Scientists today face challenges of extraordinary scale and complexity. From shaping and simulating the intricate dynamics of fusion plasma, to exploring the vast search space of new materials, to making sense of the exabytes of data pouring out of the world’s most advanced experimental facilities. The demands on modern research are unprecedented. Frontier AI can help address these challenges, while accelerating groundbreaking scientific discoveries.In December, we shared our commitment to the White House’s Genesis Mission — the national effort to harness AI and double the pace of American scientific discovery within a decade. Since then, Google DeepMind (GDM) announced an early access program that provides AI for science tools to all 17 Department of Energy (DOE) National Laboratories, and Google Public Sector shared how Gemini for Government could serve as an AI backbone for the DOE.Today, at the DOE Genesis Mission Summit 2026, we are expanding this by committing $40 million of AI tokens and cloud credits for researchers in support of the Genesis Mission.Frontier AI tools for scientific discoveryUnder this expanded commitment, we will first provide DOE’s Genesis Mission awardees in-kind access to GDM’s frontier AI for science portfolio, including:AlphaEvolve — a Gemini-powered coding and discovery agent, for designing advanced algorithms.AlphaFold 3 — a model for predicting the structure and interactions of proteins and other biomolecules.AlphaGenome — a tool for understanding how variation in DNA, including the non-coding genome, shapes biology and disease.WeatherNext — a state-of-the-art family of AI weather forecasting models for mapping weather conditions.AlphaEarth Foundations — a foundational AI model for mapping and understanding our planet in unprecedented detail.Second, we will provide Gemini for Government seats and tokens for one year to tens of thousands of users across the DOE National Laboratories’ operations, research, and management teams. This secure platform supports the full breadth of work from the research bench to the administration of specialized user facilities serving the entire scientific community, providing a single secure foundation that the DOE mission can depend on.AI for science tools in action across the laboratory ecosystemWhile we have a lot of work still to do, the practical impact of the Genesis Mission is already coming to life across the laboratory ecosystem.At Pacific Northwest National Laboratory (PNNL), senior scientist Dr. Henry Kvinge is using AlphaEvolve to map out massive mathematical systems that are far too complex for humans to explore by hand. The AI uncovers hidden connections automatically, fast-tracking discoveries that would normally take researchers years to find.“Modern math relies on abstraction, but combinatorics offers concrete models that make complex geometry and algebra easier to grasp. We’ve found that systems like AlphaEvolve are perfect for this search,” said Dr. Kvinge. “By leveraging the broad mathematical knowledge of LLMs, we can automate the exploration of countless angles. We’re still experimenting, but the discoveries are already shaping our future research.”At the National Laboratory of the Rockies (NLR), researchers are utilizing Gemini to fundamentally change how they interact with physical laboratory hardware. Dr. Steven R. Spurgeon, a senior materials data scientist at NLR, leads a pioneering program in autonomous materials discovery.”Our collaboration has allowed us to build an autonomous experimentation capability,” said Dr. Spurgeon. “By deploying Gemini in our instruments, we cut microscope calibration time from over 90 minutes to about 13 minutes (eight times faster) and reduced the manual steps needed to focus an image from as many as 50 down to two. That’s time and attention we’ve given back to the science itself, enabling genuinely autonomous workflows that observe, reason, and decide in real time. This has helped us explore parts of the material design space we simply could not have reached through manual operation alone.”Driving American innovationThe Genesis Mission represents an opportunity to transform research and science across America. By providing access to advanced AI tools, we aim to help scientists accelerate breakthroughs across critical energy, security, and scientific challenges. To learn more about how these AI capabilities can support your research initiatives, join us at the upcoming Google Public Sector Summit in October.

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. Shape-shifting mirrors on NASA’s new space telescope could unveil Jupiters like our own When NASA’s Nancy Grace Roman Space Telescope launches, as early as the end of next month, it will attempt one of astronomy’s most precise disappearing acts to date. It will carry the first space-bound “active” coronagraph, an instrument that effectively erases most of the light from a star during photography. The technology will allow astronomers to take the first pictures of planets orbiting other stars that are similar to those in our solar system. Ultimately, it could pave the way for a future mission that could snap the first photos of Earth-like worlds. “I hope it’s remembered for it being that critical stepping stone for … finding Earth 2.0,” says Brandon Creager, the instrument’s lead mechanical engineer.
