The terminal-based coding tool is powered by a new AI model, Muse Spark 1.2.

• Ukraine develops ground robot firing nets against incoming FPV drone attacks
• VORON combines drone interception with logistics and battlefield evacuation capabilities effectively
• Net launchers attempt physical drone captures instead of explosive aerial interceptions

Ukrainian firm SMART BIRDS has introduced an Unmanned Ground Vehicle (UGV) called VORON, built specifically to intercept first-person view drones from multiple directions simultaneously.

The system relies on Pavuk net launchers, a defensive mechanism designed to trap incoming drones before they reach their intended target.

A one-line command in your macOS terminal can get you access to Meta’s Muse Code, which aims to be a transparent AI coding tool that can work across large repositories.

There are already coding agents like Claude Code and ChatGPT Codex available for macOS, but Meta wants to enter the ring with its latest AI toolset. Unlike the others, it doesn’t have an app interface and runs through the Terminal.

According to an announcement post from Meta, Muse Code can take on complex software engineering tasks across large repositories. It is capable of planning changes, writing code, and validating the results while coordinating multiple persistent subagents.

As always with these AI announcements, remember that the language being used attempts to anthropomorphize the tools to be more human-like. Nothing about an AI behaves like a human — they don’t think, reason, organize, sympathize, or understand.

AI is a tool, and if Muse Code sounds like it could help you develop software, it might be a particularly useful tool. Developers have shared just how useful having a coding agent available can be, especially for troubleshooting bugs.

To install Muse Code, you’ll just need to paste in a single command into Terminal:

curl -fsSL https://dev.meta.ai/install.sh | bash

Of course, this isn’t free. Those that install Muse Code will start on Meta’s contributor tier. Developers join with a pay-as-you-go option which charges $1.25 per million tokens in input and $4.25 per million tokens of output.

The Muse Code announcement was paired with the release of Muse Spark 1.2, which was trained with coding assistance in mind. Meta says the training included rejection-sampled harness trajectories and recipe optimizations for goals, compaction, and subagents.

Choose your AI partner

Meta’s inevitable introduction of a coding agent was a long time coming. The company has been poaching Apple employees in its expensive chase for so-called superintelligence.

Muse Code is also another revenue stream to cover the incredible costs of AI and research around it. Meta previously tied some of its premium subscriptions to AI tool use as well.

There are several AI coding tools to choose from, so it will be interesting to observe if Meta can make a dent in the market. Not having a direct UI and interfacing via Terminal could be a problem for some.

Then there’s the privacy aspect. Meta is known for its horrific history of scraping every piece of data it can from users, and while it might have safeguards in place for its AI tools, it seems unwise to trust Meta software installed with access to so much information.

Prime Video and Samsung have decided that the HDR format war was not quite confusing enough.

Beginning in August 2026, Prime Video will become the first streaming service to offer HDR10+ Advanced on supported movies and television programs worldwide. The new format will initially be available through the Prime Video app on select Samsung 2026 televisions.

The promise is brighter and more detailed HDR, improved shadow reproduction and motion processing that changes according to what is happening in each scene.

The reality is that Amazon and Samsung have not revealed which titles will support it, precisely when the rollout begins or whether owners of older Samsung televisions will eventually be invited to the party.

Progress apparently still requires a scavenger hunt.

What Is HDR10+ Advanced?

Standard HDR10+ already uses dynamic metadata to adjust brightness, contrast and tone mapping on a scene by scene or frame by frame basis. That allows a compatible television to handle a dark interior differently from a sun drenched exterior instead of applying one set of HDR instructions across an entire movie.

HDR10+ Advanced expands that tool kit with six primary features:

• Enhanced overall brightness
• Intelligent motion smoothing
• Local tone mapping
• Genre based optimization
• Advanced color control
• Adaptive cloud gaming

The format supports brightness metadata up to 10,000 nits and color depth of up to 16 bits at the specification level, although current streaming video remains limited by the practical capabilities of existing displays and codecs.

Prime Video’s initial rollout is focused primarily on enhanced brightness and intelligent motion smoothing.

Enhanced Overall Brightness uses additional metadata to help capable televisions make better use of their available light output. Samsung says AI driven tone mapping can preserve shadow detail in darker scenes while allowing sports, action movies and other bright material to use more of a premium television’s brightness capability.

