Good article. Now would anyone tell me how do I short AI?

You short a big tech stock of your choice. They’re all up to their eyeballs in this and if it pops the entire tech sector will crater

Language is one of communication contracts. LLModels leverage these contracts to communicate data structures (shapes) that emerge when evaluating input. They are so good at prediction that when you give them a clue of a shape they will create something passable, and they keep getting better with training.

I hear there's work being done on getting the world models out, distilling the 'cortex-core' (aka the thinking without data), to perhaps see if they're capable of more, but so far we're looking at holograms of wishful thinking that increase in resolution, but still lack any essence.

This begs a question - can true intelligence even be artificial?

There's no seahorse emoji? Funny, but I can vividly remember it. It was pinkish-orangey. I even feel I used it several times. Feels strange..

You guys rock! I'm very curious how will this perform against real word data, where small nuance matters. Also have you tested it beyond 128K context window?

Oreole is not a plug-and-play yet. From their docs ( https://www.orioledb.com/docs ) > OrioleDB currently requires a set of patches to PostgreSQL to enhance the pluggable storage API and other PostgreSQL subsystems. All of these patches have been submitted to the PostgreSQL community and are under review.

(Opinions are my own, not of my employer)

I think that "under review" claim is doing some very heavy lifting, especially when it relates to their changes to index tuple lifecycle management. The patches that have been submitted are unlikely to get committed in full anytime soon, even after substantial changes to the patches' designs.

PostgreSQL just has not been designed for what OrioleDB is doing, and forcing OrioleDB's designs into PostgreSQL upstream would a lot of (very) sharp edges that the community can't properly test without at least a baseline implementation - which critically hasn't been submitted to upstream. Examples of these sharp edges are varsized TIDs, MVCC-owning indexes, and table AM signalled index inserts.

There are certainly ideas in OrioleDB's designs that PostgreSQL can benefit from (retail index tuple deletion! self-clustering tables!), but these will need careful consideration in how this can be brought into the project without duplicating implementations at nearly every level. A wholesale graft of a downstream fork and then hoping it'll work out well enough is just not how the PostgreSQL project works.

Oh this dampens my expectations, I was under the wrong impression that it will stabilise outside of Postgres before it is merged.