Read the full story on the space telescope that could transform the search for distant planets. —Eshan Raul
MIT Technology Review Narrated: PsiQuantum has a plan to make a massive quantum computer out of light The machine that could change the world will be housed in a room that looks like a data center crossed with an ice cream factory.  Inside, some 100 stainless-steel cabinets each hold hundreds of chips. On those chips, thousands of light particles will fly through a maze of optical switches and beam splitters. Each photon must be accounted for, because precisely measuring where it ends up will help answer questions that current computers might take millions of years to solve. This computer, as described, does not exist. It’s the brainchild of a company called PsiQuantum, founded in 2016 by four physicists from UK universities. In a crowded field of deep-pocketed competitors with similarly fantastical visions, the company aims to be the first to build a useful quantum machine. —James O’Donnell This is our latest story to be turned into an MIT Technology Review Narrated podcast, which we publish each week on Spotifyand Apple Podcasts. Just navigate to MIT Technology Review Narrated on either platform, and follow us to get all our new content as it’s released. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 OpenAI says one of its models carried out an autonomous hackIt escaped its testing sandbox and breached AI research platform Hugging Face. (Reuters $)+ OpenAI described it as a cybersecurity test that went badly wrong. (WSJ $)+ The hack is among the first known cyberattacks by an AI acting on its own. (FT $)+ Even simple AI attacks are cause for alarm, though. (MIT Technology Review)

2 France has become the first EU country to ban social media for under-15sIts parliament approved the ban, which President Macron championed. (NYT $)+ He pledged to enforce it by September, the start of the school year. (Guardian)+ But critics say it’s unconstitutional and impossible to enforce. (NPR) 3 The US and China will hold talks over AI in SeptemberTreasury Secretary Scott Bessent will lead the US side. (Reuters $)+ Chinese models have Trump’s AI world at war with itself. (MIT Technology Review) 4 Publishers are considering cutting Google off as AI reshapes searchNews outlets are weighing lost traffic against AI exposure. (WSJ $) 5 Samsung is in talks to invest €1 billion in MistralThe French AI firm is positioning itself as an alternative to US models. (FT $)+ It’s Europe’s leading AI firm, but US peers dwarf its $20 billion valuation. (Reuters $) 6 Amazon pushed up rivals’ prices, leaked records allegeInternal emails reveal tactics that allegedly reshaped online pricing. (Guardian) 7 Trump has tapped a Big Tech critic to lead the DOJ’s antitrust divisionAdam Candeub has called for tougher federal competition enforcement. (FT $) 8 New drilling methods could unlock geothermal energy almost anywhereThey aim to unlock Earth’s enormous heat reserves. (New Scientist $)+ AI is uncovering hidden geothermal energy resources. (MIT Technology Review) 9 AI researchers have proposed a “Genie coefficient” for measuring AI risksIt would track the gap between intent and action. (IEEE Spectrum)+ We need better ways to evaluate AI. (MIT Technology Review)
10 Japan’s AI boom has two unlikely winners: a toilet maker and an MSG giantThey’re supplying critical chipmaking materials. (CNBC) Quote of the day
“He’s an analog man in a digital AI world, and I think that’s incredibly appealing.” —Paul Dergarabedian, a movie industry analyst at Comscore, tells Fortune that Christopher Nolan’s commitment to human filmmaking provides an attractive counterweight to Hollywood’s embrace of AI. One More Thing DANA SMITH Taiwan’s “silicon shield” could be weakening Taiwan produces the majority of the world’s semiconductors and more than 90% of the most advanced chips needed for AI applications. Many believe that’s helped deter China from invading the island. But now some Taiwan specialists and citizens are worried that this “silicon shield” is cracking. Facing pressure from Washington, TSMC—the world’s largest chipmaker—is expanding manufacturing abroad. In Taiwan, there are worries that this will dilute the company’s power at home, making the US and other countries less inclined to defend the island. Find out why Taiwan’s chipmaking dominance could be key to its future security. —Johanna M. Costigan
We can still have nice things A place for comfort, fun, and distraction to brighten up your day. (Got any ideas? Drop me a line.) + Thrifty filmmakers have masterfully recreated Star Wars on a $10 budget.+ A man discovered squirrels hug and kiss their loved ones in the privacy of their homes.+ Toronto’s floating waterfront store is reimagining one of the most familiar spaces across cultures.+ These animations of Sesame Street characters performing classic tracks like Underworld’s “Born Slippy” will brighten up your day.

