piterrro

12 ms·

1.
by piterrro 12d ago
Interesting to see these experiments. This is early but imagine in few years there will be companies mostly run by agents with a light overview from a human operator. What then happens to scaling of the bussinesses? I would assume, just lik
2.
by piterrro 17d ago
They can run it on „commodity” hardware as gpus, that gives them ability to change direction fast without burning money on ASIC? The space moves fast so model on ASIC can be outdated in couple of months?
3.
by piterrro 17d ago
I’m using this model to „rerank” results from vector store. The model is provided a set of results and asked to produce a string of 1s and 0s where the offset reflects the position in the result set. The prompt goes along the line „do this
4.
by piterrro 18d ago
The problem with that is that it only works with simple, least interactive UIs. Each new UI a human will be presented needs to be learned to be ised effectively otherwise a user will be lost. Having said that, imo, Gen UI only makes sens as
5.
by piterrro 18d ago
I think there is a big misunderstanding in the space around what Gen UI is and what its used for. Lots of folks refer to it as a framework for building web apps - its not. Gen UI is a DSL for LLM to build UIs on the fly in a multi turn conv
6.
by piterrro 19d ago
The thing Im missing the most is the goal of this experiment. Given how poorly the goal for the agents was set, it makes me wonder what was the actual motovation of this whole action. Lets get the „make as much money as possible” goal broke
7.
by piterrro 22d ago
You can get determinostic output (mostly) by setting the temperature to zero. Using couple of other tricks you can get close to 100% of determinism with LLMs.
8.
by piterrro 23d ago
If you own or work for an invisible company, upvote this comment
9.
by piterrro 26d ago
I just typed a random sequence of the characters, long enough to be certain such domain doesnt exist. No only, the browser send an autocomplete request for every keystroke but for each request it returned a set of proposed domain names (whi
10.
by piterrro 27d ago
I do that in psql and it works really well. But your post got me thinking since I need to find a solution to store content of multiple documents, have a way to do FTS as well as vector similarity. I dont need that for all of the documents a
11.
by piterrro 29d ago
I get the closed source open binary approach - I would test it if I woild be in a need!
12.
by piterrro 1mo ago
RAG only makes sense if you have an LLM review the results, pick the most relevant ones and iterate further if there's a need running another query and repeating the process. Raw dump of vector search (even with reranking) is asking fo
13.
by piterrro 1mo ago
You could write that pseudocode as a prompt for the agent and get the same result. Use plan mode to understand what agent wants to do. Am i missing anything?
14.
by piterrro 1mo ago
true to that - currently using psql (in a single monolithic codebase) as: sql db, json db, vector store, logs store, full-text search, queue, message bus. multiple processes connected to it.
15.
by piterrro 1mo ago
really impressive, could that be the way to locate yourself without GPS? assuming we know more/less where we are
16.
by piterrro 1mo ago
Companies specialized in building DCs and AI labs specialized in niche models?
17.
by piterrro 1mo ago
The problem is, beside their size, they have not moat to compete in AI space. Their data centers are spread across the world in other companys DCs (btw do they own any DC actually from top to bottom?).
18.
by piterrro 1mo ago
I would propose the following, query vector store for 10 closest categories based on a query, feed it to an LLM, in the prompt ask it to produce a single digit 0-9 representing the number of the most appropriate choice. Use plain text promp
19.
by piterrro 1mo ago
https://grugbrain.dev/ Similar on this topic
20.
by piterrro 1mo ago
You can even run it on your desk if you want, a single gtx 4090 is enough. It can be fully air gapped.
21.
by piterrro 1mo ago
Accuracy can have different dimensions, depends on what you can tolerate and whether you can detect it to apply more powerful methods. Imagine you have a cheap and 99% accurate ocr. The other 1% you can detect and apply more powerful (more
22.
by piterrro 1mo ago
Most use cases dont need that kind of accuracy, just doesnt justify the 3-4usd range. I build for that exact case (tender documents, we’re processing north of 100k pages per day), it doesnt need to recognize scanned written text from 1930s,
23.
by piterrro 1mo ago
For anyone interested, I have an ocr pipeline running on rented GPUs, doing around 1000pages for 0.05-01 usd with around 0.8 seconds per page with full bounding boxes support for grounding. If you’re interested you can find contact to me vi
24.
by piterrro 2mo ago
In these situations I always use AI to respond
25.
by piterrro 2mo ago
Could this vllm port be faster to install? Im starting gpu machine multiple times a day and it takes 5 minutes to set vllm up. If Inise this port that time is minimized?
26.
by piterrro 2mo ago
Just cant believe AI slop is getting 1k stars on github in two days. Nothing really innovative about this project, nothing you cannot do yourself in two days with a coding agent. I wrote it before, OSS is changing in a way that will basical
27.
by piterrro 2mo ago
When can we run doom on it?
28.
by piterrro 2mo ago
Will it fit on ESP32??
29.
by piterrro 2mo ago
At first I felt bad about not having come up with this solution. But then I realized I have problems with writing binary search by myself in JS and immediately felt better. Now way I could have come up with Kimi Delta Attention.
30.
by piterrro 2mo ago
this is enough to keep them on the first page of HN and similar services. Its a growth strategy: invest tokens, build some "nice" project nobody wants, get some reach through publishment. Rinse and repeat. Heads up, in 12 months f

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