Graphcore reposted this
Graphcore joins the Ultra Ethernet Consortium, helping to shape the technical and strategic direction of next-generation Ethernet. https://lnkd.in/ezPu8HqN
Graphcore has created a new processor, the Intelligence Processing Unit (IPU), specifically designed for artificial intelligence. The IPU’s unique architecture means developers can run current machine learning models orders of magnitude faster. More importantly, it lets AI researchers undertake entirely new types of work, not possible using current technologies, to drive the next great breakthroughs in general machine intelligence. Our next generation 3D Wafer-on-Wafer Bow IPU systems are helping AI innovators worldwide to build better, more innovative AI solutions, whether their focus is on language and vision, exploring graph neural networks and LSTMs or creating something entirely new. We believe our IPU technology will become the worldwide standard for artificial intelligence compute. The performance of Graphcore’s IPU is going to be transformative across all industries and sectors whether you are a medical researcher, roboticist or building autonomous cars. Our team is at the forefront of the artificial intelligence revolution, enabling innovators from all industries and sectors to expand human potential with technology. What we do, really makes a difference. We're always interested in hearing from exceptional people to join our team.
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Graphcore reposted this
Graphcore joins the Ultra Ethernet Consortium, helping to shape the technical and strategic direction of next-generation Ethernet. https://lnkd.in/ezPu8HqN
Graphcore joins the Ultra Ethernet Consortium, helping to shape the technical and strategic direction of next-generation Ethernet. https://lnkd.in/ezPu8HqN
Exciting news: Graphcore joins SoftBank Group Corp. to build next generation of AI compute.
What do the power and processing requirements of our AI future look like, and how do we build computer systems to meet those needs? Graphcore co-founder and CTO Simon Knowles breaks down the problem and serves up some solutions in his keynote talk at the Centre for Human-Inspired Artificial Intelligence (CHIA).
AI has an enormous potential for good 🌎 🌱 - but can we realistically scale it further? In his thought provoking keynote at CHIA's annual conference, Mr Simon Knowles FRS - the co-founder, CTO and EVP of Engineering of Graphcore- a British semiconductor company that develops accelerators for AI and machine learning - discussed the global costs of scaling this powerful technology. 🎞 His full talk is now available to watch online on our YouTube channel: https://lnkd.in/ef_vEujN The Royal Society, Institute for Technology and Humanity ai@cam University of Cambridge
Your monthly digest of the most important and interesting AI papers from the Graphcore Research team just landed. https://lnkd.in/eUM97ykq
Congratulations to Graphcore's co-founder and CTO Simon Knowles and Graphcore Engineering Fellow Andrew Fitzgibbon who have been named as Fellows of The Royal Society. https://lnkd.in/en9ZzCpC
Accelerate your AI intelligence with our research team's regular digest of the most consequential new papers. https://lnkd.in/geY4dkAA
Can neuroscience help us develop better AI systems? Basis Co-founder Emily Mackevicius sets our neurons firing in the latest episode. Listen/subscribe -> https://lnkd.in/eV-qKdC5
At Graphcore we're often asked about the concept of neuromorphic processors (human brain-inspired architecture), but there's much more to the relationship between neuroscience and AI as explored in the latest episode of Knowledge Distillation with Helen Byrne.
Can understanding learning and thinking in humans and other animals help us develop better intelligence systems? Basis Co-Founder Emily Mackevicius unravels the complex relationship between neuroscience and AI. Listen -> https://lnkd.in/eV-qKdC5
Graphcore reposted this
Stable Diffusion has already been downloaded more than 330 million times making it one of generative AI's biggest success stories. In this episode, Stability AI's Kate Hodesdon tells us what's new in Stable Diffusion 3 and the importance of making such a widely-used model more efficient for inference. Listen/subscribe --> https://lnkd.in/eKDAZCgg