The real lesson is not "spend more tokens."
It's three rules:
- shrink context to high-signal tokens
- scale parallel samples only with a verifier
- match compute to query difficulty
Brute force works. Uniform brute force wastes money.
300 tokens beat 113,000 tokens at the same task.
Everything you've been told about "just use a bigger context window" is backwards. 18 models, one uncomfortable result. ๐งต
Inference cost is rewriting training economics.
An Apr 2026 paper: once you price in repeated-sampling cost, optimal pretraining shifts past Chinchilla into overtraining.
Allocate more samples to smaller models. https://t.co/KpwwUIrcYP
@simplilearn I signed up for Oxford Programme in AI and Business Analytics, and paid the fees. Now the program was to start from 7th May. The program did not start on 7th May, neither do I see the program in LLM dashboard. I raised tickets - 03419824, 03412572, but no response.
@SiddharthKG7 Optimizing for toys instead of a bloodline is a poverty mindset.
Youโre trading a lifelong support network for a slightly nicer car and a private school crest.
Stop overthinking the budget and start building the team that will carry your legacy when you're gone. ๐จโ๐ฉโ๐งโ๐ฆ๐ก๏ธ