Look Up Versus Say More Mashable's Best: E-readers, robovacs, laptops, earbuds, smart home and more Mashable Selects Creator Playbook In My Bag Trending Now Back to School Good Connection: Uplifting stories for a digital age Switch Off Mashable Voices All Series Alex Perry is a tech reporter at Mashable who primarily covers video games and consumer tech. Alex has spent most of the last decade reviewing games, smartphones, headphones, and laptops, and he doesn't plan on stopping anytime soon. He is also a Pisces, a cat lover, and a Kansas City sports fan. It doesn't seem as bad as it sounds. Google's signature AI agent did something it probably shouldn't have, and Google opted not to mention it for months.

Mashable Selects Mashable's Best: E-readers, robovacs, laptops, earbuds, smart home and more Creator Playbook Look Up Back to School Say More Trending Now Good Connection: Uplifting stories for a digital age Switch Off Mashable Voices Safety Net Versus All Series Where is Gemini 3.5 Pro? Timothy Beck Werth is the Tech Editor at Mashable, where he leads coverage and assignments for the Tech and Shopping verticals. Tim has over 15 years of experience as a journalist and editor, and he has particular experience covering and testing consumer technology, smart home gadgets, and men's grooming and style products. Previously, he was the Managing Editor and then Site Director of SPY.com, a men's product review and lifestyle website. As a writer for GQ, he covered everything from bull-riding competitions to the best Legos for adults, and he's also contributed to publications such as The Daily Beast, Gear Patrol, and The Awl. At the Google I/O event in May, CEO Sundar Pichai announced that the company's newest frontier model, Gemini 3.5 Pro, would launch in June .

Mashable Selects Mashable's Best: E-readers, robovacs, laptops, earbuds, smart home and more Creator Playbook Look Up Back to School Say More Trending Now Good Connection: Uplifting stories for a digital age Switch Off Mashable Voices Safety Net Versus All Series Google announced the news in a blog post. Timothy Beck Werth is the Tech Editor at Mashable, where he leads coverage and assignments for the Tech and Shopping verticals. Tim has over 15 years of experience as a journalist and editor, and he has particular experience covering and testing consumer technology, smart home gadgets, and men's grooming and style products. Previously, he was the Managing Editor and then Site Director of SPY.com, a men's product review and lifestyle website. As a writer for GQ, he covered everything from bull-riding competitions to the best Legos for adults, and he's also contributed to publications such as The Daily Beast, Gear Patrol, and The Awl. Google may not have any news to share about the missing Gemini 3.5 Pro (the next-gen AI model originally scheduled to be released in June), but the company does have a consolation prize for Windows users.

Google has revealed a new AI audio model that it says offers improved speech recognition and transcription. Gemini 3.5 Transcribe is joining Gemini 3.5 Live and Gemini 3.5 Live Experimental in the Gemini Audio family. The company says Gemini 3.5 Transcribe is more adept at speech-to-text than earlier models, with greater precision and the ability to automatically detect more than 85 languages. It says the model can adapt a user's unstructured speech into formatted text. You can use it to make edits with voice commands, and it removes filler words from transcribed speech too. Instead of typing out every thought, Gemini 3.5 Transcribe works with the way you actually talk: Seamlessly handles self-corrections Removes filler words to deliver clean, formatted text Understands your natural intent and speaking style Accurately captures audio in... pic.twitter.com/17YcsDi7Q0

Simone Bombari asked us whether the 1-bit quantized random vector Y = sgn(Wx) has subgaussian norm bounded by a universal constant. Here W is an n n random Gaussian matrix, and x is an independent standard normal random vector in Rn. The question is nontrivial since the coordinates of Y are not independent. We give a strong positive answer to this question - for any bounded map instead of sgn() - using AI: AIDiscovery and Generalization (Theorem 1): To handle coordinate dependence, Gemini 3.5 Flash1 proposed decomposing the Gaussian vector into independent parts, using one part to "smooth" the sign function, and then applying Gaussian concentration for Lipschitz functions.

Eyes in the tech world have turned toward Mountain View, California this week. The San Francisco Bay Area city is where Google's headquarters is located, making it a logical place to hold the company's annual developer conference. That's right, gang, Google I/O 2026 kicked off on Tuesday with the usual opening keynote, which is where the company reveals what's arguably the event's most relevant info for consumers. Google made a ton of Android announcements last week, so its mobile ecosystem wasn't really on the agenda. But what else could the onus possibly have been on if not AI? We heard the word Gemini more times than I could possibly care to count, and the company had many updates to share on that front. Search, Google's longtime bread and butter, was a big focus of the event. The company talked up a new Ask YouTube feature as well as changes to AI subscription pricing and Workspace features like Docs and Gmail.

Google says Gemini 3.5 Flash rivals'large flagship models' for coding and agentic tasks Google says Gemini 3.5 Flash rivals'large flagship models' for coding and agentic tasks It can complete tasks in a fraction of the time of other frontier models, Google claims. Google has unveiled Gemini 3.5, starting with the Gemini 3.5 Flash model that promises to outperform Gemini 3.1 Pro in real-world agentic and coding tasks. Announced at Google I/O 2026, this will be Google's default AI model (not to be confused with Flash-Lite), designed to deliver better speed than the current Gemini Pro models at a more affordable price. The tradeoff is lower performance than the 3.5 Pro model (coming next month) in tasks that require deep reasoning and high-context understanding. However, Google has reduced the compromise between the Pro and Flash models, saying Gemini 3.5 Flash delivers intelligence that rivals large flagship models on multiple dimensions.

The CEO of Google DeepMind tells WIRED that companies should use the productivity gains of AI to do more, not lay people off. Demis Hassabis, the CEO of Google DeepMind, is keen to talk about the coding skills of his company's newest model, Gemini 3.5 Flash. The model has been trained to perform complex agentic coding tasks: translate large code bases from one language to another; find and fix bugs lurking deep in knotty code; and even write entire operating systems from scratch. Hassabis does not, however, think this spells doom for software developers. "I have no idea why people are going around talking with certainty about that," Hassabis tells WIRED ahead of the new model reveal at today's Google's I/O event .

Domain adaptation faces a fundamental paradox in the cold-start regime. When target data is scarce, statistical methods fail to distinguish relevant source domains from irrelevant ones, which often leads to negative transfer. In this paper, we address this challenge by leveraging expert textual descriptions of the target domain, a resource that is often available but overlooked. We propose a probabilistic framework that translates these semantic descriptions into a choice model, namely a Language-Induced Prior (LIP), that learns the preferences from a pretrained Large Language Model (LLM). The LIP is then integrated into an Expectation-Maximization algorithm to identify source relevance. Methodologically, this framework is compatible with any parametric model where a likelihood is available. It allows the LIP to guide the selection of sources when target signals are weak, while gradually refining these choices as samples accumulate. Theoretically, we prove that the estimator roughly matches an oracle cold-start MSE under a correct prior, while remaining asymptotically consistent regardless of the quality of the LIP. Empirically, we validated the framework on a descriptive (Gaussian estimation), a predictive (C-MAPSS dataset), and a prescriptive task (MuJoCo hopper).

Apple could unveil Gemini-powered Siri in Feb. Gemini 3 is now Google's default model for AI Overviews Plus, you can start an AI Mode conversation directly from a summary. The Google logo and lettering can be seen on the façade of the company's Munich headquarters building in Munich (Bavaria). Google has begun rolling out two upgrades for Search. Starting today, Gemini 3 is the default model powering AI Overviews. When the company debuted its new family of AI systems last November, it first deployed Gemini 3 in AI Overviews through a router that was programmed to direct the most difficult questions to the new system.