That could be useful on newer OLED, MiniLED and Micro RGB televisions capable of reaching substantially higher brightness levels than earlier generations.

It does not mean that every program will suddenly resemble a television showroom with the brightness control welded to its maximum setting. The goal is to use the available brightness more intelligently, not simply make everything brighter.

At least that is the theory.

Can Intelligent Motion Smoothing Avoid the Soap Opera Effect?

Motion smoothing remains one of the most divisive forms of television processing.

It can make sports, camera pans and fast moving action look cleaner, but excessive frame interpolation can also make an expensive movie resemble a daytime soap opera filmed in the back room of a furniture store.

HDR10+ Advanced attempts to address that problem with scene specific metadata. A compatible television can reduce smoothing during cinematic material while applying more processing to sports, action and other fast moving scenes where cleaner motion may be desirable.

That sounds far more sensible than forcing viewers to choose one motion setting for everything.

Whether it actually works will depend on how accurately the content is tagged, how Prime Video encodes it and how Samsung televisions interpret those instructions. Until we can test it, “intelligent” remains a job title rather than a performance guarantee.

Filmmaker Mode Is Not Invited

There is one significant catch.

Samsung confirms that HDR10+ Advanced will not operate when Filmmaker Mode is enabled.

Filmmaker Mode is designed to disable or reduce many forms of television processing so movies and television programs can be displayed closer to the creators’ original intentions. HDR10+ Advanced also claims to preserve creative intent, but requires Filmmaker Mode to be turned off.

That leaves viewers with an unusual choice: use the picture mode specifically designed for movies or activate the new HDR format designed to make movies look better.

Someone may want to workshop that.

It is also notable that HDR10+ Adaptive, introduced several years ago, was promoted as being compatible with Filmmaker Mode. The Advanced version adds more sophisticated motion and genre based processing, which may explain the conflict, but Samsung has not provided a detailed technical explanation.

Which Samsung TVs Support HDR10+ Advanced?

Samsung says the Prime Video rollout will begin on its 2026 television lineup, although the company’s U.S. announcement refers more cautiously to select 2026 models.

Samsung has already introduced HDR10+ Advanced support across portions of its 2026 OLED, Neo QLED and Micro RGB ranges, but the Prime Video announcement does not include a definitive model by model compatibility list. Owners should check the specifications and firmware status of their individual television rather than assuming every 2026 Samsung display is supported.

There is also no confirmation that 2025 or older Samsung televisions will receive HDR10+ Advanced through a firmware update.

Support is expected to spread beyond Samsung. HDR10+ Technologies says Roku intends to deploy the format across its platform, while MediaTek has also announced chipset support. Neither company has provided a product list or rollout date.

Why This Matters for Samsung Owners

Samsung continues to support HDR10 and HDR10+ rather than Dolby Vision across its television lineup, making the success of HDR10+ considerably more important to Samsung owners.

Prime Video has supported the original HDR10+ format since 2017 and was the first major streaming service to adopt it. Netflix, Disney+ and Hulu have subsequently expanded their own HDR10+ support, giving Samsung television owners access to a much broader selection of dynamic HDR programming than they had only a few years ago.

HDR10+ Advanced is also royalty free, which could make it attractive to television manufacturers, streaming platforms and hardware companies looking for an alternative to Dolby Vision and its licensing costs. Samsung says the broader HDR10+ ecosystem now includes 183 adopter companies and more than 22,000 certified products.

The Bottom Line

HDR10+ Advanced could deliver meaningful picture improvements on newer premium televisions, particularly in scenes that combine intense highlights with dark shadow detail. Scene specific motion instructions also offer a more intelligent alternative to leaving one motion setting enabled for every type of content.

But the launch arrives with several unresolved questions.

Prime Video has not named any supported movies or shows. Samsung has not published a complete compatibility list. Older television support remains unknown, and HDR10+ Advanced cannot be used with Filmmaker Mode.

Samsung and Amazon have created a potentially smarter HDR experience. Now they need to explain why movie enthusiasts must disable the picture mode created specifically for movie enthusiasts to see it.

For more information: hdr10plus.org/advanced/

Related Reading:

Huawei just released the MateBook Pro S, a 14.2-inch laptop that weighs 798 grams and measures only 11.9 millimeters thick. That puts it among the lightest full-metal machines in its size class, lighter than many 13-inch models by a noticeable margin. The magnesium-lithium body keeps the whole package easy to carry all day, and it comes in several finishes including Midsummer Purple, Dawn Yellow, Smoke Gray, Velvet White, and Feather Black.

