Last week we announced that Gemini Enterprise has evolved to make it even simpler to get work done, and introduced the Gemini agent, your new universal agent for work. It’s always on and ready to answer your questions. It will write code, complete longer and more complex tasks, or perform whatever you need to get the job done, all from a single prompt box. And model intelligence underpins it all.

To enable a new frontier of work, we are making our new frontier model, Gemini 4 Argon, available on Google Cloud. — Read More

Muse Spark Open is available today and brings leading agentic capabilities to your desktop for the first time on Apple M5 Ultra Mac Studios.

Today, we’re releasing the weights for Muse Spark Open, the most capable US open-weight model to date. Muse Spark Open is a natively multimodal model with 816B total parameters (42B active) and a 1M-token context window. Built for coding and agentic work, it excels at long-horizon tasks, complex software engineering, and multi-step reasoning.

We believe the future is for everyone, and that includes the freedom to run advanced models wherever, including at home. Muse Spark Open is the first model in its class to run on your desktop using two Apple M5 Ultra Mac Studios with the latest MLX framework. — Read More

Gemini 4 Argon delivers frontier performance in complex workflows across real-world software engineering, enterprise knowledge work like legal and finance, and cybersecurity defense.

[W]e’re announcing our new frontier model, Gemini 4 Argon, which is rolling out to a set of trusted cyber defenders through our Fairwind Program. Built to sustain deep reasoning across complex, long-horizon workflows, Argon is fundamentally changing the way we work and build at Google. It delivers frontier performance in complex workflows across real-world software engineering, enterprise knowledge work like legal and finance, and cybersecurity defense. — Read More

Google Cloud and Accenture are working together on a joint unit dedicated to sending engineers into enterprises to help them better adopt Google’s AI tools and services.

The new unit, dubbed Accenture Gemini Enterprise Business Group, is Google’s latest foray into the increasingly competitive world of “forward-deployed engineers,” or FDEs. Rivals in the AI race, including OpenAI, Anthropic, Microsoft, and Amazon, have all recently launched separate business units in a bet that implementing AI models can become its own trillion-dollar business. — Read More

In 2024, Google DeepMind’s AlphaProof solved three of the five non-geometry problems at the International Mathematical Olympiad. Unlike a chatbot producing a plausible-looking derivation in prose, AlphaProof worked in Lean, a formal mathematical language in which proofs can be mechanically checked. It trained by proving or disproving millions of mathematical problems, receiving an unusually clean signal each time: either the proof checked out or it didn’t.

This looked like another frontier falling to artificial intelligence. Chess had fallen, then Go, then protein folding, then programming, and now serious mathematics appeared to be giving way too. Mathematics is among the activities we most strongly associate with the mysterious upper reaches of human intelligence, so perhaps the obvious conclusion was that AI was climbing toward those reaches.

But there is another way to look at what happened: Lean, where a mathematical proposition is represented as a type and a proof as a term of that type. — Read More

In January, Meta CEO Mark Zuckerberg and his top lieutenants gathered for their annual leadership retreat at his Hawaii compound. There they hatched a radical plan to reimagine work at the social-media giant in the age of artificial intelligence.

… But on the night of May 19, just hours before the first layoff wave, Zuckerberg blinked. By then, Meta employees were in open revolt, convinced that the company’s AI transformation initiatives were partly aimed at replacing them. [T]he social-media giant attempted to position itself at the forefront of an AI-driven workplace overhaul, only to stumble in the execution. — Read More

What if I told you that Google is out of the AI race?

It didn’t happen because Google lost, though. Despite an underwhelming I/O event earlier this year, several heavyweight departures, and a slower model release pace than its competitors, Google is still alive. It is out of the race because it withdrew. Weird, right? Why would Google do that willingly?

To answer that, I’m going to tell you the story of why and how Google left the AI race that OpenAI and Anthropic are betting everything on.

Here’s my hypothesis, stated plainly: Google DeepMind CEO Demis Hassabis—a pioneer of AI as we understand it today—doesn’t think that automating AI research with coding agents (AI systems that can program better AI systems) is the correct approach to artificial general intelligence (AGI, the kind of AI that’s as good as humans at everything). Google DeepMind’s leadership sees OpenAI and Anthropic’s bet at best as an off-ramp, and at worst as a dead end.

Hassabis is betting on something else: world models. Models that can understand and simulate the real world, not just predict the next token. — Read More

Mark Zuckerberg is making the case for Meta’s approach to artificial intelligence.

In a 6,500-word essay published Monday, Zuckerberg explained the company’s thinking on AI, what it could mean for society and security, and how policymakers should approach calls for greater oversight of the industry. — Read More

AI divisions are getting reshuffled, the search giant announced on Wednesday, with chief scientist Jeff Dean leaving the company after 27 years.

Demis Hassabis, the CEO of Google DeepMind, is moving into a chairman role of that unit and also assuming the title chief scientist of parent company Alphabet, according to a memo from CEO Sundar Pichai that was posted to Google’s blog. — Read More