[mogget]

A thought: Don't let some of the (valid) criticism alone dissuade you from reading this.

IMO the author makes some very valid points about fuzzy products and endpoints in the current AI/data/ML/magic craze. These are under-articulated elsewhere, because, well hey there's a lot of money flowing! Who wants to be a killjoy and not "get it" (just like in 1999 ;)?

Two more specific points: 1. The descriptions of the CEO are eerily familiar to me. This guy is almost an archetype. Reminds me of a person I've worked with in that role who was also associated with a similar-ish company. It really paints the con-game side of all this.

2. A deeper point (and worth the read for me) was the author's thinking about how all this didn't fit existing needs and workflows and then has a chilling thought: "It’s possible that the market for a user-hostile data system that inaccurately predicts the future and turns its human operators into automatons exists after all, and is large." You can make an argument that this kind of thing has already happened in modern customer service and, with greater negative impact, in healthcare. I.e. where the tail of easy metrics and saleable endpoints ends up wagging the dog of quality.

[ghostcluster]

The problem, besides the condescending tone towards everyone around him, is that he doesn't present an understanding of the actual state of the field of AI and deep learning, and what's worse, he cites bad science essays that will misinform more people about how a brain works.

There's a meme going round about how the best way to refute an argument is to 'steelman' it: present the best arguments of the opposing side before refuting them. He doesn't do that here, which is one of the reasons I found it frustrating.

I agree that the way the venture raising market works today rightfully deserves some fair criticism.