Google Photos continues to get new and improved features on a regular basis, and one of the most recent Android updates has focused on video editing. Even if you don’t have the latest Pixel 9 phone (which is required if you want to try out the weird new Reimagine tool), you can now speed up, slow down, and enhance your clips with a few taps as well as trim them down more easily.
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How to use the latest AI video editing tools in Google Photos
/cdn.vox-cdn.com/uploads/chorus_asset/file/23952250/HT012_google_0006.jpg?ssl=1 "How to use the latest AI video editing tools in Google Photos")
You can also expect what Google calls “AI-powered video presets” on both the Android and iOS versions of Google Photos. After the app algorithm analyzes your clips, you get a choice of effects — trims, zooms, slow-mos — you can apply with a tap. The app takes the role of director and chooses where and how these tweaks should be applied.
When the changes arrive on your phone, you’ll also notice the interface is a little cleaner, with larger icons and bigger text that make it more obvious what you’re doing. The idea is it’s more straightforward than ever to quickly apply a few edits before sharing your clips, without having to open up a separate editor on your phone or computer.
Trim tool
First up, we have what Google describes as “improved controls” for cutting out extraneous footage at the start and end of your clips — though, to my eyes, there’s not a huge amount that’s different here compared to the previous version of the trim tool.
The handles at each end of the clip are a little bigger and thicker, making them easier to hit with a finger press. You also get a timestamp shown onscreen as you drag those handles around, so overall, the edits are a little easier to apply.
The trim tool shows up automatically as soon as you edit a video, and you can get back to it by tapping the Video button.
- Drag the left-hand handle to change where the video starts.
- Drag the right-hand handle to change the video’s end point.
- Drag the white bar between the two handles to move around the clip.
- Tap the play button at any point to check your new footage.
- Choose Save copy to confirm your changes and save a separate clip.
Auto-enhance tool
Google Photos now has a new auto-enhance feature you can access, which analyzes your clip and then applies its own choice of color enhancements, while stabilizing the video at the same time.
- Tap Video then Enhance to apply the automatic enhancements.
- Tap the play button to see how the updated footage looks.
- Tap Enhance again to see the difference with and without the tweaks.
- Choose Save copy to save the enhanced video as a separate file.
If you’d rather apply the video stabilization without the color enhancements, just tap Stabilize on the Video panel of tools instead.
Speed tool
The new speed tool in Google Photos gives you more control over the pace of your videos for speeding up and slowing down the action. The effect can be applied to a specific section of your clip or all of it.
- Tap Video and then Speed to bring up the editor.
- Use the bars on the timeline to indicate where you want the effect to start and stop.
- Choose a playback speed under the timeline: from 1/4 speed to 4x the speed.
- Tap the play button to see how the video now looks.
- Choose Done, then Save copy when you’re happy with the results, to save a separate video file.
It’s not the most advanced video editing effect you’ll ever see, but considering it only takes a couple of taps on your phone screen, you can get some impressive results from it.
Video presets
Unlike the tools above, which are exclusive to Android, the AI-powered video presets are available in Google Photos for both Android and iOS. Or at least, they will be eventually — though they were announced in September, as of this writing, I haven’t yet seen the presets in the Google Photos apps on either platform.
When they do appear, the Presets button will appear between Video and Crop in the options at the bottom of the interface. Select it, and you’ll see a choice of edits you can apply with a tap: Basic cut, Slow-mo, Zoom, and Track. These will be applied as the Google Photos AI sees fit based on the video content.
The example Google gives is a skateboard video, with the action trimmed right down to a key jump, which is also slowed down. Color enhancements are applied at the same time for good measure. As before, you can preview the changes, then tap Save copy to accept the changes and save a new video file, leaving the original untouched.
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Xbox just allcapsmaxxed: Meet XBOX. This isn’t a joke; Microsoft appears to be actually rebranding Xbox to XBOX. Asha Sharma, Xbox CEO, ran a poll on X earlier this week, asking fans whether Microsoft should use Xbox or XBOX. The results were in favor of XBOX, and the company has now renamed its X account.
Curiously, the Threads and Bluesky accounts for Xbox haven’t been renamed yet, but if Microsoft is going ahead with a rebranding then I expect those will change soon. I asked Microsoft to comment on this potential Xbox rebranding and the company simply referred me to Sharma’s post.
