|
The Case for Smaller AI
In this week's newsletter, we're starting to see the results of the last three years of research, experimentation, success and failure. Since ChatGPT had its iPhone moment, the dominant focus was bigger and better. And that worked really well, until it started not to.
The pitch for big AI models was simple: more intelligence, better outcomes. What nobody mentioned was that "more intelligence" came with less control. Data routed through third-party APIs you don't manage. Outputs you can't audit. Decisions you can't explain, especially to a board or regulator.
Gartner puts a hard number on what's coming: 40% of enterprise applications will embed task-specific AI agents by end of 2026, up from less than 5% today. AI is moving out of the chat window and into your workflows.
Small language models (SLMs) aren't a step backward. They're the architecture that makes AI deployable at every layer: enterprise systems, edge hardware, and the AI now embedded across your personal data and devices.
|
