Models & Labs · United States

AI agent makers are promising privacy — will they deliver?

Credited to The Verge · theverge.com · 7h ago

Photograph · The Verge

Meta positioned its Muse agent as a safer alternative to OpenClaw. OpenAI promises Dots is a safer alternative to Muse.

At this year’s OpenAI DevDay, CEO Sam Altman unveiled the company’s new AI agent Dots — and told the crowd that the company wants to “set a new standard for privacy in frontier AI.” OpenAI would spend the day taking veiled shots at Meta’s Muse, its primary competitor, for failing to keep users’ data safe. Yet Muse itself, a couple of months earlier, had launched as a supposedly safer alternative to predecessor OpenClaw — with CEO Mark Zuckerberg promising it was “built from the ground up for privacy and security.”

In an age when companies hoard customers’ personal data and cyberattacks are a dime a dozen, AI labs are trying to convince users to share even more information with their agents. Their latest strategy for success is one-upping the competition by promising that unlike their rivals, they’ll keep user data away from prying eyes. The question is whether companies can keep these promises.

Nat Friedman, head of product at Meta Superintelligence Labs, wrote on X that the company’s “goal with muse was to build something like openclaw that we could make safe and secure and easy to use and scale to billions of people.” User data is stored on a secure VM, what Zuckerberg described as an “isolated linux computer with a browser, CPU, memory, and storage.” The company said that most of the effort in building Muse was related to “careful design and engineering to operate [it] more safely.” Meta’s blog post continued, “Muse can and will still make mistakes, but we expect they’ll be much less frequent and cause much less damage due to the safety systems we’ve built in.”

But though Muse topped the App Store charts and, per Apptopia, gained 600,000 daily active users in the US within weeks, Meta’s promises seem to have fallen short. Although data is isolated from other users, and the company plans to introduce a way “to cryptographically and verifiably prevent Meta from accessing data in your VM” later this year, Meta itself can still access the data. A security researcher quickly exposed a zero-day vulnerability that could allow someone to take control of Muse (which has since been patched), raising fears of outside attacks. Multiple serious security issues reportedly cropped up at the last minute before launch, one of which could have allowed users to access Meta’s own internal databases, per 404 Media.

Muse also appears to liberally collect (and in some cases, hand out) data. It defaults to allowing Meta to train models on what users put into it, though it’s possible to opt out. An Inc. reporter complained that Muse uploaded and read his private messages without him asking it to, and a YouTuber said it had offered his address to a stranger via Marketplace — in both cases, Muse was functioning apparently as intended, but the user didn’t realize how far it would go. The platform creates “detailed profiles of all your friends and family,” as Wired reported. None of this is necessarily unexpected from Meta, but it certainly doesn’t back up the idea that Muse is uniquely privacy- or security-conscious.

OpenAI seized on this fact when announcing Dots in late September. Alexander Embiricos, OpenAI’s Codex product lead, said onstage at DevDay that OpenAI is focused on having the “most trustworthy, safe, and secure assistant,” and CEO Sam Altman demonstrated ways that people could exert control over their individual Dots, such as setting a rule that it should never make a purchase over a certain dollar amount. “I think we’re in a different position to Meta in that they don’t have an AI product that has 1.2 billion users,” said Glen Coates, OpenAI’s head of app platform, adding that “launching something that makes those kinds of mistakes is something that we would try to take the care to avoid.”

Altman himself also pushed the privacy angle at DevDay. To court business customers, executives presented a framework allowing enterprises to have “stronger controls” over their data and zero data retention policy options (meaning no data is stored on OpenAI servers). Indeed, so far, there haven’t been many privacy scandals with Dots — although since it’s only available on the $100-and-up ChatGPT subscription tiers, there are also likely fewer people using it.

People may still not feel comfortable giving OpenAI their personal data, in part simply because AI agents require so much of it. For instance, The Verge ’s Allison Johnson felt uncomfortable typing in her bank information when the bot asked as part of a relevant task (Muse has a Stripe integration to take care of that).

Not all companies are making privacy promises, of course. Instinct was publicly criticized for reportedly overly-broad terms of service that gave it unfettered access to data; since then, the company seems to have made adjustments. For now, AI labs seem to be counting on a three-part approach to popularizing AI agent use with the general public: Make them useful, make them cute and disarming to help offset the creepiness, and make promises about privacy — and hope they hold up.

Models & LabsUnited States

Google's Gemini 4 "Carbon" model is reportedly matching Anthropic's Opus 5.5 coding performance

Credited to The Decoder · the-decoder.com11h ago

Useful

Gemini 4 "Argon" hasn't even shipped yet, and there are already rumors about the next performance update.

According to documents, screenshots, and internal chats seen by Business Insider, Google is testing several Gemini 4 variants called Argon, Barium, and Carbon. Carbon was deployed on Google's internal coding platform Jetski over the past few days and is said to beat Argon mainly on programming tasks.

One employee compared Carbon to Anthropic's strongest coding model, Opus 5.5, though it still needs more testing. Early Argon versions, by contrast, reminded another employee of the older Opus 5 on some coding tasks, even though internal feedback was positive overall. Ad

Argon is Google's frontier reasoning model

Early rumors pegged Argon as a Flash model optimized for speed over peak performance. The announcement of Google's Gemini agent for Google Workspace puts that to rest. Google maps its models to specific roles: "Argon for frontier reasoning, Flash for speed and volume, Omni for generative media, and Gemma for lightweight, open-weights edge workloads," the company writes. Ad

So Argon is definitely Google's most capable reasoning model, comparable to Anthropic's Opus or OpenAI's Astra. Carbon and Barium are likely checkpoints or updates within the Argon family, not separate tiers. One employee internally called Carbon "Gemini pro next model," suggesting it would ship under the Argon name. That fits with internal documents showing the now-unveiled Argon was previously called "Barium-B." Whether Carbon ships as an Argon update or a standalone model remains unclear.

The quick update pace, similar to what Google has done with the Flash models, suggests Google has gotten better at using AI to build new models. Google Deepmind employee Vedant Misra responded to the Business Insider report on X by writing, "Have you heard of recursive self improvement," referring to using AI to build better AI. OpenAI and Anthropic have reported similar progress. Ad

Google is already prepping for the Gemini 4 launch

There's still no official Gemini 4 launch date yet, but Google is already retooling its apps. The Gemini app now shows a new "Automatic" mode for the 3-series models and adjustable reasoning intensity from low to high. Google AI Studio has surfaced a new "Ultra" mode promising "advanced skills and tools." Google's Logan Kilpatrick confirmed the team is working on getting the most out of Argon.

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