More from Demis Hassabis | AI News

Gemini Robotics 2 unlocks dexterity and teamwork

According to @demishassabis, Gemini Robotics 2 brings full‑body intelligence, knot-tying dexterity, and multi-robot teamwork for complex workflows. (Source)

Share 07-30-2026 17:39

NVIDIA Backs Open Models, 300M+ Downloads Milestone

According to sundarpichai, NVIDIA and Google tout open models like Gemma hitting 300M+ downloads and propose standards for responsible deployment. (Source)

Share 07-25-2026 15:31

DiffusionGemma Delivers 4x Faster Text

According to demishassabis, DiffusionGemma generates text up to 4x faster than Gemma 4 by producing blocks simultaneously, per Google Gemma’s announcement. (Source)

Share 06-11-2026 00:52

Gemma 4 12B Launches under Apache 2.0

According to @demishassabis, Gemma 4 tops 150M downloads and adds a 12B model that runs locally on 16GB VRAM under Apache 2.0 for laptop-grade multimodal AI. (Source)

Share 06-03-2026 18:35

Gemini 3.5 Flash debuts with multimodal speed

According to @demishassabis, Google details Gemini 3.5 Flash’s fast multimodal performance and developer features on its official blog. (Source)

Share 05-20-2026 01:05

Gemini 3.5 Flash delivers 800 tps speed

According to @demishassabis, Gemini 3.5 Flash outpaces 3.1 Pro on coding and agent tasks, hits 800 tokens per second, and costs less than half in many cases. (Source)

Share 05-20-2026 01:05

Gemini Omni Debuts multimodal editing power

According to DemisHassabis, Gemini Omni builds new scenes from photos, video, and audio, starting with video outputs and expanding to any input or output. (Source)

Share 05-19-2026 20:16

Gemini Pointer Demos Reimagine UX

According to @demishassabis, Google DeepMind demoed Gemini-powered pointer controls in Google AI Studio using motion, speech, and shorthand. (Source)

Share 05-12-2026 22:22

Isomorphic Labs Secures $2.1B to Turbocharge Drug Discovery

According to @demishassabis, Isomorphic Labs raised $2.1B to accelerate AI-driven drug discovery building on AlphaFold, expanding partnerships and pipelines. (Source)

Share 05-12-2026 13:50

AlphaGo Anniversary Spurs Pro Go Strategy Shift

According to Demis Hassabis, AlphaGo reshaped pro Go strategy and training over the past decade, highlighted by a reunion with Lee Sedol and Shin Jin-seo. (Source)

Share 05-09-2026 18:36

Google DeepMind partners Eve Online for AI research

According to demishassabis, Google DeepMind partnered with Eve Online studio to research game AI, leveraging complex virtual economies and player behavior. (Source)

Share 05-06-2026 22:03

Google DeepMind Seals Korea AI MoU

According to demishassabis, Google DeepMind and Korea’s MSIT signed an AI MoU to speed scientific discovery, talent training, and AI safety collaboration. (Source)

Share 04-29-2026 12:26

DeepMind CEO meets Korea, advances AI safety

According to demishassabis, DeepMind discussed AI safety and science collaboration with President Lee Jae-myung in Seoul, signaling future Korea partnerships. (Source)

Share 04-29-2026 00:53

Google Gemma Momentum: Startups Accelerate Adoption at YC Event — Latest Analysis and 5 Business Opportunities

According to Demis Hassabis on Twitter, many startups are building with Google’s Gemma models, shared during a chat hosted by Garry Tan at a YC community event. As reported by Demis Hassabis, this signals growing developer traction for Gemma’s lightweight open models, which are optimized for on-device and cost-efficient inference. According to Google’s official Gemma documentation, Gemma models are available in sizes like 2B and 7B with permissive licensing, enabling startups to fine-tune for domain tasks while controlling infrastructure costs. As reported by Google, the Gemma stack integrates with popular frameworks such as JAX, PyTorch, and TensorFlow, and supports safety toolkits, boosting time-to-market for early-stage AI apps. Business implications include lower total cost of ownership for inference, faster iteration cycles for vertical copilots, and improved data privacy via edge deployment, according to Google’s Gemma launch materials. (Source)

Share 04-25-2026 02:55

Gemini 3.1 Text to Speech Prompt Guide: Latest Analysis and Business Opportunities for Voice AI in 2026

According to Demis Hassabis, Google AI shared a practical guide on prompting Gemini 3.1’s new text to speech model, detailing techniques for style control, prosody, and contextual grounding (as referenced in his tweet). According to Google AI on Dev.to, the guide explains how to specify speaker persona, control latency versus quality tradeoffs, use inline annotations for emphasis and pauses, and chain prompts with multimodal context to achieve more natural conversational synthesis. As reported by Google AI on Dev.to, the post outlines enterprise use cases such as dynamic voice agents, multilingual customer support, and content localization, and recommends evaluation strategies including AB testing with human preference ratings and robustness checks on long-form generation. According to Google AI on Dev.to, developers are advised to use structured prompts, few-shot style examples, and safety filters for sensitive content, which can reduce error rates and improve voice consistency in production deployments. (Source)

