Why Should Your Electricity Bill Subsidize an AI Data Center?
AI infrastructure needs electricity at a scale that is forcing utilities to rethink generation, transmission, substations, interconnections, and lon…
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Nvidia is buying power, not just selling GPUs
The Nvidia Cloverleaf data center partnership announced on Friday tells you where the real constraint in AI has moved, and it is not the chip. TechC…
The Meter Is Always Running
The Meter Is Always Running For forty years, enterprise software rested on a comfortable assumption: that it was a fixed cost. You paid a license, a…
Hosting Is Not Owning
Last week I deleted the sentence I was proudest of. It said I run hand-built inference engines: serving stacks I wrote myself, running Qwen and Deep…
Harness Engineering
Why production AI is 90% harness and 10% model. And what most pilots miss. Blake Aber · Predicate Ventures · 2026 The gap between an AI demo that la…
Using LLM for Dialogue Management Tasks
Dialogue management is the logic layer that decides what a conversational system should do next. Traditional implementations rely on finite state ma…
Optimizing LLM Model Performance for Real-Time Applications
Real-time applications, from live coding assistants to conversational voice agents, require LLM latency measured in hundreds of milliseconds, not se…
Using LLM for Dialogue Management
Dialogue management is the process of tracking conversational state and deciding what an agent should say or do next. Classical systems split this i…
Optimizing LLM Model Performance: Best Practices and Techniques
Production LLM workloads rarely fail because of model intelligence. They fail when latency spikes, context windows overflow, or inference costs scal…
Few-Shot Learning with LLM: A Deep Dive
Few-shot learning with large language models is one of the most practical ways to steer model behavior without updating weights. By embedding task-s…
LLM Trends and Future Outlook
The conversation around large language models has shifted. The frontier is no longer defined solely by parameter counts or training compute, but by…