Connect with us

Tech

DeepMind CEO calls for an independent standards body to regulate frontier AI

In an X post on Tuesday morning, Google DeepMind CEO Demis Hassabis called for the creation of a new regulatory body to oversee frontier model releases. Titled “A Framework for Frontier AI and the Dawning of a New Age,” the post makes the case for a “standards body” modeled after the Financial Industry Regulatory Authority (FINRA), which could test frontier models and develop best practices for their release.

“Initially, Frontier Labs would voluntarily share models with the Standards Body for review up to 30 days before release,” the post reads. “Once the assessment protocol is shown to be effective and robust, formalisation could quickly follow, meaning that Frontier Models would be required to pass it to be deployed in the US market. Labs would also work with the Standards Body to address any critical post-release vulnerabilities.”

The proposed system would build on the ad hoc reviews performed by the U.S. government on Anthropic’s Mythos and OpenAI’s Sol. Those reviews drew significant criticism for lack of technical expertise and opaque decision-making as to when a model could be released. Under Hassabis’ proposed regulator, those decisions could be handed off to a new organization, backed by the U.S. government but funded by the AI industry and operated independently.

The prospect of AI regulation remains controversial for both the tech industry and the Trump administration. Most recently, White House AI advisor and a16z general partner Sriram Krishnan discounted the possibility of an AI regulator within the executive branch, saying “there will not be an FDA for AI.”

Establishing the standards body as a self-regulatory organization like FINRA could be a way to address those concerns. Hassabis envisions the regulator being staffed by open source representatives and technical experts from within the industry, along with the financial backing from AI labs that would be necessary to retain them. They could even outsource some evaluations to the growing pool of AI safety groups that would be able to specialize in specific risks.

“The strength of this approach is it would be technically focused, while at the same time supporting innovation and incentivising responsible behaviour,” Hassabis argues. “It is designed to keep up with the field’s acceleration and adapt to the biggest risks as they are identified, and could be ratcheted up if the seriousness of the situation demands.”

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

source

Continue Reading
Click to comment

Leave a Reply

Your email address will not be published. Required fields are marked *

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.

source

Continue Reading

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.

Image Credits:Google

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.

Image Credits:Google

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.

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

source

Continue Reading

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.

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

source

Continue Reading