this post was submitted on 04 Jun 2024
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[–] fubarx@lemmy.ml 9 points 5 months ago

You still need a massive fleet of these to train those multi-billion parameter models.

On the invocation side, if you have a cloud SaaS service like ChatGPT, hosted Anthropic, or AWS Bedrock, these could answer questions quickly. But they cost a lot to operate at scale. I have a feeling the bean-counters are going to slow down the crazy overspending.

We're heading into a world where edge computing is more cost and energy efficient to operate. It's also more privacy-friendly. I'm more enthused about a running these models on our phones and in-home devices. There, the race will be for TOPS vs power savings.