Sparse Efficiency vs. Superposition: The Interpretability Tradeoff

·LessWrong··

Today’s frontier models train in an expensive style: dense forward passes, huge matrix multiplies, and broad weight updates.The human brain (~5 MWh over 28 years) is an existence proof that learning can be vastly more energy efficient - about 10,000x - than modern AI training runs (https://coefficientgiving.org/research/how-much-computational-power-does-it-take-to-match-the-human-brain/).The human brain does not achieve this by activating everything all at once. Normal cognition is extremely spa...

Read full article →

Related Articles

Kolibri: A Sovereign Open-Weight Model
bastitx · Hacker News · 9h ago
Pi 1.0
sergiotapia · Hacker News · 1d ago
Updates to Full Disk Access in macOS
notfirstpost · Hacker News · 23h ago
FTL: A new operating system for clouds
romac · Hacker News · 4h ago
Court agrees with EFF: Utah's VPN law demands a technical impossibility
hn_acker · Hacker News · 1d ago