at military installations, directing federal agencies to accelerate the siting and permitting of advanced reactors. The ADVANCE Act, signed into law with an 82-to-14 Senate vote, streamlines NRC licensing for advanced reactor designs. Congress has appropriated $125 million for military microreactor development. The Army’s separate Project Janus programme is evaluating nine additional bases for microreactor deployment.

The convergence of military energy security and commercial AI infrastructure is not coincidental. The Department of Energy has identified 16 federal sites, many adjacent to existing nuclear facilities, as candidates for data centre construction. Nuclear-powered AI data centres are attracting dedicated venture capital, with Valar Atomics raising $450 million at a $2 billion valuation to build small modular reactors purpose-built for AI workloads. The same microreactors that power a missile field in Montana could, in a commercially licensed configuration, power an AI training cluster in Texas. The ANPI programme is a military procurement initiative, but it is also a proving ground for the reactors that the technology industry hopes will solve its energy problem.

What stands in the way

The 2030 deployment target is ambitious by nuclear standards. No advanced microreactor design has completed NRC licensing. HALEU fuel supply remains constrained, with Centrus Energy as the only domestic commercial producer and Russia historically the dominant global supplier, a dependency that sanctions have complicated. Community opposition to nuclear facilities, even small ones on existing military bases, has slowed previous projects. The cost economics of microreactors at the one-to-20-megawatt scale remain unproven in commercial operation, though the commercially owned model shifts that financial risk from the Department of Defense to the vendors.

The nuclear waste question also persists. Microreactors produce far less spent fuel than conventional power plants, but the United States still lacks a permanent repository for any nuclear waste. Advanced fuel forms like TRISO are more proliferation-resistant and easier to store than conventional spent fuel rods, but “easier” is relative in an industry where waste management has been a political impossibility for four decades.

The broader debate over nuclear power and AI has tended to focus on fusion, the technology that is always 20 years away, or on gigawatt-scale conventional plants that take a decade to build. Microreactors occupy a different niche: small enough to be manufactured in a factory rather than constructed on site, simple enough to operate with minimal staffing, and modular enough to scale by adding units rather than building larger. The military is betting that this niche is real. The down-selection from eight companies to three means the Pentagon has now seen enough proposals to decide which designs are credible and which are not. The three that remain have roughly four years to prove that a nuclear reactor can be as reliable, and as unremarkable, as the diesel generators that military bases currently keep for backup power. If they succeed, the implications extend well beyond the fence line of an Air Force base.

The new model reasons about composition, searches the web for context, generates up to eight coherent images from one prompt, and renders text in non-Latin scripts with near-flawless accuracy. It also took the number one spot on the Image Arena leaderboard within 12 hours of launch, by the largest margin ever recorded.

Two years ago, asking ChatGPT to generate a visual was like commissioning a poster from a sleep-deprived intern with a glue stick and a head injury. You’d ask for a clean design and get “leftovers creativity” splashed across the image, plus three new words that looked like they’d been invented during a minor software malfunction.

The images looked AI-generated in the way that has become a cultural shorthand for uncanny: almost right, conspicuously wrong, and instantly recognisable as synthetic.

The leap matters. Text rendering has been the persistent, embarrassing weakness of AI image generators since DALL-E first turned heads in January 2021, a model we covered at the time as a fascinating curiosity.

Images 2.0 claims approximately 99% accuracy in text rendering across any language and script, including Japanese, Korean, Chinese, Hindi, and Bengali. If that figure holds in independent testing, it closes the gap between “impressive AI demo” and “tool a graphic designer would actually use for production work.”

The architectural change that makes the model different, though not just better, is what OpenAI calls “thinking capabilities.” Images 2.0 is the company’s first image model to integrate its O-series reasoning architecture.

Before generating a pixel, the model researches the prompt, plans the composition, reasons about spatial relationships between elements, and can search the web for real-time context.

It is, in OpenAI’s framing, not a rendering tool but a “visual thought partner.”