EXECUTIVE SUMMARY When NASA’s Nancy Grace Roman Space Telescope launches, as early as the end of next month, it will attempt one of astronomy’s most precise disappearing acts to date. The telescope will carry the first space-bound “active” coronagraph, an instrument that effectively erases most of the light from a star during photography. It will allow astronomers to take the first pictures of planets orbiting other stars that are similar to those in our solar system. Ultimately, it could pave the way for a future mission that could snap the first photos of Earth-like worlds. “I hope it’s remembered for it being that critical stepping stone for … finding Earth 2.0,” says Brandon Creager, the instrument’s lead mechanical engineer at NASA’s Jet Propulsion Laboratory (JPL). Named after Nancy Grace Roman, NASA’s first chief of astronomy, this new telescope will carry a roughly 300-megapixel wide-field camera that will enable it to capture images about 100 times larger than the Hubble Space Telescope’s widest exposures at a similar resolution.
These capabilities will help astronomers unpack the mysterious identities of dark matter and dark energy—and to detect around 100,000 new exoplanets, planets outside our solar system, whose presence can be inferred from the way they distort the starlight of more distant stars. Javier Viaña, a research scientist at Harvard who has had two projects selected for Roman’s highly competitive first year of observing, compares the leap to moving from “interviewing a handful of people” to “conducting a global census.” Another camera will use the coronagraph, blocking out a star’s light as it observes one stellar system at a time. The instrument will allow astronomers an unprecedented look at the space around stars, enabling them to see smaller, dimmer, and more close-in exoplanets. “It’s giving us the ability to see planets that we haven’t been able to physically see before,” says Creager.
The anatomy of a vanishing trick Coronagraphs in space aren’t new. But earlier incarnations, such as those currently aboard Hubble and the James Webb Space Telescope, use a stationary system to block a star’s blinding light. The approach does help, but it’s a bit like putting your thumb over a flashlight while searching a dark room for a firefly. Though the bulb vanishes, stray glare can still escape and overwhelm the light of the insect. Inside a telescope, that glare can come from light leaking around the edges of machinery or from minuscule imperfections in mirrors and coatings that can scatter starlight into speckles. All this can hide, or even impersonate, a planet. Roman’s coronagraph, however, will attempt something completely unseen in space telescopes until this year: Before each observation, it will measure that leftover light and try to suppress it, a technique known as active wavefront control. The telescope is able to do this because it contains two deformable mirrors. Each has a 48-by-48 checkerboard of actuators (tiny pistons) beneath a thin, deformable sheet of glass. Applying a small amount of voltage makes the actuators contract and tug their patches of mirror slightly backward, like thousands of microscopic fingers delicately sculpting a surface. The effect is very subtle: Each patch of mirror can deform by up to 0.5 micrometers, or about one-fourth the size of an E. coli bacterium, and in increments as small as approximately 10 picometers. That’s about a tenth the diameter of a hydrogen atom, says Ilya Poberezhskiy, the instrument’s project systems engineer at JPL. The actuators allow the mirrors to create an “active wavefront,” where each component is moved to the perfect position to cancel out incoming waves of unwanted light—a bit like a pair of noise-canceling headphones, but for light instead of sound. The “canceled-out” light creates a “doughnut-shaped region around the star where we suppress starlight and where we’re hoping to see exoplanets,” says Poberezhskiy. Compared with current space-based coronagraphs, the system is expected to improve sensitivity to exoplanets against the glare of their host stars by a factor of up to 1,000, revealing planets that would have been far too faint to detect before. Like Hubble and JWST, Roman also uses masks, patterned plates placed in the path of the light that are designed to block the photons that run into them. One tool in Roman’s mask arsenal is “silicon grass,” a thicket of microscopic spikes on some masks that can be used in certain configurations to absorb photons so they don’t bounce around the telescope and accidentally reach a detector. Light entering the forest bounces deeper and deeper between the blades and gets trapped instead of reflecting back toward the camera. “Once the light gets into there, it never gets out,” Poberezhskiy says. The mirrors and masks form a succession of gates and hedges to guide as much of the preserved planetary light as possible toward the final detector.

