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Demis Hassabis 2026 AI predictions: Agentic systems will transform how we work. Robotics is about to level up. And world models will unlock new potential on edge devices. The future is closer than you think. Holy moly.

Chubby♨️

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37,105 次观看 • 8 个月前 •via X (Twitter)

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Why I’m bullish on AI in 2026 2026 feels like the year AI becomes impossible to ignore. Not because of better chatbots, but because AI starts doing real work. Agents will run tasks end to end, humanoid robots will actually work in factories, and suddenly the labor market feels very different. That’s when the disbelief fades. Demis Hassabis basically confirmed it: reliable agentic systems, a real robotics push, useful on-device assistants, and world models that let AI plan in the real world. That combo is explosive. Once people see robots on factory floors and AI agents quietly replacing office tasks, the conversation changes. AI stops being hype and starts being reality. That’s why 2026 matters

Why I’m bullish on AI in 2026 2026 feels like the year AI becomes impossible to ignore. Not because of better chatbots, but because AI starts doing real work. Agents will run tasks end to end, humanoid robots will actually work in factories, and suddenly the labor market feels very different. That’s when the disbelief fades. Demis Hassabis basically confirmed it: reliable agentic systems, a real robotics push, useful on-device assistants, and world models that let AI plan in the real world. That combo is explosive. Once people see robots on factory floors and AI agents quietly replacing office tasks, the conversation changes. AI stops being hype and starts being reality. That’s why 2026 matters

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AI is rapidly evolving, and it’s reshaping how and where computing happens. From data center infrastructure to AI systems in the physical world, to the future of personal AI devices, intelligence is being distributed across a new compute landscape. At the edge, more agentic experiences are starting to show up, expanding what devices need to do. Tomorrow in New York, we’ll share what Qualcomm is building across it and how it will drive our next phase of growth. Stay tuned for #QCOMInvestorDay.

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⚡Why Edge Compute Matters for the Future of Agentic AI AI isn’t just about smarter models, it’s about where they run. Centralized clouds are costly, slow, and controlled by a few. That’s not the future. 👉Join the OptimAI Network: With OptimAI Edge Compute and the upcoming Core Node release, every device becomes part of a decentralized supercomputer: + AI models run directly on your devices (phones, desktops, IoT devices) + Data stays local, secure, and real-time + Compute scales with the community, not corporations This is how we power the next generation of Agentic AI - AI systems that don’t just think, but act like you. Lightweight, fast, everywhere, for everyone. Stay tuned. The Edge is coming.

⚡Why Edge Compute Matters for the Future of Agentic AI AI isn’t just about smarter models, it’s about where they run. Centralized clouds are costly, slow, and controlled by a few. That’s not the future. 👉Join the OptimAI Network: With OptimAI Edge Compute and the upcoming Core Node release, every device becomes part of a decentralized supercomputer: + AI models run directly on your devices (phones, desktops, IoT devices) + Data stays local, secure, and real-time + Compute scales with the community, not corporations This is how we power the next generation of Agentic AI - AI systems that don’t just think, but act like you. Lightweight, fast, everywhere, for everyone. Stay tuned. The Edge is coming.

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What happens in a world post-foundation model? "Foundation models are not going away, they will remain a core part of future systems. The question is not whether they get replaced, but what gets built on top of them. Future AI systems will likely combine foundation models with additional components to create more complete systems." Demis Hassabis Love to hear your thoughts Yann LeCun François Chollet Jürgen Schmidhuber Aran Komatsuzaki

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Google DeepMind CEO Demis Hassabis says AI agents are coming that will be able to search the Tree of Knowledge to discover new and original things about the world

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Google DeepMind CEO Demis Hassabis: AGI will be 10x bigger than the industrial revolution and 10x faster. To reiterate: I think we will see the first significant changes in many scientific fields in 2026.

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“In the next 10 years we are going to be entering what I feel like is a new renaissance.” Nobel Prize laureate Demis Hassabis was awarded the Nobel Prize for using AI to predict the structure of proteins. For him, AI is a tool that will help scientists make even more discoveries in the years to come. Hassabis took part in our Nobel Prize Dialogue ‘The Future of Science With AI’ which discussed how AI might transform science in the future. Watch the full event at

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I’m fully with Demis Hassabis on this. STEM still matters deeply, not because humans will outcode AI, but because we need to understand, steer, and define problems at a high level. At the same time, AI is blowing the doors open for creativity. When technical barriers fall, taste, judgment, and vision become the real edge. The future belongs to people who know what to build and why, not just how. Do you think schools are preparing kids for that reality or are they still training them for a world that’s already gone?

