From Wired UK, June 16:
An AI chip is any processor that has been optimised to run machine learning workloads, via programming frameworks such as Google’s TensorFlow and Facebook’s PyTorch. AI chips don’t necessarily do all the work when training or running a deep-learning model, but operate as accelerators by quickly churning through the most intense workloads. For example, NVIDIA’s AI-system-in-a-box, the DGX A100, uses eight of its own A100 “Ampere” GPUs as accelerators, but also features a 128-core AMD CPU.
AI isn’t new, but we previously lacked the computing power to make deep learning models possible, leaving researchers waiting on the hardware to catch up to their ideas. “GPUs came in and opened the doors,” says Rodrigo Liang, co-founder and CEO of SambaNova, another startup making AI chips.
In 2012, a researcher at the University of Toronto, Alex Krizhevsky, walloped other competitors in the annual ImageNet computer vision challenge, which pits researchers against each other to develop algorithms that can identify images or objects within them. Krizhevsky used deep learning powered by GPUs to beat hand-coded efforts for the first time. By 2015, all the top results at ImageNet contests were using GPUs.
Deep learning research exploded. Offering 20x or more performance boosts, NVIDIA’s technology worked so well that when British chip startup Graphcore’s co-founders set up shop, they couldn’t get a meeting with investors. “What we heard from VCs was: ‘what's AI?’” says co-founder and CTO Simon Knowles, recalling a trip to California to seek funding in 2015. “It was really surprising.” A few months later, at the beginning of 2016, that had all changed. “Then, everyone was hot for AI,” Knowles says. “However, they were not hot for chips.” A new chip architecture wasn’t deemed necessary; NVIDIA had the industry covered.
GPU, IPU, RPU – they’re all used to churn through datasets for deep learning, but the names do reflect differences in architecture.
Graphcore....
....MUCH MORE
If interested see also the second link in today's "The metaverse is coming, but Big Tech’s latest obsession needs safeguards" post.