The use of all caps for Xbox is a return to original form, though. Microsoft’s first Xbox logo for its console was all caps, and the company has favored using similar capped versions for the Xbox 360, Xbox One, and Xbox Series X / S console logos.
The apparent rebranding comes just a few weeks after Sharma scrapped Microsoft Gaming and renamed Microsoft’s gaming division back to Xbox. It’s part of Sharma’s continued promise of a “return of Xbox,” which has involved fan-focused console updates, a new Xbox logo, Game Pass pricing changes, and lots more in recent weeks.
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Artificial intelligence (AI) already shows up in your phone, your searches and plenty of apps you use every day. Now, some Silicon Valley investors are betting the machines behind those AI answers could one day run at sea.
A company called Panthalassa has raised $140 million in new funding to develop and deploy autonomous, floating AI computing nodes powered by ocean waves. The Series B round brings Panthalassa’s total funding to $210 million, a sign that investors are taking this ocean-based AI idea seriously. The round was led by Peter Thiel, the Palantir co-founder, and the company says the money will help complete a pilot manufacturing facility near Portland, Oregon. Panthalassa also plans to deploy its Ocean-3 pilot node series in the northern Pacific Ocean later in 2026.
Instead of building another giant AI data center on land, Panthalassa wants to place computing power out at sea. Ocean waves would generate electricity. Seawater would help with cooling. Onboard computing systems would process AI prompts and send the results back to land through low-Earth-orbit satellites.
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Panthalassa’s Ocean-2 prototype rides in open water during testing, giving a real-world look at the kind of floating wave-energy system behind the company’s ocean AI plan. (Panthalassa)
How AI data centers at sea could work
Panthalassa’s floating nodes are designed to capture wave motion and turn it into electricity. The company says it has spent a decade developing the technology behind its power generation, onboard computing and autonomous ocean operations. Its earlier Ocean-1, Ocean-2 and Wavehopper prototypes were tested in 2021 and 2024. Think of each node like a floating power station with AI hardware inside. Waves move the system. That motion helps drive a generator. The power then feeds the onboard chips.
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The company’s plan is to use those chips for AI inference. That is the part of AI where a model responds to your prompt after it has already been trained. In simple terms, it is what happens when you ask a chatbot a question and get an answer back. That makes the ocean plan a little easier to understand. Training massive AI models requires huge data movement and tight coordination. Answering prompts may be more realistic for a floating node, at least in some situations.
Why AI data centers are moving offshore
AI data centers need huge amounts of electricity. They also need space, cooling systems and local support from communities that may not want a massive facility nearby. Those problems have pushed companies to look for unusual answers. Ocean-based computing is one of them.
Panthalassa says its nodes would operate far from shore in wave-rich parts of the ocean. The goal is to use that wave energy directly onboard instead of sending the power back to land. “We’ve built a technology platform that operates in the planet’s most energy-dense wave regions, far from shore, and turns that resource into reliable clean power,” said Garth Sheldon-Coulson, Panthalassa’s co-founder and CEO.
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The ocean also offers cold surrounding water. That could help cool the chips onboard. Cooling is a major issue because data centers produce a lot of heat. Panthalassa is taking a different path from traditional land-based data centers. Instead of pulling more power from the grid, it wants floating nodes that generate their own electricity from waves.
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The Ocean-2 prototype sits inside a coastal facility, showing the size and shape of Panthalassa’s floating node before deployment at sea. (Panthalassa)
The satellite problem for ocean AI data centers
The ocean may help with power and cooling, but it creates another problem: connection. Traditional data centers rely on high-capacity fiber-optic connections because they need to move huge amounts of data fast. A floating node far out at sea may depend on low-Earth-orbit satellite links. That can work for some AI responses, but it may be slower and more limited than fiber.
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The challenge grows when multiple nodes need to work together. AI systems often depend on fast communication between chips, servers and storage. If those parts are floating in the ocean and talking by satellite, coordination gets harder. That means AI data centers at sea may not replace land-based data centers anytime soon. They may be better suited for certain AI tasks where the model can live onboard, and the response does not require constant back-and-forth with other machines.
Repairing floating AI nodes could be difficult
There is another practical question: What happens when something breaks? A land-based data center can send in technicians. A floating AI node in rough seas may need a ship, special equipment and the right weather window. That adds cost and delay.
