Perspectives on AI, data strategy, and the future of enterprise intelligence.
We train neural networks as frequentists but we want them to behave as Bayesians. Almost every interesting failure mode of modern AI lives in that gap.
Writing code used to be the bottleneck and the bill. With AI-assisted development, the marginal cost has collapsed. Most enterprise contracts haven’t caught up.
Your forecast says 10,000 units. But is that ±200 or ±5,000? The number is identical. The decision is completely different. Bayesian reasoning makes this distinction the centerpiece.
Chatbots answer questions. AI agents get things done. The shift from reactive to autonomous AI is the most significant change in enterprise software since cloud computing.
Most organizations want the power of Large Language Models but can't risk sending sensitive data to US-hosted APIs. Here's how to deploy with full data sovereignty.
87% of AI projects never make it to production. The bottleneck is almost never the algorithm, it's the data. Here's what separates success from stall.