A 14.2-inch flexible OLED display sits right in the center of this slim laptop. It has a crisper-than-crisp 3,120 by 2,080 pixel resolution in that ‘document-friendly’ 3:2 ratio, and it refreshes at 120 times per second, boasting 1,600 nits at its brightest points, a color gamut that covers the entire P3 range, and even ten-point touch. Let’s not forget the two million to one contrast ratio. That’s some very impressive screen technology, but the real magic isn’t in the numbers, but in how those pixels are arranged.

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Huawei refers to this screen as their “privacy display,” and it’s a game changer. The deal is that each part contains two entire sets of light-emitting pixels, and this is what happens when you flick a physical switch on the side. The first set covers standard viewing, so your coworkers can crowd around the screen without issue, but the second set kicks in and light travels practically straight ahead. So, if someone looks in from the side, they’ll see a dark or virtually black surface, but the person in front gets to keep the full brightness, resolution, and color accuracy intact; no extra film, no software dimming, just 100 percent pixel power. There is a camera on board that is continually on the watch for someone attempting to peek over their shoulder, and when this occurs, the system gently asks the owner if they want to change to private mode. Now, the switch is easy, works instantaneously, and is entirely controlled by hardware, which is a significant improvement over add-on filters or reduced pixel counts.

So, what makes this whole thing work? Huawei’s proprietary Kirin XE90 chip is the brains of the operation. It has a 9-core ARM CPU that boasts a 23% increase in single-core speed, 25% higher energy efficiency, and a 40% more powerful neural processing work than the previous model. We’re also talking about a sustained output of roughly 20 watts, thanks to two fans and improved heat distribution. You can have up to 32GB of RAM and 1TB of storage, and you’re running HarmonyOS 6.1, which includes some useful tools for creating documents, filling out forms, and making rudimentary web pages. There are six microphones (yes, six!), four speakers for audio, and a pair of 1080p cameras in the front and back. Finally, a fingerprint sensor is buried away inside the power button.

According to Huawei, the battery capacity is a reasonable 54 watt-hours, which is enough to power an 18-hour marathon of 1080p movie streaming. Power it up with one of the two USB-C connections, which can handle a speedy recharge of up to 66 watts. The greatest part is that those same ports can also be used to charge other devices. For wireless networking, they use no fewer than four antennas and Wi-Fi 7 to deliver the kind of long-range connections you’d expect from a high-end device, with Huawei claiming they can reach up to a kilometer under perfect conditions.

The base model starts at 7,999 yuan ($1,185) and includes 16 GB of memory and 512 GB of storage. If you want a privacy screen, which sounds like a fairly handy feature, you’ll have to pay a premium of 10,299 yuan ($1,526) for 24 GB of RAM and 512 GB of storage, with more fancier configurations available if you’re willing to spend. We should expect the machine to be ready for purchase in China between mid and late August, but there is still a wait for those outside of China at this moment, and it may be longer than that, given that it runs on ARM-plus-HarmonyOS rather than Windows.
[Source]

Content warning: This article discusses self-harm.

On Tuesday night, the gossip blogger Perez Hilton, aka Mario Lavandeira Jr., was hospitalized after showing up on a TikTok livestream naked, covered in a red fluid that looked like blood, and wielding what appeared to be a knife.

The stream—which TikTok claims lasted around 15 minutes—prompted concern from horrified viewers, who immediately contacted the police. But it also raised questions about how TikTok could have allowed the stream to continue for so long without intervention.

TikTok spokesperson Jamie Favazza told WIRED via email that TikTok’s automated moderation systems flagged the livestream minutes after it started, but a “moderator error” caused a delay in its removal as well as the account’s subsequent ban. Favazza also shared that TikTok contacted law enforcement shortly after the livestream was flagged.

The platform did not respond to follow-up questions regarding the nature of this moderator error or exactly how long the error delayed the removal of the livestream.

During Lavandeira’s stream, the Miami-Dade County Sheriff’s Office received “multiple calls regarding an individual who was livestreaming acts of self-harm on social media,” dispatching a crisis response unit and mental health professionals to his home, according to Samantha Choon, a detective with the sheriff’s office. A public information officer for the sheriff’s office separately confirmed to WIRED over the phone that the individual in question was Lavandeira.