This is my cat transformed into a comic strip with ChatGPT.

In practice, this manifests in two access modes. Instant mode ships to all ChatGPT users, including free-tier accounts, and delivers the core quality improvements: better text, sharper editing, richer layouts.

Thinking mode, which enables web search, multi-image batching, and output verification, is restricted to Plus ($20/month), Pro ($200/month), Business, and Enterprise subscribers.

The distinction is commercially significant. The reasoning capabilities, where most of the quality premium lives, sit behind the paywall. Free users get better images; paying users get images the model has thought about.

The multi-image capability is the feature most likely to change professional workflows. A single prompt can now produce up to eight images that maintain character and object continuity across the set.

That means a designer can generate a family of social media assets, a children’s book sequence, or a series of storyboard frames from one instruction, with consistent visual identity throughout.

Previously, each image had to be prompted individually and stitched together manually. For marketing teams and content creators, that is a meaningful reduction in production friction.

The integration into Codex, OpenAI’s coding environment, is the strategically loaded move. Developers and designers can now generate UI mockups, prototypes, and visual assets inside the same agentic workspace they use for code, slides, and browser automation, using a single ChatGPT subscription.

The image model is no longer a standalone product; it is a capability embedded in OpenAI’s broader platform, competing not just with Midjourney and Google’s Nano Banana 2 on quality but with Canva and Figma on workflow integration.

The benchmark performance is striking. Within 12 hours of launch, Images 2.0 took the number one spot on the Image Arena leaderboard across every category, with a score of 1,512, a +242-point lead over the second-place model, Google’s Nano Banana 2. That is the largest lead ever recorded on the leaderboard.

For most of 2026, OpenAI and Google had been trading the top position within a tight margin; Images 2.0 broke away decisively. 

DALL-E 2 and DALL-E 3 are being deprecated and retired on 12 May 2026. GPT-Image-1.5, released in December 2025 as an intermediate upgrade, remains accessible via the API for legacy integrations but is no longer the default model.

OpenAI did not disclose the architecture of Images 2.0, describing it only as a “generalist model” or “GPT for images” and declining to specify whether it uses a diffusion, autoregressive, or hybrid approach. The API model identifier is gpt-image-2; the API is expected to open to developers in early May 2026.

Token-based pricing is $8 per million tokens for image input, $2 for cached input, and $30 for image output, with per-image costs typically ranging from $0.04 to $0.35 depending on prompt complexity and resolution. Output resolution reaches up to 2K.

The knowledge cutoff is December 2025, which introduces a practical boundary: the model cannot accurately render events, people, or products that emerged after that date without supplementing its internal knowledge with live web search.

The model’s safety architecture includes content filtering, C2PA metadata for provenance, and what OpenAI described in the press briefing as ongoing monitoring, a point the company was notably emphatic about, given the growing regulatory scrutiny of synthetic media and the use of AI image generators in deepfakes, scams, and non-consensual imagery.

The most consequential question Images 2.0 raises is not about quality. The technical gap between AI-generated and human-created imagery has been narrowing for years; this model narrows it further.

The question is about what happens when the tool is no longer a novelty but infrastructure, when image generation is a default capability of every coding environment, every chat interface, and every enterprise productivity suite, and when the distinction between “designed by a person” and “generated by a prompt” becomes something only metadata can verify.

OpenAI, for its part, appears to be betting that the answer is scale: more images, faster, better, cheaper, everywhere. When we covered first covered DALL-E five years ago, the model’s outputs were fascinating oddities. Now they are production assets.

The era in which AI-generated images were obviously AI-generated is over. What comes next depends on whether the guardrails can keep pace with the capability.

Lots of smart glasses have AI bots inside them now. The one in L’Atitude 52°N’s glasses is called Goya, named after Francisco Goya, the famous Spanish artist who painted renowned masterpieces of romanticism.

