Tech
Google faces another AI training lawsuit from major publishers
A group of publishers and authors have filed a class action lawsuit against Google, accusing the tech giant of using their copyrighted works to train its AI platform, Gemini.
The group of plaintiffs, which includes Hachette, Cengage, Elsevier, author Scott Turow, and S.C.R.I.B.E., also alleges that Google intentionally removed or changed copyright information on these works to “conceal… that its Gemini Models were trained on stolen materials,” according to the lawsuit.
This lawsuit is just one of many complaints that publishers, authors, and other copyright holders have filed against AI companies such as Google, Meta, OpenAI, and Anthropic.
While many of these lawsuits are still pending, two early court decisions in California have favored the AI companies, ruling that the use of copyrighted works for AI training is considered “fair use” under U.S. copyright law that has not been updated since before the existence of the internet.
Anthropic was, however, fined $1.5 billion for pirating the works it trained on, marking the largest payout in the history of U.S. copyright law. Around half a million writers were eligible for payments of at least $3,000. However, many authors opted out of receiving the settlement so that they could pursue further legal action over AI training.
The California judges’ decisions don’t bode well for how other courts may view the tech companies’ fair use defense, but the conflict is too nuanced for these rulings to establish an inarguable precedent. The lawsuit against Google was filed in the U.S. District Court for the Southern District of New York, giving a different judge the opportunity to weigh in.
In the Google case, the publishers have a more nuanced, long-term relationship with the company. The lawsuit explains that publishers and authors have a long history of providing Google with copyrighted works for the specific purpose of making books searchable through Google Books. These search results do not allow users to view entire books. Instead, they provide access to short snippets of the book along with bibliographic information. The plaintiffs claim that Google trained Gemini on copies of these books, as well as books uploaded to the Google Play store, even though it never received permission to do so.
“Google illegally copied works from all these scope-limited programs for AI training, knowing it lacked authorization to do so,” the lawsuit reads.
The plaintiffs also cite an internal document from Google that allegedly states that using copyrighted books for AI training could be “highly problematic for Google” and might result in “$10Bs-$100Bs in potential fines.”
Google did not immediately respond to a request for comment.
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Tech
Iran abused mobile networks’ vulnerabilities to locate US military in the Middle East, report says
The Iranian government abused well-known vulnerabilities in the global telecoms infrastructure to locate U.S. military personnel in the build-up to the Iran War, as well as in the early days of the conflict, according to Financial Times.
The Iranian government exploited Signaling System 7, or SS7, a set of protocols for 2G and 3G networks that has long been the backbone of how cellular networks connect to each other to route subscribers’ calls and texts around the world, the newspaper reported, citing research by the Mobile Surveillance Monitor, as well as anonymous government officials with knowledge of the spy campaign.
Intelligence agencies have long abused SS7 to track cellphones abroad, which is what happened in this campaign.
Using this technique, Iran was reportedly able to locate U.S. military forces stationed in military bases as well as hotels in Iraq, Bahrain, and other countries in the Middle East, which allowed the regime to strike them. These attacks resulted in several injuries.
Apart from SS7, Iran also abused advertising technology used to serve tailored ads to cellphone users, another well-known surveillance technique that relies on everyday technology.
Tech
Google Images gets a Pinterest-like redesign focused on discovery
Google Images, the tech giant’s image search engine, is taking on Pinterest with its latest redesign that turns the site into a browsable, dynamic gallery of images from across the web. Google is also adding a way for users to create AI images right in Search, as it celebrates 25 years since the debut of Google Images.
Pinterest has long been known for allowing people to browse and save visual inspiration for everything from fashion to home decor. With this redesign, Google is essentially copying that playbook by turning Google Images into a place for discovery and inspiration, and not just search, which could increase users’ time spent on Google platforms, helping boost its ad revenue.
In addition, Google is likely hoping that when users can’t find the image they’re looking for on Google Images or when they want to visualize something, they’ll stay within its ecosystem to create it rather than turn to third-party services like ChatGPT.

After navigating to the redesigned Google Images, users will see a “For You” gallery of images tailored to their interests and browsing history. Like Pinterest, the gallery is designed for continuous browsing, with Google saying it updates in real time with new images.
As users browse, they can save ideas to their “collections,” which will appear as tabs above the main gallery of photos. For example, users can create collections for things like vacation outfit ideas, travel inspiration, and ways to design a reading nook, which they can come back to later.
The redesign is rolling out over the coming weeks on desktop in the U.S. in English. Users need to be signed into a Google Account to try it out, the tech giant says.

As for generating images directly in Search, Google says the feature is meant for moments when you have a highly specific idea for an image that doesn’t already exist online. Google is bringing image generation directly into AI Overviews on Search and will use its latest Nano Banana model to transform a text prompt into a custom visual.
The feature can also help users reimagine spaces and visualize ideas, such as seeing what a room might look like painted red or what a dorm room with a coastal theme could look like.
Image generation in AI Overviews will start to roll out over the coming weeks in English for all regions that currently support image creation in AI Mode, Google says.
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Tech
Meta’s Adam Mosseri says AI token budgets could soon be capped per engineer
In a recent interview, Instagram head Adam Mosseri said he can see a time in the future, perhaps only a year or two, when putting limits on Meta employees’ AI token spend will become necessary.
“I think that you can imagine, at least in a year or two … that the burn rate of a strong engineer might be the same as their salary, or their cost of employment. And in that world, you’re going to probably need to put in some caps,” the Meta executive said, while speaking on Lenny’s Podcast.
AI token spend, a reference to the cost of processing AI prompts and responses, has been a much-buzzed-about subject in recent days. Meta shut down an internal AI token spend leaderboard after AI costs put the company on track for billions of dollars in 2026.
Meta is not alone in rethinking its approach to AI experimentation. Uber also had an AI reckoning after it blew through its 2026 AI coding budget by April. Soaring token costs saw Microsoft cancel Claude Code licenses, consolidating its engineers around its own Copilot CLI tool instead.
Mosseri’s belief, he explained, is that AI token costs will have to be managed just like any other resource, offering an analogy to things like payroll or operating expenditure (OpEx), which is the day-to-day costs of running a business.
“I think of it like…any other resource,” Mosseri said. “I have to decide how to deploy capacity to my different teams because I have a limited number of GPUs and CPUs and storage and RAM etc. I have to decide how to deploy OpEx for labeling budgets across my teams. I have to decide how to deploy payroll for headcount across my teams.”
Token budgets will be the same, he added, noting that the cap per engineer would have to be proportional to the company’s trust in their ability to use the budget in an “ROI-positive” way.
Meta doesn’t currently have token caps for any employee, Mosseri said, but he believes that their use could be healthy in the future. Further down the road, he expects token costs to come down as the AI model makers enter a pricing war to attract people to use their tools over their competitors.
For now, the company has managed to rein in its token costs a bit by shutting down the “silly things” that it was doing, Mosseri noted — like that token spend leaderboard.
“It’s not that hard to build a token incinerator, and that doesn’t create a lot of value,” he said.
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