[ad_1] Responsible from design to deployment We’re mindful about not only advancing the state of the art, but doing so responsibly. So we’re taking measures to address the challenges raised by generative technologies and helping enable people and organizations to responsibly work with AI-generated content. For each of these technologies, we’ve been working with the…

[ad_1] Our approach to analyzing and mitigating future risks posed by advanced AI models Google DeepMind has consistently pushed the boundaries of AI, developing models that have transformed our understanding of what's possible. We believe that AI technology on the horizon will provide society with invaluable tools to help tackle critical global challenges,…

[ad_1] How summits in Seoul, France and beyond can galvanize international cooperation on frontier AI safety Last year, the UK Government hosted the first major global Summit on frontier AI safety at Bletchley Park. It focused the world’s attention on rapid progress at the frontier of AI development and delivered concrete international action…

[ad_1] 1.5 Flash excels at summarization, chat applications, image and video captioning, data extraction from long documents and tables, and more. This is because it’s been trained by 1.5 Pro through a process called “distillation,” where the most essential knowledge and skills from a larger model are transferred to a smaller, more efficient model. Read…

[ad_1] Inside every plant, animal and human cell are billions of molecular machines. They’re made up of proteins, DNA and other molecules, but no single piece works on its own. Only by seeing how they interact together, across millions of types of combinations, can we start to truly understand life’s processes. In a paper published…

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[ad_1] Introducing SIMA, a Scalable Instructable Multiworld Agent [ad_2] Source link

[ad_1] Responsible by design Gemma is designed with our AI Principles at the forefront. As part of making Gemma pre-trained models safe and reliable, we used automated techniques to filter out certain personal information and other sensitive data from training sets. Additionally, we used extensive fine-tuning and reinforcement learning from human feedback (RLHF) to align…