AI research is splitting into groups that can train and groups that can only fine tune

Reddit r/artificial News

Summary

Discussion on how compute access is becoming the primary driver of AI progress, creating a divide between organizations that can train large models and those limited to fine-tuning existing foundation models.

I strongly believe that compute access is doing more to shape AI progress right now than any algorithmic insight - not because ideas don't matter but because you literally cannot test big ideas without big compute and only a handful of organizations have that. everyone else is fighting over scraps or fine tuning someone else's foundation model. Am i wrong or does this feel accurate to people working in the field? Curious to know what you think
Original Article

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