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Introducing Gemini Omni

Last year, Nano Banana brought Gemini's intelligence to image generation and editing. Since then, it’s helped millions of people restore old photos, design from sketches and visualize ideas in ways that weren’t possible before. From the start we built Gemini to be natively multimodal from the ground up, and now we’re taking the next step.…

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Genesis AI Releases Nyx, Quadrants, and Genesis World 1.0 Physics Platform for Scalable Robotics Foundation Model Evaluation

Genesis AI released Genesis World 1.0. The platform consists of four components: the Genesis World physics engine, Nyx (a real-time path-traced renderer), Quadrants (a Python-to-GPU compiler), and a simulation interface. It is designed to accelerate robotics foundation model development through simulation-based evaluation. Robotics model development has two bottlenecks: data and iteration speed. The field has…

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We’re launching the Google DeepMind Accelerator program in Asia Pacific to tackle environmental risks.

The Asia-Pacific region is a global engine for economic growth, but it's also highly vulnerable to climate change. While green technologies are gaining momentum, a recent report shows they aren’t scaling fast enough to keep up with the region’s rising environmental risks. To help innovators tackle these environmental challenges, we’re launching an inaugural Google DeepMind…

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TurboQuant: Is the Compression and Performance Worth the Hype?

  #  Introduction   TurboQuant is a novel algorithmic suite and library recently launched by Google. Its goal is to apply advanced quantization and compression to large language models (LLMs) and vector search engines — indispensable elements of retrieval-augmented generation (RAG) systems — to improve their efficiency drastically. TurboQuant has been shown to successfully reduce…

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Liquid AI Releases LFM2.5-VL-450M: a 450M-Parameter Vision-Language Model with Bounding Box Prediction, Multilingual Support, and Sub-250ms Edge Inference

Liquid AI just released LFM2.5-VL-450M, an updated version of its earlier LFM2-VL-450M vision-language model. The new release introduces bounding box prediction, improved instruction following, expanded multilingual understanding, and function calling support — all within a 450M-parameter footprint designed to run directly on edge hardware ranging from embedded AI modules like NVIDIA Jetson Orin, to mini-PC…

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