🤖 AI that creates AI: ASI-ARCH finds 106 new SOTA architectures

ASI-ARCH — experimental ASI that autonomously researches and designs neural nets. It hypothesizes, codes, trains & tests models.

💡 Scale:
1,773 experiments → 20,000+ GPU-hours.
Stage 1 (20M params, 1B tokens): 1,350 candidates beat DeltaNet.
Stage 2 (340M params): 400 models → 106 SOTA winners.
Top 5 trained on 15B tokens vs Mamba2 & Gated DeltaNet.

📊 Results:
PathGateFusionNet: 48.51 avg (Mamba2: 47.84, Gated DeltaNet: 47.32).
BoolQ: 60.58 vs 60.12 (Gated DeltaNet).
Consistent gains across tasks.
🔍 Insights:
Prefers proven tools (gating, convs), refines them iteratively.
Ideas come from: 51.7% literature, 38.2% self-analysis, 10.1% originality.
SOTA share: self-analysis ↑ to 44.8%, literature ↓ to 48.6%.

@datascience_bds