Thinking

A recent episode of Latent Space with Joon Sung Park, co-founder of Simile AI, caused a strange flashback to my student days in industrial engineering. Long before anyone talked about generative AI, we learned to use a piece of software called Arena to build probabilistic simulations of airports, supermarkets, factories, and other complex systems. The basic idea was simple and surprisingly powerful. Instead of changing the real system, you built a simplified version of it on a computer. Customers arrived according to some probability distribution. A cashier took a variable amount of time to serve them. Queues formed, resources became occupied and available again. You could add another checkout lane, change the staffing level, or rearrange a production line, run the simulation thousands of times, and see what happened before spending money in the real world. ...

When an artificial intelligence system gives us a wrong answer, almost everyone reaches for the same explanation, which is that the system never learned the thing we asked about. The information was missing from its training, and so the remedy is to supply more of it, whether that means more data, a larger model, or another round of training on our own internal documents. This explanation has become so common that most organizations no longer treat it as an assumption, and they build their budgets and their improvement plans around it. ...

The idea of a “second brain” is simple. An external place to put thoughts, notes, ideas, and fragments of work, so your actual brain can focus on thinking and deciding instead of remembering. In theory, this is how knowledge compounds instead of disappearing. I have liked this idea for a long time. It is why I used Microsoft OneNote for years, and later moved to Obsidian. What I never liked was how much work these systems require in order to be useful. ...