Reading up on LLaMA

AT&T and other corporations are shifting significant portions of their AI workloads to free, open‑source models to cut costs and reduce vendor dependence.

Mark Zuckerberg argues that superintelligence should be democratized so everyone can benefit, warning that centralized control would stifle human potential and innovation.

Modern LLMs have grown complex with many attention variants and mixture-of-experts, echoing the messy evolution of recommendation systems.

AGI capable of most cognitive work could arrive by 2028–2034, but deployment will lag capability due to verification bottlenecks, uneven automation, and institutional friction.

LLM inference works by tokenizing input, computing embeddings through transformer layers, then generating tokens autoregressively with KV caching and quantization optimizations.