Panthalassa says it is developing autonomous systems meant for harsh ocean conditions. Its press release says Ocean-3 testing is meant to demonstrate AI inference and refine manufacturing before commercial deployments in 2027. Still, the ocean is brutal. Saltwater eats away at equipment. Storms can turn a routine repair into a major operation. Constant motion also puts stress on the hardware. For this plan to work, Panthalassa will have to show that each node can keep running for years in harsh ocean conditions without frequent human repairs.
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Panthalassa’s Ocean-2 prototype is transported by barge, a reminder that building AI infrastructure at sea also means solving major deployment and maintenance challenges. (Panthalassa)
Ocean data centers have been tested before
Ocean data centers are not new. Microsoft experimented with underwater data center servers through Project Natick, including tests in 2015 and 2018. Those tests showed that sealed underwater servers could run reliably while using seawater for cooling, with Microsoft reporting a lower failure rate than comparable land-based systems. Microsoft later ended the project.
Chinese companies have also reportedly pushed ahead with underwater data center projects near Hainan and Shanghai. Keppel has explored floating data center designs in Singapore, where land constraints make the concept especially attractive. Panthalassa’s plan goes in a different direction. It combines wave power with onboard AI chips and satellite-based results. It also depends on floating nodes that would need to operate far from the kind of support a normal data center gets. That is why the idea is getting attention. It is also why skepticism is fair.
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What AI data centers at sea mean for you
For now, this will not change how your phone or computer works. You will not suddenly see a “powered by ocean waves” label on your favorite AI app. But the bigger picture affects everyone. AI needs an incredible amount of electricity. As more companies add AI tools to their products, they need more places to run those systems. That pressure can affect energy grids, water use, local battles over new data centers and even your utility bills over time.
Panthalassa argues its approach could reduce the need for new data centers and power plants on land. That could ease pressure on local communities and the grid, but the company still has to prove the system can work reliably at sea. If ocean-based AI moves beyond testing, it could also raise fresh questions about marine maintenance, environmental oversight and who controls computing infrastructure in international waters.
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Kurt’s key takeaways
Everyone is using AI on their phones and computers these days, but the heavy lifting often happens in huge data centers behind the scenes. That is why Panthalassa’s ocean plan is getting attention. The company wants to use waves for power and seawater for cooling. The hard part is proving that floating AI nodes can survive rough seas, limited satellite links and complicated maintenance. If Panthalassa can pull it off, ocean-based AI could become part of the tech we use every day. If it cannot, it may show just how difficult it is to keep feeding AI’s growing demand for power.
If this kind of ocean-powered AI takes off, would you worry about what these floating nodes could mean for our oceans? Let us know by writing to us at Cyberguy.com
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OpenAI announced yet another reorganization Friday, consolidating certain areas and making company president Greg Brockman the official lead of all things product.
In a memo viewed by The Verge, Brockman wrote that since OpenAI’s product strategy for this year is to go all-in on AI agents, the company is combining its products to “invest in a single agentic platform and to merge ChatGPT and Codex into one unified agentic experience for all.”
To do this, the company is making a suite of org chart changes, although it’s still operating under some of the same ones from last month. That’s when AGI boss Fidji Simo went on medical leave and OpenAI announced that Brockman would be in charge of product strategy and CSO Jason Kwon, CFO Sarah Friar, and CRO Denise Dresser would take control of business operations.
It’s all part of OpenAI’s recent strategic shift to focus on key revenue drivers like coding and enterprise and stop pouring resources into “side quests” ahead of its potential IPO later this year and amid investor pressure to turn a profit.
In Simo’s continued absence, Brockman’s role leading product strategy is now official, as well as the company’s “scaling” arm. Under Brockman will be four different pillars. The first is core product and platform, led by Thibault Sottiaux, who has been OpenAI’s engineering lead for Codex, and the second is critical enterprise industries, led by ChatGPT head Nick Turley. Third is the consumer pillar, such as health, commerce, and personal finance, which will be led by Ashley Alexander, who has been its healthcare products VP. The fourth pillar — core infrastructure, ads, data science, and growth — will be led by Vijaye Raji, who has been OpenAI’s CTO of applications.
Brockman wrote in the memo that OpenAI’s goal is now to “bring agents to ChatGPT scale, in order to give individuals and organizations significantly more value and utility from our products.”
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