On Space

Related to the prior post on reflection, reflection requires space. Space is needed to explore and investigate, test, probe, and question. And adapt.

On Reflection

What is the value of reflection, and how can it be incorporated into AI?

In Transit

This week I’ll be out of town on a retreat. More later, but posts may be shorter/off the usual schedule.

Forecasting is Hard

Assume for argument’s sake that we have no idea how AI will transform the future.

High Floors

Ensuring high floors for performance is arguably more important than slightly raising the performance ceiling (SOTA chasing). The worst case examples are the ones that get shared, so ensure that they aren’t that bad.

Full Circle

Google search made it easier to access relevant and useful information via a clean design and very simple interface.

Push and Pull

Building on yesterday’s post, there can be a pull towards digitalization as access to compute, technology, prediction, etc. gets easier and cheaper. But don’t blindly follow that pull at the expense of the physical.

Drag and Drop

With prediction getting cheaper and cheaper, there is more RPG-ification of day-to-day life. Decisions being outsourced to AI means that decisions are being outsourced to dice. These models are estimating probabilities and acting upon them. In a way, we are too when we make our own decisions, but it’s good to keep this in mind explicitly.