It's limits and biases are well documented. But, what about the ideologies of the people behind those models? What can it tell us about their aims behind those models? Questions worth exploring in my opinion.

Interesting work, trying to get back to the source material used by a generative model. This is definitely necessary as well.

Good explanation about how sampling works. Does a good job explaining why it shines and where it is limited.

This is lesser known and probably should stay obscure... don't do that at home kids. Those alternative operators (more like tokens really) don't help with readability at all and make not much sense with UTF8 code bases.

Looks like a young but interesting tool to assess the power consumption of a service. There's been quite some work in this domain on the client side, not so much on the server side. This is welcome.

Too often forgotten. Data is indeed a mean to an end. It's not outright knowledge and will require work to be useful. It better be aligned with your needs if you want to use it for decision making.

Interesting business model. Could be a new path for at least some maintainers to be sustainably funded. Still a lot of unknowns though... probably worth keeping an eye on it.

Excellent conclusion to the recent turmoil around undefined behaviors. The way they are currently used as definitely a problem, they shouldn't be ignored in your code (although that's admittedly not that easy). There's hopefully a path forward.

A few interesting points in there. Too much hype and important points are glanced over, we'd all benefit from them being more actively explored.

An interesting but sometimes forgotten possibility for extending SQLite. Keep in mind this can lead to bad coupling between the software and the DB though which could carry interesting challenges around upgrades for instance.

OK, this is the best critique of the "Spotify Model" I've seen around. There's been plenty of unfair criticism thrown at this "model" (never aimed to be something you fully replicate though, hence the complaints I think). This one is properly balanced and doesn't just throw everything in the garbage bin, it takes the model bits by bits and try to highlight where the limits are. Very constructive.

Very nice summary of the architecture in the latest trend of transformer models. Long but comprehensive, a good way to start diving in the topic.

It seems this isn't necessary after all. At most if you like it you can put the year of creation of the copyrighted content, but the range and bumping it really isn't necessary.

Looks like an interesting (even though young) tool to make your own linters and to analyze code source.

Looks like an interesting tool to deal with dependencies in some tests.

Such generative models are getting more and more accessible. You can play with them using a few lines of python now.

A very neat 3D experiment in the browser. The 3D abilities in this context made a lot of progress lately.

Interesting points about agile and lean approaches. In my view they tend to complete each other, that said the diagnostic of Scrum as practiced in most places today is not Agile is very true. So beware about what you're doing, is it folklore? is it dogmatic? or do you really apply values and principles?

This is an interesting new family of hardware. Definitely to keep an eye on for homelabs.

Nice primer on std::variant. Covers all the bases of how to use it properly.