硬體

AI 晶片、GPU、資料中心、邊緣裝置與硬體安全。

推論系統

Daedalus-150M Replaces Two-Thirds of Attention Layers With Convolutions, Accelerating CPU Decoding by 1.76× at 2K Context

Daedalus-150M is designed specifically for single-user, 4-bit CPU inference, allowing most network layers to avoid repeatedly reading an ever-growing KV cache. Preliminary results indicate that its speed advantage increases with context length, but the model is limited to 2K context, and its performance figures still await independent reproduction across different hardware.

代理工具

NVIDIA AVO Completes All 183 Levels in the ARC-AGI-3 Public Set With About 12% Fewer Actions Than VISTA

NVIDIA adapted the AVO agent architecture, originally used for evolutionary search over GPU kernels, to interactive reasoning and achieved a 100.00 RHAE score with Claude Opus 5. The results show that agent memory and verification loops can substantially change the performance of the same model, but they cover only public environments, and the comparison with VISTA is not a controlled ablation.

硬體

VSPG Updates Discrete-Action Actors Without Backpropagation, Outperforming the DNN Baseline on Both SustainGym Benchmarks

VSPG stores each action as a unit hypervector, reformulating the softmax policy gradient as advantage-weighted vector superposition and normalization, without requiring automatic differentiation for the actor or optimizer state. It achieves higher returns and greater resilience to bit errors in two building-control climates, but performance depends heavily on the fixed encoder.