Wondering how to implement your own inference engine? Here is a nice simple blueprint to get started.

This is definitely an interesting declarative language. Looking forward to more such neurosymbolic approaches.

Interesting endeavor... this is nice to have an attempt at a formal definition with no axiom introduced.

A neat little introduction to an important field in computer science. Lambda calculus is often too little known but it has very important ramifications in several fields.

When you put the marketing claims aside, the limitations of those models become obvious. This is important, only finding the root cause of those limitations can give a chance to find a solution to then.

Very interesting research. Looks like we're slowly moving away from the "language and thinking are intertwined" hypothesis. This is probably the last straw for Chomsky's theory of language. It served us well but neuroscience points that it's time to leave it behind.

Now this is an interesting paper. Neurosymbolic approaches are starting to go somewhere now. This is definitely helped by the NLP abilities of LLMs (which should be used only for that). The natural language to Prolog idea makes sense, now it needs to be more reliable. I'd be curious to know how many times the multiple-try path is exercised (the paper doesn't quite focus on that). More research is required obviously.

Finally a path forward for logic programming? An opportunity to evolve beyond Prolog and its variants? Good food for thought.

Of course I recommend reading the actual research paper. This article is a good summary of the consequences though. LLMs definitely can't be trusted with formal reasoning including basic maths. This is a flaw in the way they are built, the bath forward is likely merging symbolic and sub-symbolic approaches.

This is a short article summarizing a research paper at the surface level. It is clearly the last nail in the coffin for the generative AI grand marketing claims. Of course, I recommend reading the actual research paper (link at the end) but if you prefer this very short form, here it is. It's clearly time to go back to the initial goals of the AI field: understanding cognition. The latest industrial trends tend to confuse too much the map with the territory.

On the importance of invariants and consistent requirements in our trade. Admittedly it's a long demonstration but it show the point well.

Interesting way to look at our profession... I wonder if this is the core reason of why we have a hard time to turn into a proper engineering discipline, is it even possible at all then?

Nice resource to get started with Prolog.