Group aims to create open, efficient, and sustainable platforms for scalable AI
Several companies in the AI industry announced a new consortium aimed at making AI platforms more open, efficient, and sustainable. The initial companies include Ampere which leads the effort, along with Cerebras Systems, Furiosa, Graphcore, Kalray, Kinara, Luminous, Neuchips, Rebellions and Sapeon. Additional participants are expected to join in the coming months.
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The AI Platform Alliance was formed specifically to promote better collaboration and openness when it comes to AI and comes at a pivotal moment not just for the technology industry, but for the world at large. The recent explosion of AI has created unprecedented demand for compute power to train and run these workloads. While AI training requires large amounts of compute up front, AI inferencing can require up to 10x more total compute over time, creating an even larger problem as the scale of AI usage increases. One of the goals of the AI Platform Alliance is to increase the power efficiency and cost efficiency of hardware for AI to deliver better total performance than with GPUs.
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Because AI solutions can be complex to implement, the AI Platform Alliance will work together to validate joint AI solutions that provide a better alternative than the GPU-based status quo. By developing these solutions as a community, this group will accelerate the pace of AI innovation by making AI platforms more open and transparent, by increasing the efficiency of AI to solve real-world problems, and delivering sustainable infrastructure at scale that is environmentally friendly and socially responsible.
Ampere is a modern semiconductor company designing the future of cloud computing with the world’s first Cloud Native Processors. Built for the sustainable Cloud with the highest performance and best performance per watt, Ampere processors accelerate the delivery of all cloud computing applications. Ampere Cloud Native Processors provide industry-leading cloud performance, power efficiency and scalability.
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