Exafunction aims to reduce AI dev costs by abstracting away hardware
TechCrunch
APRIL 28, 2022
The most sophisticated AI systems today are capable of impressive feats, from directing cars through city streets to writing human-like prose. But they share a common bottleneck: hardware. Developing systems on the bleeding edge often requires a huge amount of computing power. For example, creating DeepMind’s protein structure-predicting AlphaFold took a cluster of hundreds of GPUs.
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