Gemini 3 Flash excels in capabilities required for rapid prototyping, including instant code generation, aesthetic versatility, and creative ideation. It can also natively drive the design process, like generating new prompts for style exploration, and can produce multiple distinct UI variations with just a single click to accelerate development. Learn more at https://deepmind.google/models/gemini/flash/ ___ Subscribe to our channel https://www.youtube.com/@googledeepmind Find us on X https://twitter.com/Go ...

What we have here is a simple web app that takes simulated unstructured data, in this case a chat, and matches it to the right customer record, bringing everything together. It's a good example of how Gemini 3 Flash can quickly pull information from different systems and merge it into one clear, organized piece of data. ...

Gemini 3 flash enables an entirely new way to develop. It's low latency and quality coding capabilities allow you to AB test real-time code generations. In this example, Gemini 3 flash evolves the perfect loading spinner.So fast, you barely need a loading spinner. Once you start evolving, it streams the code for the next version of spinners and shows you the latency metrics. You select your favorite variant and the next generation of spinners will be based upon that one.You can imagine this for any app, per ...

Gemini 3 Flash excels in speed and efficiency by coding SVG images, HTML, and three.js side-by-side between 3 Flash and 2.5 Pro. 3 Flash generates the imagery better, faster and with fewer token usage. Learn more at https://deepmind.google/models/gemini/flash/ ___ Subscribe to our channel https://www.youtube.com/@googledeepmind Find us on X https://twitter.com/GoogleDeepMind Follow us on Instagram https://instagram.com/googledeepmind Add us on Linkedin https://www.linkedin.com/company/deepmind/ ...

Gemini 3 Flash specializes in capabilities critical for live assistance, including complex geometric calculation, velocity estimation, and multimodal processing. It can also simultaneously analyze video and hand-tracking inputs to provide strategic, real-time guidance in this slingshot game. Learn more at https://deepmind.google/models/gemini/flash/ ___ Subscribe to our channel https://www.youtube.com/@googledeepmind Find us on X https://twitter.com/GoogleDeepMind Follow us on Instagram https://instagram.co ...

Gemini 3 Flash can handle a huge number of function calls reliably at low latency. In this function calling challenge, it must successfully sequence tasks to prepare dishes. Let's cook some ramen.We start with 100 ingredients and 100 tools which the model has to reason across simultaneously. Each kitchen tool is a separate function call. There are three agents powered by Gemini 3 flash.The cooking agent triggers the function calls. It plans ahead by combining raw ingredients to use later on. New combination ...

Product Overview - The product generates travel stories based on user-defined routes, start and end points [1] - Users can customize the story based on travel method (driving, walking) and desired story type [1] - Gemini 3 Flash technology ensures rapid story and voice-over generation, tailored to trip duration [1] Technology - Gemini 3 Flash is used for quick story and voice-over generation [1]

Product Features - Gemini 3 Flash enhances image generation with a contextual UI, showcasing strong multimodal capabilities [1] - The system demonstrates understanding of visual input and reasons to describe image content interactively [1] Company Information - Google DeepMind promotes its Gemini Flash model [1] - Google DeepMind encourages users to learn more via a provided link [1] - Google DeepMind directs users to its social media channels (X, Instagram, LinkedIn) and YouTube channel [1]

Robotics Advancements - Google DeepMind's robotics research has achieved significant progress in the last four years, particularly in visual generalization, enabling robots to operate effectively in diverse lighting and backgrounds [3][4] - The integration of large vision language models (VLMs) has enabled robots to understand general human concepts and improve their ability to generalize in new scenes, visuals, and instructions [5] - Vision Language Action Models (VALAs) allow robots to model sequences of physical actions, enabling action generalization and longer-horizon tasks, such as packing luggage by checking the weather in the destination [7][9] - Robotics is applying the principle of "thinking before acting," similar to language models, to improve performance in basic manipulation tasks [12][13] Capabilities and Demonstrations - Robots are now capable of performing complex, long-horizon tasks that require millimeter-level precision, such as packing a lunchbox, demonstrating improved dexterity [15][17] - Robots can now perform general tasks by understanding spoken instructions, interacting with novel objects, and chaining together short tasks into longer, more useful sequences [24][29] - Demonstrations include sorting trash according to San Francisco rules and sorting laundry, showcasing the ability to reason and act in complex scenarios [30][33] - The "thinking and acting" model allows robots to output their thoughts before taking action, providing insight into their decision-making process [34][36] Future Directions - The progress in robotics is currently limited by the amount of physical interaction data available, which is not as vast as the data available for language models [45][48] - A major breakthrough is needed to enable robots to learn more efficiently with data, potentially through learning from human manipulation videos [43][46] - The current advancements are considered foundational blocks towards achieving general-purpose robotics, but further development is needed to ensure safety and task mastery [42][45]

The Roman bridge building is maybe a better analogy of how we do AI development where we have some intuitions just like the Romans had intuitions and they built some beautiful bridges but they didn't have all the equations and full understanding and yet they built things they needed and yet they were able to drive carts across the bridge they built. We are in that sense operating partially intuitionally in AI but downstream the people using tools like alphafold I think it's more like having a great computat ...