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🧵 Just watched a 45-min deep dive on AI scaling laws. Here are the 5 insights that blew my mind:
1/ The "data wall" is real — but it's not where you think. Most companies hit quality bottlenecks before quantity ones. The fix? Synthetic data pipelines that self-improve.
2/ Inference costs will drop 10x in 18 months. That changes every business model built on API pricing.
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I just spent 45 minutes watching a masterclass on AI scaling — so you don't have to. Here are the key takeaways for anyone building in this space:
The bottom line:We're entering an era where the competitive moat isn't data volume — it's data quality and inference efficiency.
Three things I'm changing in my approach after this...
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This Week in AI
The Scaling Laws Nobody's Talking About
There's a widely held belief in Silicon Valley that AI progress is all about scale — more data, more compute, bigger models. But a fascinating 45-minute conversation this week challenged that assumption head-on...
Est. reading time: 3 min · 487 words
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