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“We think we have a competitive advantage.” - Demis Hassibis, Head of Google DeepMind / AI efforts While Anthropic and OpenAI seek to win via training on “text” (written language), Demis Hassabis says Google Gemini is attempting a different path: Multimodal. Gemini aims to be the most effective model in the real world: physics, robotics, voice, visual, sensory, & text. The bet is multimodal unlocks more of what humanity really cares about.

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Demis Hassabis says world models are his longest standing passion and explains benefits vs. language models: ▫️ “I think language models are able to understand a lot about the world. More than we expected because language is actually probably richer than we thought. But there's still a lot about the spatial dynamics of the world, spatial awareness and the physical context we're in — and how that works mechanically — that is hard to describe in words and isn't generally described in corpuses of words. Alot of this is allied to learning from experience. There's a lot of things which you can't really describe something. You have to just experience it. Maybe the senses and so on are very hard to put into words. Whether that's motor angles and smell and these kinds of senses, it's very difficult to describe that in any kind of language.”▫️ This is what Demis and Google Deepmind is trying to solve with Genie. He also says that the video models (Veo) will play a part in training the world models and this is all key for AI robotics.

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Without World Models, There Is No AGI. Google Just Proved It. If AGI ever happens, it will not come from bigger chatbots alone. From the very start of this interview, one thing is crystal clear: without world models, we will never reach AGI. And right now, Google is leading with its world simulator Genie 3. Here is the core of what Demis Hassabis explains in this conversation: • World models are the missing core of AGI Hassabis says his deepest long term focus has always been world models and simulations. Not just language. Not just prediction. Actual internal simulations of reality. • LLMs are impressive, but incomplete Language models understand more about the world than expected because human language encodes a lot of reality. Still, language is only a shadow of the real thing. • What text can never fully teach Reality includes things text struggles to express: •3D space and spatial dynamics •Physical causality and mechanics •Sensorimotor experience like movement, force, smell, or balance • Experience beats description To close the gap, AI must learn from interaction and experience, not just static text. That is how you build an internal world simulator. • Why Genie 3 matters With Google DeepMind pushing systems like Genie 3, AI starts to model reality itself, not just talk about it. • Robots and real world assistants depend on this True robotics, smart glasses, and universal assistants require AI that understands the physical world you live in, not just your screen. Bottom line: AGI will not emerge from better text prediction. It will emerge from systems that can simulate, predict, and understand reality itself. Right now, Google is clearly ahead on that path. Curious what you think. Are world models the real AGI unlock, or just another stepping stone?

Without World Models, There Is No AGI. Google Just Proved It. If AGI ever happens, it will not come from bigger chatbots alone. From the very start of this interview, one thing is crystal clear: without world models, we will never reach AGI. And right now, Google is leading with its world simulator Genie 3. Here is the core of what Demis Hassabis explains in this conversation: • World models are the missing core of AGI Hassabis says his deepest long term focus has always been world models and simulations. Not just language. Not just prediction. Actual internal simulations of reality. • LLMs are impressive, but incomplete Language models understand more about the world than expected because human language encodes a lot of reality. Still, language is only a shadow of the real thing. • What text can never fully teach Reality includes things text struggles to express: •3D space and spatial dynamics •Physical causality and mechanics •Sensorimotor experience like movement, force, smell, or balance • Experience beats description To close the gap, AI must learn from interaction and experience, not just static text. That is how you build an internal world simulator. • Why Genie 3 matters With Google DeepMind pushing systems like Genie 3, AI starts to model reality itself, not just talk about it. • Robots and real world assistants depend on this True robotics, smart glasses, and universal assistants require AI that understands the physical world you live in, not just your screen. Bottom line: AGI will not emerge from better text prediction. It will emerge from systems that can simulate, predict, and understand reality itself. Right now, Google is clearly ahead on that path. Curious what you think. Are world models the real AGI unlock, or just another stepping stone?

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Demis Hassabis says DeepMind is on track to solve intelligence by around 2030 As AI enters the "agentic era" of autonomy this year, the risk is that bad actors could repurpose the tech for harm "then we have to make sure... that these systems do what we expect them to do"

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