TikTok’s official content guidelines prohibit “content that shows, promotes, or provides instructions for suicide or self-harm” as well as “graphic, violent, or disturbing content.” The platform has said that it uses a “combination” of automated systems and human moderation to screen for such content. The company entered into a new ownership structure in January, with a newly formed joint venture assuming responsibility for content moderation and data security in the US.

Yet following news that Lavandeira was hospitalized, many on social media questioned why the platform left the livestream up for long enough that thousands of viewers saw it, given its content guidelines. Some speculated that the platform left the stream up for 30 minutes or more before it banned the account. Favazza denied this to WIRED, saying the stream was up for “half” that time and that Perez’s subsequent streams were cut within 90 seconds.

Nonetheless, this is not the first time that TikTok, as well as livestreaming platforms in general, have been accused of failing to properly moderate content featuring suicide or self-harm. In 2020, The Intercept reported that a young Brazilian man had livestreamed his own suicide on the platform. Later that year, TikTok also struggled to remove graphic clips of the final moments of Ronnie McNutt, who went viral after taking his own life on Facebook Live.

In response to a request for comment from WIRED, Dante Rusciolelli, Lavandeira’s manager and the CEO of Golden Artists Entertainment, said Lavandeira’s team was “not in a position to comment on TikTok’s internal policies, moderation decisions, or its communications with law enforcement.”

“Our focus remains entirely on Perez’s health and well-being,” Rusciolelli added via email. “We appreciate the concern surrounding this situation and respectfully ask that his privacy be honored while he receives the care and support he needs.”

Additional reporting by Manisha Krishnan.

If you or someone you know is struggling with thoughts of self-harm or suicide, call the Suicide and Crisis Lifeline at 988 for support.

Apple’s employee lottery for the September iPhone launch doesn’t mean it will be a return to a live-presented event. It’ll probably be the same pre-recorded presentation with press in the room as usual.

It’s barely a month away from Apple’s regular fall event, which will see the launch of products like the iPhone 18 Pro, the iPhone Fold, and other long-rumored items. It is always a major event, with most of the tech world paying close attention.

However, with the prospect of a new CEO at the helm, there are also expectations of other changes. That can also include the September event itself.

The problem is, it probably won’t be that different from what we’ve already got. Even with John Ternus saying “Good Morning” to the audience.

Tweet expectations

On Tuesday, Bloomberg posted about an internal memo within Apple, inviting retail employees to enter a lottery. This is to select workers across the country to staff Apple’s usual in-person event.

The tasks they will take range from organizing lines, checking in guests, greeting attendees, offering directions, and supporting security teams, the memo stated. It also indicated that the event will take place during the first half of September.

The probable date for the event is September 9, since Labor Day is September 7, and it would give attendees a workday to travel.

All of this is completely unsurprising for an Apple Event. However, extrapolations by others online are raising expectations a little too high.

Live events always have a more natural atmosphere. Pre-recorded presentations have been a bit boring for years. We can’t wait for #AppleEvent! pic.twitter.com/vCoInY6r7v

— Marcin Flov (@fl00vyee) August 5, 2026

Mark Gurman’s post to X on Tuesday promoting the retail employee lottery story has its fair share of comments. Among expectations for the iPhone Fold and wondering if Apple’s paying for the employees to be flown out, some are indicating that they hope it will be a live event.

“I’ve been waiting for the day they went back to in-person,” writes one commenter. “Each year that went by I was getting worried they’d never return.”

There was praise for the “natural atmosphere” of live events, as well as some mourning the slick pre-recorded announcements as if they are already gone.

While a little reminiscing doesn’t hurt, the growing expectation of an in-person event with a live component isn’t reasonable.

Necessity becomes habit

Apple’s prerecorded announcements commenced in 2020, long after the last live-presented iPhone launch in late 2019.

The company had a very good reason not to hold its signature live presentation: COVID-19. It simply couldn’t invite the world’s media to an in-person meet-up and a live on-stage Apple Park presentation for health reasons.

At the time, Apple had few options, but it still had to hold a special event. A live presentation under lockdown conditions would’ve been possible, but the restrictions posed many production problems, let alone for a live stream on the Internet.

Prerecording the presentation was the way to go. It allowed Apple to work around the necessary health restrictions, while still providing a slick presentation to an awaiting audience.

