How to achieve same intelligence with less computation? Exploring 7 technical paths
prateekj · x · 2026-08-27
Explores the mathematical meaning of "same intelligence with less computation," pointing out the redundancy in current AI model processing. The goal is to eliminate unnecessary computation while maintaining capability, rather than simply making a slightly worse model.
The post lists several potential avenues for optimization:
- Sparse activation: Don't activate the whole model for every token.
- Dynamic compute: Don't spend the same compute on every token/problem.
- Better algorithms: Build more efficient algorithms.
- Memory optimization: Utilize memory infrastructure to remember vs. recompute.
- Distillation: Compress what the large model has learned.
- Efficient representation: Move beyond transformers to represent information more efficiently.
- Cheaper operations: Make each individual operation cheaper.
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