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Google DeepMind

Google DeepMind

Research Services

London, London 1,155,505 followers

We're committed to solving intelligence, to advance science and benefit humanity.

About us

We’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority. Our long term aim is to solve intelligence, developing more general and capable problem-solving systems, known as artificial general intelligence (AGI). Guided by safety and ethics, this invention could help society find answers to some of the world’s most pressing and fundamental scientific challenges. We have a track record of breakthroughs in fundamental AI research, published in journals like Nature, Science, and more.Our programs have learned to diagnose eye diseases as effectively as the world’s top doctors, to save 30% of the energy used to keep data centres cool, and to predict the complex 3D shapes of proteins - which could one day transform how drugs are invented.

Website
https://www.deepmind.google
Industry
Research Services
Company size
501-1,000 employees
Headquarters
London, London
Type
Privately Held
Founded
2010
Specialties
Artificial Intelligence and Machine Learning

Locations

Employees at Google DeepMind

Updates

  • We’re launching Gemini Code Assist for free globally to help developers build faster. 🤝  It comes with: 🛠️ 180,000 code completions per month 🌐 Support for all programming languages in the public domain  💡 A context window of 128,000 tokens to create more relevant responses Whether you’re a student building an interactive data visualization using JavaScript, or a freelancer testing ideas for an app or game, Gemini Code Assist can help you get your project done faster, with more expertise, at no cost. Get started → https://goo.gle/3F3Snpj

  • Google DeepMind reposted this

    View profile for Demis Hassabis
    Demis Hassabis Demis Hassabis is an Influencer

    Co-Founder & CEO, Google DeepMind

    Finishing up my time in Paris for the AI Action Summit, and I had a few takeaways: First, I want to thank President Macron and Prime Minister Modi for convening this summit. It’s incredibly important the international community continues to come together and discuss the future of AI. We all have to be on the same page about the future we’re working to create. I’ve dedicated my life to building artificial intelligence because I’ve always believed it will be the most transformative and beneficial technology ever invented – particularly to accelerate scientific discovery. AlphaFold was powerful proof of this fact. But AI is a dual-purpose technology. As we work to reap its benefits, we have to address two central questions. The first is about risks from bad actors, or people who would use this technology for malicious ends. If we really want to unlock a golden era of progress, we have to enable good actors to continue to make advancements, while restricting access to would-be bad actors. The second question is how we ensure we stay ahead of novel risks that could arise as we approach AGI. This includes things like deceptive misalignment, which we discuss in our recent update to the Frontier Safety Framework. These concerns are not far-off or far-fetched, nor are they limited to one particular geography. They are global concerns that require focused, international cooperation. We still have work to do to find the best path towards the best future. There are many questions we’ve yet to answer about what we want society to look like post-AGI. I look forward to more collaboration on these urgent questions at the next AI Summit, and beyond.

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  • Google DeepMind reposted this

    Privacy-enhancing technologies (PETs) can provide organisations with enhanced security and confidentiality of data and code, but several challenges and barriers stand in the way of their adoption. One such barrier is a lack of trust: sceptical, privacy-aware individuals find it difficult to trust that PETs will effectively keep their sensitive data and code protected and safe. In this research, we set out to answer a set of research questions regarding trust in Google’s Project Oak. We aimed to analyse different transparency measures that PET providers can use to increase trust, and the extent to which they do so in practice. Find out more. #Privacy #Trust https://lnkd.in/dFuyxvWE

    Trust and transparency in privacy-enhancing technologies

    Trust and transparency in privacy-enhancing technologies

    theodi.org

  • You can now use our state-of-the-art video generation model Veo 2 in YouTube Shorts. 🎥 With the Dream Screen feature, creators can: ✨ Generate standalone clips which fit seamlessly into your storytelling with a quick text prompt ✨ Make unique backgrounds for videos 💡 With a better understanding of real-world physics and movement, the model can help render specific styles or cinematic effects. 🔍 Any content generated using this tool is labelled with SynthID, which accurately identifies AI-generated images, audio, text and video. 🌐 These features are launching to everyone in the US, Canada, Australia, and New Zealand - with plans to expand in the future. Find out more → https://goo.gle/4jTa7nt

  • Google DeepMind reposted this

    View profile for Claudiu Musat

    Research Manager at Google DeepMind

    Come and join us for our workshop, Natural Interactions with Foundation Models, at AMLD - Applied Machine Learning Days 2025 in Lausanne 🇨🇭! Together with my colleagues Diego Antognini, PhD, Leandro Kieliger, Philippe Schlattner, Vincent Coriou, and Anastasia Fadeeva from Google DeepMind, we are excited to show you how to use stroke interactions to interact with large language models. We hope to see many of you at AMLD - Applied Machine Learning Days - Applied Machine Learning Days, especially on Friday, February 14th, from 14:00 to 17:30! If you plan to attend, please fill out this form in advance: https://lnkd.in/eX2B3vS6. Learn more about AMLD: https://lnkd.in/egqVyeQ9

    [Computational Request] AMLD Workshop - Natural Interactions with Foundation Models - 14th Feb 2025

    [Computational Request] AMLD Workshop - Natural Interactions with Foundation Models - 14th Feb 2025

    docs.google.com

  • Today, we’re making Gemini 2.0 available to everyone - and expanding the model family. ✨ Say hello to: 🔵  An updated 2.0 Flash, which is optimized for high-volume, high-frequency tasks at scale - enabling developers to start building production applications. You can now use it via the Gemini API in Google AI Studio, Google Cloud’s #VertexAI platform and the Gemini app. 🔵  2.0 Pro Experimental: our best model yet for coding tasks and complex prompts. With a 2 million token context window, it’s able to analyze and understand large amounts of information. 🔵 2.0 Flash-Lite, our most cost-efficient AI model yet - now available across Google products. It has better quality than 1.5 Flash, at similar cost and speed, and comes with a 1 million token context window, multimodal input and text output. 🔵 And 2.0 Flash Thinking Experimental now available in the Gemini app. Find out more → https://goo.gle/3CMXg5p

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  • As we make progress towards AGI, developing AI needs to be both innovative and safe. ⚖️ To help ensure this, we’ve made updates to our Frontier Safety Framework - our set of protocols to help us stay ahead of possible severe risks. These include: 🟢 Outlining an industry leading approach to deceptive alignment risk 🟢 Implementing a more consistent procedure for how we apply deployment mitigations 🟢 Recommending specific security levels for different critical capabilities Find out more → https://goo.gle/4hhKDOS

    • Updating the Frontier Safety Framework

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Funding

Google DeepMind 1 total round

Last Round

Series A
See more info on crunchbase