After the event aired, and the world saw what Apple could produce in advance, it gave Apple license to keep on doing it. Indeed, as the world tried to return to normal post-COVID, everyone tried to stay safe, and that meant Apple could continue with the prerecorded messages a while longer.

Eventually, after the world opened back up and the danger was over, Apple could’ve taken the opportunity to go back to live events. Except it didn’t.

After a few prerecorded presentations, it became the norm for Apple. It avoided the problems of live broadcasting and presenting, like waiting for cheers and applause to die down.

There were no issues with live tech demos, as you would have a perfect on-screen example prepared ahead of time. It also meant Apple could be as TV-like and creative with graphics as it wanted to, which a stage simply couldn’t match.

Sticking with it was a necessity. Now, it’s beneficial.

But the employee lottery…

Regular observers of Apple’s special events will have noticed a pattern over the last few years. That is, while there’s a prepared presentation for people to see online, there’s an off-line, on-site component as well.

For Apple events and the WWDC keynote, that manifests as an event at Apple Park. Media and guests are invited to attend to watch the presentation, as well as to hear and participate in some other on-site activities.

When it comes to a product-based event, that means setting up multiple areas at Apple Park for attendees to try out the just-announced items. Your favorite tech YouTubers have frequently aired travelogs about their visit to Apple Park, so it is a well-known process.

Since there’s a mass of people suddenly appearing at Apple Park, which is usually occupied by employees who don’t usually talk face-to-face with outsiders on Apple matters, help is needed. For Apple, the obvious move is to tap into its army of customer-facing workers who are already well-versed in answering questions.

A lottery to win a trip to the headquarters is also a training and employee loyalty-building opportunity as well.

Apple has held these lotteries for a few years now, and they have all helped staff the in-person component of events at Apple Park. Just not one that Apple chooses to broadcast to the public.

“It’s the hope that kills you”

The talk about live events can be seen as being hopeful that Apple will return to that format down the road. It’s entirely possible for that to happen, but not a certainty.

Apple has found that it can create the ideal presentation for its needs. Polished like the company’s brand image, information-dense, and highly entertaining as well.

It has no incentive to divert away from this strategy at all. And on a pre-record, there’s no chance of something critical failing.

There’s no need for smoke and mirrors, like Steve Jobs miraculously pulled off with the original iPhone.

John Ternus will be CEO in time for Apple’s fall events. Expect a lot of screen time from him – Image Credit: Apple

If John Ternus is inclined to return to live presentations once again, it would require a lot of changes from Apple’s production pipeline. Not least the prospect of Apple executives walking on stage and willing for everything to go smoothly.

Ternus could make that call. But, since it’s the very start of his tenure, the last thing he needs is for his first event to be live and error-prone.

A few events down the road, he may be confident enough to go live. But days after taking the CEO seat, it would be an insane move.

Agentic AI has permanently changed cybersecurity by making it quicker and easier to discover vulnerabilities in software and fix them—or develop so-called exploits to weaponize them. But longtime web security researcher James Kettle wanted to look beyond the bug-hunting apocalypse to explore a question that has taken on even more urgency as major AI organizations disclose real-world examples of rogue AI hacking: Can agentic AI develop novel, abstract hacking methods, from concept through to practical attacks?

At the Black Hat security conference in Las Vegas on Wednesday, Kettle presented his findings, which illustrate both AI’s rapidly advancing cybersecurity capabilities and its limitations. For now, the answer to Kettle’s question is nuanced. He concluded that AI is perhaps minimally capable but extremely limited in its ability to devise new attack paths in a fully autonomous way. Importantly, though, when paired with human guidance and insight in key moments, Kettle found that AI is an extremely powerful partner in conceptualizing and uncovering new strategies for hacking.

After spending years researching web security vulnerabilities, Kettle now says he has uncovered an entirely new area of potential vulnerability—dubbed Shared-Parser Confusion—as the result of an AI revelation about web servers using shared code to process both requests and responses.

“This is an absolutely massive deal, because if you think about it, requests to a website are completely untrusted, they could be anything, but responses are trusted,” Kettle told WIRED ahead of his conference talk. “So this is a major attack surface and potentially spills into a lot of different attack types.”

