The Real Story This Week Isn't the Model Releases—It's the Infrastructure Ungating
Meta's $13B Alberta data center bet and the steady stream of llama.cpp optimizations matter infinitely more than OpenAI's incremental GPT-5.6 or Grok 4.5 announcements, because they're solving the actual bottleneck: inference cost and latency at scale. The papers on transformer linearization and continuous-query memory aren't academic noise either—they're direct attacks on why GPU-bound inference remains prohibitively expensive, which is why llama.cpp gets four updates in a week while most model papers languish. Watch the infrastructure plays and optimization research; ignore the consumer model versioning theater.