Will Grannis

CTO @GoogleCloud

[Aaron Levie @levie]

Good post if you’re trying to understand AI diffusion. Progress driven by AI will ultimately be rate limited by its interaction with the real world.

The reason coding, for instance, has been adopted so quickly is you can write a near infinite amount of code, test it, and run it -and it can add value- without anyone in the outside world ever having to do anything differently. A single person, from a computer, can just make something work end-to-end differently.

This is not true for life sciences, where new drug development eventually needs to be tested for years. Doing a sale, which requires going back and forth with a prospect. Or even a contract, which has to be negotiated on the other side by your counterparty.

“An AI will hand you a genuinely clever design for a jet turbine blade. It might be far more likely to work than anything your engineers came up with. It'll still probably fail, because that's the base rate at the edge of what anyone knows. The only way to find out is to build the blade and try to break it.

That's the real limit on learning, and it doesn't care how smart you are. Coming up with ideas was never the hard part. The hard part is how fast reality answers them.”

Incidentally, this is why you need an applied AI that actually takes intelligence and makes it useful within the workflows of existing industries. Model outputs -alone- are not enough in most cases. You need to actually change the underlying workflows, and you need systems to deal with the realities of the real world feedback loops that are in these industries.

This is why there’s so much opportunity in the applied AI layer.

[Mojtaba Seyedhosseini @mseyed]

Gemini Embedding 2: A Native Multimodal Embedding Model from Gemini 🚀

Today, we’re sharing the @GoogleDeepMind white paper for GE 2, our first native multimodal embedding model. Whether it’s text, audio, video, or image, GE 2 provides a unified representation of the input.

[Jeff Dean @JeffDean]

1/ Today at #GoogleIO, we’re releasing Gemini 3.5, our latest family of models combining frontier intelligence with action.

We’re starting by releasing 3.5 Flash, which is built to help you execute complex, long-horizon agentic workflows.

Gemini 3.5 Flash is our strongest model for coding and agent https://t.co/m62cBJhIjJ outscores 3.1 Pro on agentic and coding benchmarks like Terminal-Bench and MCP Atlas, while running 4x faster than other frontier models.

Used in Google Antigravity, 3.5 Flash is even further optimized to be up to 12x faster. It’s a powerful engine to deploy sub-agents that collaborate, run high-frequency iterative loops, and solve real-world problems at scale.

Some highlights we’re excited about 🔽

[a16z @a16z]

The majority of new jobs created since 1940 didn’t even exist in 1940.

There is no fixed "lump of labor". Again and again, new technologies create new jobs.

a16z's David George dismantles the "AI job apocalypse" myth: https://t.co/0gL5mdffKD

[Logan Kilpatrick @OfficialLoganK]

Good news for AI builders: the File Search tool in the Gemini API is now multi-modal 🗃️, powered by our Gemini Embedding 2 model, + support for custom metadata & inline citations : )

File Search comes with storage and embedding generation at query time free of charge!

[Will Grannis @GrannisWill]

guess it's their turn to dance? https://t.co/afqvJW0I6u

[Sundar Pichai @sundarpichai]

Q1 earnings are in: 2026 is off to a terrific start.

Our AI investments and full stack approach are lighting up every part of the business: Search queries are at an all-time high with AI continuing to drive usage. Google Cloud revenue grew 63%, Gemini models have incredible momentum, and it was our strongest quarter ever for consumer AI subs, driven by @GeminiApp.

Thanks to our partners + employees around the world. Much more to share on our earnings call in 20 minutes… and at Google I/O in 20 days!

[Demis Hassabis @demishassabis]

Gemma 4 outperforms models over 10x their size! (note the x-axis is log scale!)

[Demis Hassabis @demishassabis]

Excited to launch Gemma 4: the best open models in the world for their respective sizes. Available in 4 sizes that can be fine-tuned for your specific task: 31B dense for great raw performance, 26B MoE for low latency, and effective 2B & 4B for edge device use - happy building!

