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Enterprises seem to accept it as a basic fact: AI models require a significant amount of compute; they simply have to find ways to obtain more of it.
But it doesn’t have to be that way, according to Sasha Luccioni, AI and climate lead at Hugging Face. What if there’s a smarter way to use AI? What if, instead of striving for more (often unnecessary) compute and ways to power it, they can focus on improving model performance and accuracy?
Ultimately, model makers and enterprises are focusing on the wrong issue: They should be computing smarter, not harder or doing more, Luccioni says.
“There are smarter ways of doing things that we’re currently under-exploring, because we’re so blinded by: We need more FLOPS, we need more GPUs, we need more time,” she said.
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Here are five key learnings from Hugging Face that can help enterprises of all sizes use AI more efficiently.
1: Right-size the model to the task
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