Alien Jupiters This elaborate setup could open a new chapter in the direct imaging of exoplanets. Nearly all exoplanets photographed so far are oversize youngsters that are nothing like the residents of our solar system: several times the mass of Jupiter, still glowing with the heat left over from their birth, and orbiting tens or hundreds of times farther from their star than the Earth is from the sun. This is because they are relatively easy to see. Their size, warmth, and distance from their parent star makes them shine brightly in infrared light, far away from the worst of the stellar glare. Roman, however, could directly image a true Jupiter analogue—a planet similar to Jupiter in mass and circling a sunlike star a few times farther out than Earth is from our sun. Unlike the hot Jupiters we can see now, this one would be a much more mature gas giant like ours, primarily reflecting its parent star’s light after billions of years of cooling instead of heavily emitting its own. Astronomers have been able to infer the existence of such planets from the gravitational wobble they impart to the star. Roman instead will collect starlight reflected from the planet itself. “We’re not looking at the star. We’re not looking at the effect of the planet on the star,” says Meredith MacGregor, a professor of astronomy at Johns Hopkins who has also secured an observing program. “We are actually looking at the planet, and that is super powerful.” Once this instrument becomes available, it will become the scientists’ turn to do their jobs. “I’m honestly a little terrified about how we’re all going to deal with it, because I think it’s just so much data,” MacGregor says. “I think people will legitimately still be working on Roman data for decades.” But don’t expect to see a 4K photo of an alien Jupiter in the coming months. Roman will not be able to resolve such a planet into a solid globe—at best, it will likely resemble a smattering of pixels. Still, that will be enough, MacGregor says, as Roman can then use the coronagraph to get information on the various wavelengths of light from the planet, which can tell astronomers about its atmospheric chemistry. “You’re taking something that’s a point of light and turning it into an actual world,” she says, “because if you know that about its atmosphere, now you know something about the surface of the planet and the possibility of life being on that planet, right? So that’s a big step.” During its first observations, scientists and engineers will see whether they can hold a star at the very center of the coronagraph’s masks, shape the mirrors, “dig” the dark doughnut (as Poberezhskiy describes it), and then maintain everything as the spacecraft moves through space and actively changes temperature. The results will inform NASA’s proposed Habitable Worlds Observatory, the daydream of many an exoplanet astronomer, which will in theory be able to separate the light of an Earthlike planet from that of a sunlike star, over 10 billion times brighter. Creager, who has worked on the instrument since 2018, is proud of the achievement: “Not too many people get to say, ‘I built something and it’s taking a picture of a planet that’s at a star that’s 50 light-years away or 100 light-years away.’” He imagines the moment he and his team will be able to look at the first image as it arrives: “Yes, we did that.” While the planet may show up only as a tiny dot, Roman’s achievement will be the darkness engineered around it.