[Will Grannis @GrannisWill]

Excited to join my first Open Confidential Computing Conference tomorrow, March 12th.

If you want to catch the talk, head over to https://t.co/FSduj0XeZe to register.

The full agenda is here: https://t.co/3HIctgRJKl

I’ll be sharing a behind the scenes look into how we use Confidential Computing @Google scale to protect internal workloads and securely accelerate AI innovation. Whether we are hardening our own infrastructure or shielding IP, we rely on these tools to move fast without compromising security.

Strategically, we also use Google as a testing ground for the infrastructure, services and products we deliver via @googlecloud. So the same technology proven at web-scale is ready and available for all of you.

From secure data collaboration to ensuring privacy for GenAI, we’ll dive into what it takes to build a trusted foundation for the future.

See you there!

[Jeff Dean @JeffDean]

I'm delighted to jointly author this year-end summary of research advances with @DemisHassabis and James Manyika, on behalf of all of our colleagues across @GoogleDeepMind, @GoogleResearch and @Google.

We look at research advances across eight different areas. These summaries are always fun to work on because one can reflect back on the breadth and depth of our collective work over the last year!

https://t.co/45lqpHwvnI

[Google AI @GoogleAI]

Rolling out today we are launching Nano Banana Pro, the world’s best image model built to move beyond casual creation and into a new era of studio-quality, functional design.

Nano Banana Pro enables a new level of precision and creative control, transforming the way you bring ideas to life. Here are a couple of our favorite new features:

— Text rendering and translation: Generate crystal-clear text directly within your images. With the model’s advanced language understanding, you can even translate and regenerate visuals with localized text.

— World knowledge: By connecting to Search’s vast knowledge base, Nano Banana Pro generates factually accurate diagrams and realistic product placements, making it an invaluable tool for learning and communication.

[Benjamin De Kraker @BenjaminDEKR]

It turns out "the next Google" was also Google

[Oriol Vinyals @OriolVinyalsML]

The secret behind Gemini 3?

Simple: Improving pre-training & post-training 🤯

Pre-training: Contra the popular belief that scaling is over—which we discussed in our NeurIPS '25 talk with @ilyasut and @quocleix—the team delivered a drastic jump. The delta between 2.5 and 3.0 is as big as we've ever seen. No walls in sight!

Post-training: Still a total greenfield. There's lots of room for algorithmic progress and improvement, and 3.0 hasn't been an exception, thanks to our stellar team.

Congratulations to the whole team 💙💙💙

[Google DeepMind @GoogleDeepMind]

This is Gemini 3: our most intelligent model that helps you learn, build and plan anything.

It comes with state-of-the-art reasoning capabilities, world-leading multimodal understanding, and enables new agentic coding experiences. 🧵

[Will Grannis @GrannisWill]

@sylvester_mol @Google @brysondech @RyderCupUSA As this all scales out we need ai assisted evals or the deluge will force us into really dangerous compromises.

[Will Grannis @GrannisWill]

Two of my favorite things in the news today, technology and golf. Sharing how @Google AI is being used by @brysondech, one of the sport’s most dynamic athletes to continuously optimize his performance. Hopefully this will pay dividends @RyderCupUSA this weekend ;)

Congrats to the teams at @googlecloud supporting this collaboration.

https://t.co/hZujfgmcak

[Jeff Dean @JeffDean]

An exciting new approach for doing continual learning, using nested optimization for enhancing long context processing.

[Anthropic @AnthropicAI]

Today, we announced that we plan to expand our use of Google TPUs, securing approximately one million TPUs and more than a gigawatt of capacity in 2026.

[Google Quantum AI @GoogleQuantumAI]

Today in @Nature, we published a breakthrough demonstration of verifiable quantum advantage using a measurement known as out-of-time-order correlator (OTOC), or Quantum Echoes. Performed on our Willow chip, it paves a path toward real-world applications → https://t.co/kZyomrKPSx