CEO and founder Gary Chen, who has worked on wearable devices for companies like Oppo, OnePlus, and HTC, says his company’s glasses are focused on travelers, with AI features that act like a tour guide and talk about all the paintings in famous museums.

“Basically, you can say, ‘Hey, Goya, what is the story about Mona Lisa?’” Chen says. “You can ask anything and, with your permission, they will take a photo to analyze what’s in front of you.”

I ask if you could quiz it about perhaps the most famous Goya painting, the terrifying, Gothic horror-esque image of Saturn devouring his own son.

“Yes, yes,” Chen says, “It can also give you some recommendations about restaurants.”

Berlin-based L’Atitude 52°N is a new player in the smart glasses space, selling its first pairs on Kickstarter in September 2025, where the campaign surpassed its funding goal and raised more than $400,000. There have been some bumps since then, as shipments were delayed from an originally announced release date in February 2026, and one model in development was scrapped outright. Now, L’Atitude 52°N has announced an official release date for its smart glasses.

Preorders for one model, called Berlin, start on May 19. The glasses actually go on sale on May 26. This might be a disappointment for Kickstarter backers, as the most recent official update from the campaign came in March and said shipping would begin on April 15 for Berlin units and June 7 for the second model, called Milan. L’Atitude 52°N still hasn’t set an official launch date for the Milan, except to say that it will be “arriving in the second quarter of 2026.”

The Berlin glasses cost $399. Add another $50 for the photochromatic lenses. There is one very big catch: The AI features enabled on the device will only work for 12 months, which L’Atitude 52°N calls an “AI feature trial.” After that, customers have to pay for a subscription service, or will be limited to the base features, like playing music and capturing media.

How much will that subscription service cost? Chen says he doesn’t know.

• Leica announced a strategic partnership with Chinese sensor maker Gpixel
• Recent Leica cameras use Sony-made sensor tech
• We can expect a new bespoke sensor for future models, possibly the rumored M12

There has been plenty going on behind the scenes at Leica recently, not least of which potentially selling a controlling stake of the business for approximately $1.2 billion to Chinese and Swedish investors. Now, it looks set to change the bedrock of the tech inside its digital cameras.

In January, Leica’s Chairman of the Supervisory Board, Dr Andreas Kaufman, revealed that “we’re also developing our own sensor again” when referring to future development of the Leica M-system. He made the comment in the German-language ‘Leica Enthusiast Podcast’, according to a report by Peta Pixel.

The Turkish parliament has voted through a bill that would ban all children under the age of 15 from using social media. As part of the legislation, social media platforms would be required to enforce age-verification measures on their apps, provide parental control tools, and react more quickly to harmful content being posted.

As reported by , lawmakers have passed the bill in the wake of two deadly school shootings in Turkey, after which police 162 people accused of sharing footage of the tragedies online.

Turkey’s President Recep Tayyip Erdogan now has 15 days to accept the bill in order for it to become law, after reportedly saying social media platforms had become “cesspools” in a televised address to the nation.

As well as the major social media platforms, AP reports that online gaming companies would also have to implement their own restrictions on minors, with potential punishments including bandwidth reductions and financial penalties.

This isn’t the first time Turkey has locked horns with social media and online gaming platforms. Instagram has been in the country before, back in 2024, relating to a dispute over the posting of Hamas-related content. Access was restored around a week later, but in the same time period Turkey also Roblox over reports of inappropriate sexual content accused of being explorative to children. At the time, a Turkish official also named the “promotion of homosexuality” as one reason for the ban.

Turkey has also temporarily banned (now called X) on several occasions, most after 2023’s devastating earthquakes, though it was not clear at the time why the government may have moved to block the social media platform.

The country’s lawmakers moving to ban under-15s from accessing social media is part of an emerging trend in Europe and across the globe. The likes of and have recently introduced similar legislation of their own, following becoming the first country in the world to ban children under 16 from social media last year. The UK has since bringing in tighter restrictions too.