i read this at least once a month.

Purdue University's IDEAS Lab built an autonomous drone that tracks runners through dense forests completely without GPS or cloud networks. By running 3D LiDAR mapping and obstacle-avoidance AI entirely on-chip, it can weave under tree canopies and predict target movement through blind spots in real time. Massive implications for next-gen search & rescue and edge AI.

if you have a qwen3.5 4b around, please try steering neurons L14 N8949 +1 and L13 N7956 -1 now you have evil qwen recipe: dose × median(‖resid‖ leaving layer L, tokens 1:) / ‖W_down[:, n]‖` at the down_proj at every input

sidebar any rational society would have positive electrons and negative protons but we got fucked over by benjamin franklin

I described a man in terms of radians in Reno just to watch him pi

Anthropic reasoning yields the best graphics

I encouraged a man in Reno just to watch him try

hear me out, mathematicians entering ai alignment maybe consider this challenge. i think its probably millennium level problem(?) take any complex real world software, like a browser or a kernel. let's pick a kvm based sandbox, which i suspect is somewhat less complex than chromium(?), running an increasingly capable, potentially adversarial AI agent. we want to formally prove one simple property, no matter what code the agent executes inside the VM, it cannot escape and compromise the host. for that we need to prove the entire relevant software stack, kvm, cpu virtualization, kernel, virutal devices that could affect the isolation. (to make things easiers, lets assume hardware wont have weird states) can we mathematically establish whether formally verifying a system of this complexity is even computationally feasible?