AI for Everyone. Then Came the Token Bill.
Cut enterprise AI costs with smarter model routing, leaner context, prompt caching, bounded agents and task-appropriate file formats.
Inference
6posts
CALM and the Revolt Against the Token
Continuous Autoregressive Language Models challenge the token-by-token bottleneck and hint at a different future for language generation.
From PDE Guarantees to LLM Inference: What BEACONS Gets Right About Reliability
BEACONS offers a model for reliability that AI systems badly need: explicit bounds, checkable guarantees, and less benchmark theater.
Engram, DeepSeek, and the return of “memory” as an architectural primitive
DeepSeek's Engram reframes memory as an architectural primitive, suggesting models may need recall structures rather than ever-larger layers.
Beyond the Token Stream: Investigating Introspective Awareness in Large Language Models
Interpretability research asks whether LLMs can detect their own internal states, moving introspection from philosophy toward experiment.
Elon Musk's Vision: Turning Tesla's Idle Fleet into a Global AI Inference Powerhouse
Musk's idea of using idle Teslas for inference turns a car fleet into a provocative vision of distributed AI infrastructure.