The finding came out of months of experiments that began in September 2025 using Anthropic and OpenAI’s latest models at the time. Kettle wanted to explore AI’s ability to do theoretical security research, but quickly realized that one obstacle was that the systems were attempting to pass existing research off as original by returning findings about extremely esoteric topics that were difficult to vet. With this in mind, he decided to scope his tests more narrowly so the AI systems were working within his own area of web security expertise. This way he had total command of the material and knew that AI couldn’t trick him. Additionally, Kettle realized that by synthesizing his own research methodology and training models on it, he could probe deeper into what the systems were capable of extrapolating on their own.

“I’m interested in pushing AI to the absolute limit to see where it fails and where you need a human,” Kettle says. “There are still very few people talking about where the limits are, especially in the security space, because there aren’t incentives to talk about that angle. Everyone wants to be seen as AI native, not talk about where their system falls apart completely.”

As Kettle honed his experiments—providing models with more methodological data and more refined parameters—and as time passed and more powerful models debuted, he says the systems had more and more findings at a rate far surpassing his own, creating what he describes as a productive research feedback loop.

“It was really interesting going through the process. It would have notable findings maybe every two days without me even logging into the system, to the point that it was making me anxious,” Kettle says, “like I almost don’t want to know. It was so many research leads that you have FOMO about not exploring all of them, so it forces you to automate more analysis.”

In addition to finding more proven examples of certain vulnerabilities in a few months than Kettle could likely find in a few years, he also hoped that the AI system could find an entire novel class of those types of bugs. And in a way it did succeed, he says, but the finding related to an extremely rare type of bug and was not actually exploitable in the one vulnerable target available. Kettle emphasizes, though, that the Shared-Parser Confusion finding was so significant, even though it was a human/AI collaboration, because it illustrates the reality of how AI systems can contribute most powerfully to cybersecurity work right now for both defensive and offensive hacking.

“It wasn’t able to prove this itself, but it analyzed some real, proven findings and came up with the hypothesis, and I evaluated it and confirmed it,” Kettle says. “That’s probably going to be the discovery that has the biggest long-term impact. It couldn’t do that on its own, but I would never have found that on my own for sure. Even if you gave me the single line from the [documentation], I wouldn’t have seen it. But together we managed to find it.”

Jeff Dean, one of the longest-serving and most influential executives at Google, is stepping down from the search giant to launch his own AI startup.

Coming with him as co-founders are several other top researchers at the company, including Sanjay Ghemawat, a top engineer and senior fellow at Google; Quoc Le, a key AI researcher and founding member of Google Brain; and Oriol Vinyals, a senior research scientist at Google DeepMind. Dean reportedly plans to serve as CEO.

Together, the group is starting Discovery Loop, a public benefit corporation that seeks to use AI to turbo-charge scientific research.

Discovery Loop says it plans to use high-octane algorithms to initiate and iterate thousands of experiments simultaneously, with the goal of partially automating the research process and expanding the scale at which experimentation can be conducted.

The startup is also interested in using AI to help create more powerful AI (a process known as recursive self-improvement), which would cut human iteration out of the loop entirely.

“While science and engineering have tremendously advanced society over past centuries, progress has traditionally relied on slow, sequential human iterations, creating a significant bottleneck,” the company said in a press release. “Discovery Loop is developing advanced AI systems that leverage massive computational scale to fundamentally transform the speed and efficiency of innovation by automating complete experimental loops.”

Using AI to accelerate scientific discovery has been a key interest of the science and tech communities for many years, but until recently, it remained a largely experimental field with limited commercial application.

The company has received financial support from a number of different sources, including Google’s parent company Alphabet. The initial funding round is being co-led by Radical Ventures and Khosla Ventures, the company announced Wednesday. Kleiner Perkins, Lightspeed, and Doerr Capital also participated.

“The next great frontier for AI is to go beyond answering questions and to begin making discoveries,” the founding team said in a joint statement. “By fundamentally accelerating how engineering and scientific discovery are conducted, we can deliver the benefits of transformative technologies to the world far sooner.”

Dean has worked at Google since 1999 and was Google’s 30th employee. Over the years, he has contributed to Google search’s core infrastructure, including its crawling and indexing system and its query-serving system. He has also had a significant impact on Google Gemini’s multimodal models and played a leading role in the company’s early AI research.

“We think there is opportunity for AI to more fully automate what has traditionally been a very human-intensive experimental loop,” Dean told the New York Times. “You will get both a higher quantity and a higher quality of experiments, and that will lead to scientific breakthroughs and advances.”