Share 04-16-2026 02:50

Google Unveils Gemini 3.1 Flash and TTS: Latest Multimodal Breakthroughs and Business Use Cases

According to Demis Hassabis, Google introduced Gemini 3.1 Flash and Gemini 3.1 Flash TTS, expanding the Gemini model family with faster multimodal inference and native text to speech for real-time experiences (as reported on Google Blog). According to Google Blog, Gemini 3.1 Flash targets low-latency, cost-efficient multimodal tasks like rapid vision grounding, on-device agents, and streaming assistants, while Flash TTS generates natural speech with controllable style and latency for voice bots, media dubbing, and accessibility. As reported by Google Blog, enterprise customers can access the models via Google AI Studio and Vertex AI with features like safety filters, data governance, and usage-based pricing, positioning the releases to compete on speed and total cost of ownership in contact centers, ecommerce search, and creative automation. According to Google Blog, developers gain server-side streaming, tool use, and improved long-context handling, enabling retrieval-augmented generation and rapid function calling for production-grade agents. (Source)

Share 04-16-2026 02:10

Gemini 3.1 Flash TTS Launch: Latest Expressive Text-to-Speech with 70 Languages and Fine-Grained Control

According to Demis Hassabis on X, Google introduced Gemini 3.1 Flash TTS, a new text-to-speech model offering scene direction, speaker-level specificity, audio tags, more natural and expressive voices, and support for 70 languages, available in preview via Gemini API, Google AI Studio, and Vertex AI for enterprises. According to Logan Kilpatrick on X, the model is designed for granular control over AI-generated speech and is accessible through a new audio playground in AI Studio, enabling developers to rapidly prototype voice experiences. As reported by the X posts, business use cases include multilingual IVR, voice-over localization, dynamic ad narration, and interactive agents, with enterprise access via Vertex AI simplifying governance and deployment. According to the same sources, the steerability features and language coverage indicate opportunities for cost-effective voice pipelines, faster content turnaround, and differentiated brand voices across markets. (Source)

Share 04-16-2026 02:09

Gemini Robotics-ER 1.6 Breakthrough: Google DeepMind and Boston Dynamics Enable Spot to Autonomously Read Industrial Gauges

According to GoogleDeepMind on X, Gemini Robotics-ER 1.6 improves visual and spatial reasoning so robots can plan and complete more useful tasks, including autonomously reading complex industrial gauges on Boston Dynamics’ Spot (source: GoogleDeepMind thread by @GoogleDeepMind). As reported by Demis Hassabis on X, the upgrade is designed to help robots reason about the physical world and operate more usefully in real environments, highlighting a step toward robust perception-to-action pipelines in robotics (source: @demishassabis). According to GoogleDeepMind, these capabilities target practical deployments in industrial inspections, where accurate analog gauge reading and context-aware navigation can reduce downtime and labor costs while improving safety at facilities (source: @GoogleDeepMind). (Source)

Share 04-14-2026 22:09

DeepMind’s Demis Hassabis on the Path to AGI: Latest 2026 Analysis of AI for Science and Medicine

According to Demis Hassabis on X, his 20VC conversation with host Harry Stebbings focused on the path to AGI and concrete ways AI is accelerating science and medicine today, highlighting the UK’s deep tech talent and ecosystem advantages (source: Demis Hassabis on X, Apr 8, 2026; Harry Stebbings on X). As reported by 20VC via Harry Stebbings, the discussion positions frontier AI research—exemplified by Google DeepMind’s work—as a driver for breakthroughs in drug discovery and biomedical research, creating commercialization opportunities for biotech partnerships, AI-first R&D platforms, and healthcare productivity tools (source: Harry Stebbings on X). According to the public post, the episode underscores UK-based opportunities including talent concentration, research universities, and venture funding alignment for scaling AGI-adjacent startups in therapeutics, protein design, and clinical decision support (source: Demis Hassabis on X). (Source)

Share 04-08-2026 17:17

DeepMind CEO Demis Hassabis on AlphaFold, Drug Discovery, and the Future of Creative AI: Key Insights and 2026 Analysis

According to @demishassabis, in a new interview highlighted by @cleoabram, Google DeepMind sees AI accelerating scientific discovery, with AlphaFold’s protein-structure predictions enabling faster drug target identification and pipeline triage for pharma R&D, as reported on X. According to the conversation summary by Cleo Abram on X, Hassabis details how systems like AlphaGo, AlphaZero, and AlphaStar inform scalable research methods that transfer to biology and materials science. As reported by Cleo Abram on X, he also outlines near-term business impact in drug discovery workflows—from hit finding to lead optimization—alongside governance considerations for governmental and military AI use. According to the X thread, Hassabis emphasizes building AI responsibly while pushing creativity in models, positioning DeepMind’s portfolio to open new market opportunities in therapeutics, protein engineering, and automated science. (Source)

Share 04-08-2026 00:56