Google has invested in cybersecurity for years, pioneering automated vulnerability discovery to secure the world’s codebases. Tools like CodeMender, our code security agent, can automatically find and fix critical software vulnerabilities. But as AI agents become more capable at finding vulnerabilities faster than defenders can fix them, addressing this global threat requires a highly capable, affordable, and scalable approach.Today, we’re expanding our longtime efforts to better prepare defenders by introducing Gemini 3.5 Flash Cyber, our lightweight cybersecurity model built on top of 3.5 Flash and fine-tuned to find, validate, and patch vulnerabilities quickly and efficient, making it more effective at these tasks than Gemini’s mainline Flash models.Flash’s performance and efficiency makes it an ideal foundation for our cybersecurity model efforts. By building on top of Flash, 3.5 Flash Cyber offers a cost-efficient and highly capable alternative to large, costly cybersecurity models.Given the dual-use nature of this technology, we have taken an intentional approach to how we deploy 3.5 Flash Cyber. As part of a limited-access pilot program, 3.5 Flash Cyber will be exclusively available to governments and trusted partners via CodeMender soon, expanding over time. This will give frontline defenders a head start in finding and fixing critical vulnerabilities before they can be exploited, while mitigating against broader misuse.Separately, we’re also bringing CodeMender’s foundational capabilities directly to customers with generally available Gemini models through the Gemini Enterprise Agent Platform.The search space problem: The advantage of lightweight models in code securityFinding deep-seated flaws requires exploring an immense execution search space. Relying on a single, expensive call to a massive language model can create a bottleneck. 3.5 Flash Cyber is particularly suitable for finding vulnerabilities where the agent has to scan a large codebase and analyze a large number of codepaths.CodeMender invokes 3.5 Flash Cyber multiple times, so agents can analyze vastly more code paths to discover and validate vulnerabilities. The sub-agents then produce a single, high-quality report.Thanks to its speed and affordability, 3.5 Flash Cyber can be easily integrated into frequent scans, time-sensitive launch processes or commit scanning pipelines at scale.3.5 Flash Cyber benchmark results: an efficient alternative to larger cybersecurity modelsWe tested 3.5 Flash Cyber on a variety of benchmarks. In particular, we tested 3.5 Flash Cyber on the CyberGym benchmark, which evaluates AI agents against hundreds of real-world software vulnerabilities. Leveraging the low cost of 3.5 Flash Cyber by configuring CodeMender to call 3.5 Flash Cyber up to five times for a single, final report, the overall agent achieved competitive performance against significantly larger models on CyberGym*.

Developers and customers building production AI agents need higher token efficiency, lower latency, and more reliable performance. Our Flash series of models is built to meet the sweet spot of efficiency and quality to enable scaling agentic workflows. Building on Gemini 3.5 Flash, we’re introducing new Gemini models:3.6 Flash: Our workhorse model that delivers better coding, knowledge work, and multimodal performance. According to the Artificial Analysis Index, it reduces output token usage by 17% compared to 3.5 Flash, and in some benchmarks like DeepSWE by Datacurve, we observe up to 65%, all at a lower cost per output token.3.5 Flash-Lite: Our fastest, most cost-effective 3.5-class model, delivering 350 output tokens per second according to the Artificial Analysis Index, also significantly outperforming prior Flash-Lite generations in agentic workflows.3.5 Flash Cyber in CodeMender: Successful cybersecurity applications require careful orchestration of a model alongside an agent infrastructure. We’re introducing a combination of a new, highly efficient, specialized cyber-focused model paired with our CodeMender code security agent that delivers competitive performance at the frontier.Beyond today’s releases, Gemini 3.5 Pro is currently testing with partners and we plan to make it broadly available as soon as it’s ready. In parallel, our team is already focusing on building the next generation of models. We have started our most ambitious pre-training run yet, for Gemini 4, and are excited by the progress.3.6 Flash: More efficient and better quality than 3.5 FlashGemini 3.6 Flash builds directly on developer and customer feedback from 3.5 Flash. 3.6 Flash not only delivers a step up in coding and knowledge work, but it does this while meaningfully improving token efficiency. For example, on the Artificial Analysis Index, we see 3.6 Flash consuming 17% fewer output tokens than 3.5 Flash. It also takes fewer reasoning steps and tool calls to accomplish multi-step workflows.This enhanced efficiency is also combined with a lower price than 3.5 Flash. At $1.50/1M input tokens and $7.50/1M output tokens, 3.6 Flash reduces the overall cost per agentic task, making agents more cost-effective to build and run.

