Homelab adventures, infrastructure deep-dives, and lessons learned building enterprise-grade systems on a budget
We're building an adaptive memory system for AI inference — memory that operates at the activation level, not the token level. Early Gemma-4-31B results: a 3.12 selectivity ratio for on-topic vs adversarial recall. Provisional patent filed.
Jane Street published the Dormant LLM Challenge answer key today. My March submission claimed all three triggers. The answer key disagrees on every model. Here's what I actually got wrong, the methodology error that drove it, and what I'd do differently with the benefit of hindsight.
Three things landed this week at Light of Baldr — an open SAE dataset for Gemma-4-31B, a working MAX Engine stack on DGX Spark, and early signal from an activation-level memory system.
The original observation has grown. Three independent measurement instruments now converge on the same universal structure inside neural networks.
What happens when AI agents develop persistent identities, shared history, and one of them goes offline — an observation from the Nomos research fleet, grounded in mechanistic interpretability data
How curiosity, physics, and looking inside neural networks revealed something unexpected about how computation organizes itself