I learned a solution is to turn the documents into vectors in say PostgreSQL (with pgvector) and do a cosine similarity search with a search vector. Doing a search for embed models on HuggingFace shows nomic-ai/nomic-embed-text-v1.5 and Qwen/Qwen3-Embedding-0.6B. I might have used a larger one like Qwen/Qwen3-Embedding-4B.
There's some info for AnythingLLM[0] which supports RAG. AnythingLLM has LanceDB out of the box but also supports others including pgvector.
I just discovered the name of this. I visualized that you can do a quicksort but only recurse one of the partitions each time--the one that contains the median index. It has the same worst-case O(n^2) and can be fixed the same way choosing the median pivot of 3 potential pivots. Apparently C++'s `std::nth_element` uses quick-select and since if you choose a different target index can find any percentile not just the median.
I don't even like carrying the smallest of folding umbrellas around in case it might rain. Then if it does, this thing will hover so far above and away that you get wet anyway optimistically saving up to 50% of raindrops. 50% wet is still wet. If I have an umbrella I hold it close over my head unless I'm covering someone walking with me.
The problem isn't AI. The problem has been the mass fan-out of information and unchecked regulation, people, or algorithms that determine it. AI only makes it worse.
The first and mostly only time I use byobu was for production operations on a mysql database cluster. I thought it was some customized script or version of screen meaning Bring-Your-Own-BackUp. I later realized that's what those folding screens are called.
The general public will not care about these debates. If they have an individual humanoid AI that they've gone through many good times and bad and know each other throughout, they will be treated as a valued immediate member. Labels don't matter, just behaviour less of AI's but of humans. Shared experiences, values, and predictable behviour count for a lot (maybe everything).
An interesting shift is in how we routinely say "AI" and people hardly ever push back, vs saying "LLM" which how sounds pedantic in many contexts.
I don't recall him having any impact on the story. The movie didn't lose anything by omitting the detour. To me it's like hedonistic gods in Buddhism--all powerful but not practically consequential to humans.
The best thing that I'd used for auto-updated software with weekly updates was to prefix user-facing visible commits with "uv:" Then each week we search for them and either use the text as-is or massage it slightly. We even got it into the product itself in the Help/Release-notes menu.
Funny to ask to stop doing something I don't do or never even heard of. I typically only mark database schema migrations or other major things with special prefixes.
First thing that comes to my mind is the procedural generation in Rescue on Fractalus! (Behind Jaggi Lines) 1984 by LucasFilm Games which blew my mind on Atari 6502.
Links are broken--proper ones below. They all have a similar tone/structure, like it had a few seeds of originality but then got 'produced'. More style than substance/depth for my liking.
Well that led me down an unexpected rabbit hole. I happened to be looking for ways to subset scatter-gather queries in a distributed database using composite hash keys and this seemed relevant. Grid partitioning (or multi-dimensional indexing) I knew of, but then also found Morton Z-Ordering (Bit-Interleaving), Coprime Matrix Multiplication (Lattice Hashing), Locality-Sensitive Hashing (LSH) / Random Projections and its relation to perceptual hashing.
Then I realized it's on Daniel Lemire's blog which is very fitting. Thanks HN.
> Since Dohmke’s departure, there’s been an ongoing talent drain at GitHub. Some GitHub employees have followed Dohmke to his Entire startup[0], a new developer platform that looks like it will compete directly with GitHub. Out of the 30 employees listed at Entire, at least 11 of them used to work at GitHub.
I wish the copy button for a response included the prompt (unless it's code). So many times I'm reading a response that starts running assuming the context of the prompt and I'm left wondering what it's about for the first half.
> And can anything truly novel be created by a technology that feeds on what already exists?
When I was very young, I used to make up jokes that didn't really make sense, but they seemed novel and I cracked myself up. Late in life I wondered what truly original idea(s) I've had that wasn't an extension or mashup of existing ones or I'd learned from somewhere even subconsciously. It was very hard to come up with any. So this fault like many others that can be ascribed to machines can equally apply to ourselves.
I did finally think of a few, the clearest being the idea of 2*Pi being more fundamental than Pi back when I was in grade 7 math (I can visualize the room and lesson when the thought occurred to me) back in '77 long before I learned of Tau.
I'm hoping we'll have many of these pelican cyclist pictures collected. Then when all the models can do it well, we'll stop posting about them, and dhen the next generations of AIs train on the data we'll have these canonical archetypes.
There's some info for AnythingLLM[0] which supports RAG. AnythingLLM has LanceDB out of the box but also supports others including pgvector.
[0] https://docs.anythingllm.com/features/embedding-models