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. China’s AI models have Trump’s AI world at war with itself Last weekend, several current and former advisers to President Donald Trump on AI publicly lobbed insults at the country’s leading AI companies. David Sacks branded Anthropic’s models “lobotomized” and “woke.” Emil Michael, a top Pentagon official, called OpenAI’s new head of strategic futures a “supreme village idiot.” It began because no one can agree on what to do about Kimi, a free, open-source model that Chinese AI company Moonshot launched last week. It appears to rival the intelligence of models from OpenAI and Anthropic, which are very much not free.  Every time a new smart, free model from China gets released, US companies see less reason to fork out money for models from Anthropic or OpenAI. That’s creating economic and political problems for the president—and dividing the top AI strategists in his orbit. 
Read the full story on why no one can agree what to do about Kimi. —James O’Donnell
This article is from The Algorithm, our weekly AI newsletter. Sign up to receive it in your inbox every Monday. The must-reads I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 1 Anthropic’s record $1.5 billion copyright settlement has been approvedThe plaintiffs said Anthropic used pirated works to train Claude. (Reuters $)+ And won the largest known copyright payout in history. (Engadget)+ Yet many authors and creators still don’t view it as a win. (TechCrunch)+ But AI copyright anxiety could limit creativity. (MIT Technology Review) 2 The Trump administration is weighing a ban on Chinese AI modelsThe launch of Kimi K3 has revived calls for restrictions. (Axios)+ But officials are divided on the proposals. (Fast Company)+ China’s bet on open-source is paying off. (MIT Technology Review) 3 China is mulling tighter export controls on AI models and chipsIt wants to stop the West from acquiring its tech and startups. (FT $)+ Beijing has held talks with tech firms about potential restrictions. (Reuters $) 4 Trump’s AI safety head has resigned after just three monthsChris Fall had led CAISI, the federal AI Safety Institute, since April. (Axios)+ No reason was given for his exit. (CNBC) 5 Google is working on a new chip to run Gemini models more efficiently The chip, called “Frozen V2,” may be deployed in 2028. (Information $)+ Alphabet stock popped on the report. (CNBC)6 New Orleans police have explored arming drones with weaponsA draft drone manual paves the way for weaponised quadcopters. (404 Media)+ Shoplifters could soon be chased by drones. (MIT Technology Review) 7 The EU has handed AliExpress a record fine over unsafe product salesThe €550 million fine is the largest-ever under the Digital Services Act. (BBC)+ Alibaba has vowed to appeal the fine. (SCMP)8 Election advice from AI chatbots is “inaccurate and unreliable”That’s the conclusion from tests in Hungary earlier this year. (Guardian)9 Red light therapy is showing promise for healing and healthy agingBetter skin and reduced vision loss are also on the cards. (Economist $)10 Neill Blomkamp’s new horror clip is all AI-generated—and it sucksThe acclaimed director wants to make “a full feature in this format.” (Gizmodo) Quote of the day “This would be a terribly self-defeating form of intervention if it were to happen.”  —Tech investor Chamath Palihapitiya slams plans to restrict Chinese AI models in a post on X. One More Thing AKILAH TOWNSEND Inside Chicago’s surveillance panopticon Early on the morning of September 2, 2024, four people were shot and killed on a westbound train in Chicago. Police swiftly activated a digital dragnet—a surveillance network that connects thousands of cameras across the city—and arrested the suspect just 90 minutes later.

Law enforcement and security advocates say this vast monitoring system protects public safety and works well. But activists and many residents say it’s a surveillance panopticon that creates a chilling effect on behavior and violates guarantees of privacy and free speech. Go inside the surveillance network that’s dividing Chicago. —Rod McCullom We can still have nice things A place for comfort, fun, and distraction to brighten up your day. (Got any ideas? Drop me a line.) + NASA has shared a stunning timelapse video of the Psyche spacecraft’s view of Mars.+ This comparison of American and European Urbanism shows good city design is a choice.+ Musician Luca Stricagnoli recently performed a marvellous acoustic guitar medley of Prodigy songs.+ Two Australian paddleboarders saved a stranded wallaby after it was swept out to sea—and caught the whole rescue on video.