An excellent essay about generative AI and art. Goes deep in the topic and explains very well how you can hardly make art with those tools. It's just too remote from how they work. I also particularly like the distinction between skill and intelligence. Indeed, we can make highly skilled but not intelligent systems using this technology.

Very good primer on a widespread and very hard to avoid bias. This is why it's hard for projects to properly meet deadlines.

Interesting research! Is reading code a math and logic task? Is it a language task? Well... it might be its own thing.

I guess we kind of suspected it, this studies tends to prove it. Defects are more easily found in the first files of a code review rather than in the last ones.

Interesting take on why people see more in LLM based systems than there really is. The parallels with psychics and mentalists tricks are well thought out.

A bit of a high level view on technical debt. There's a couple of interesting insights though. In particular the lack of good metrics to evaluate technical debt... and the fact that it's probably about "both the present state and the possible state" of the code base. So it's very much linked to the human cognition in order to conceive the "ideal state".

This is an excellent piece. Very nice portrait of Emily M. Bender a really gifted computational linguist and really bad ass if you ask me. She's out there asking all the difficult questions about the current moment regarding large language models and so far the answers are (I find) disappointing. We collectively seem to be way too fascinated by the shiny new toy and the business opportunities to pay really attention to the impact on the social fabric of all of this.

Interesting research on how relying on digital systems reshape our memory and our perception of our own abilities.

Fascinating research... indeed some spiders have really better cognition than we'd expect.