eskibars

12 ms·

1. 91.▲
   Show HN: Quepid now works with vector search(quepid.com)

   2 points by eskibars 3y ago|0 comments
2. 92.▲
   by eskibars 3y ago

   Personal pet project for my son who loves seeing trains: I'm trying to get a system set up to auto-rotate through live webcams when the trains are most likely to show up through their live location status. https://train.api
3. 93.▲
   Show HN: Launching a new home-grown embedding LLM for RAG(vectara.com)

   12 points by eskibars 3y ago|1 comments
4. 94.▲
   by eskibars 3y ago

   So far, we haven't really focused on code ingestion. We've had a few users try it out for that use case, but we code ingestion and generation is a bit different. We've found a lot of users have success in the natural langua
5. 95.▲
   by eskibars 3y ago

   I'd love to hear them!
6. 96.▲
   Show HN: Live Train Webcams(train.api.connelly.casa)

   15 points by eskibars 3y ago|4 comments
7. 97.▲
   by eskibars 3y ago

   I've seen a lot of this, and other problems with fine tuning, that result in real business outcomes. For example: - I've seen research orgs have a *lot* of difficult to fine tuning out something that might be taken as "f
8. 98.▲
   by eskibars 3y ago

   IMHO I think the best points you make here are the last 2. To contrast the first 2, I have seen that many users can provide really good capabilities with RAG -- especially combined with some kind of keyword/hybrid blending so that
9. 99.▲
   You don't need a vector database. You need a GenAI Platform(vectara.com)

   5 points by eskibars 3y ago|0 comments
10. 100.▲
    by eskibars 3y ago

    Also, many times I've had to wait 5 minutes for an agent to respond at all (presumably because they're way oversubscribed) and then had the "chat with an agent" thing time out and disconnect me entirely after 10 minu
11. 101.▲
    by eskibars 3y ago

    I think there are multiple facets to this argument (both for and against). Yeah, a lot of chatbots are so "stupid" or at least so obviously non-human that as a user, I have absolutely no desire to interact with them. They waste
12. 102.▲
    by eskibars 3y ago

    I wasn't, and I'm not sure how you got that out of what I said. I'm not claiming "understanding," "sentience," etc. I'm claiming there's a great deal of work in the realm of research that I&#x27
13. 103.▲
    by eskibars 3y ago

    I know the article doesn't go into this particular element, but I do wonder how much opportunity is still in front of us for adversarial LLM systems that try to detect/control for hallucinations. I'm pretty excited by the re
14. 104.▲
    by eskibars 3y ago

    Vectara is hiring a number of positions: https://jobs.lever.co/vectara Vectara is a SaaS platform built from the ground up to support LLM-focused retrieval (think LLMs for search applications) as well as using that to surfa
15. 105.▲
    by eskibars 4y ago

    > I'm sure people have thought about these things: what technical challenges exist in improving search in these areas? is it just a matter of integrating engines like the one that's linked here? Or maybe keyword searches are of
16. 106.▲
    Ask HN: Developer opinions on SaaS in-product walkthroughs

    1 points by eskibars 4y ago|1 comments
17. 107.▲
    by eskibars 4y ago

    I agree there's a place for both right now. Curious if you think that's going to be the case forever? I've been seeing huge, nearly step-function increases in precision gains for neural systems recently, and I'm wonder
18. 108.▲
    by eskibars 11y ago

    I've been collecting SF MUNI's GPS info (including speed, current position) for the past 2 months and comparing it to what should be happening (speed limit, route). This is a heatmap of where MUNI speeds most often. Full source a
19. 109.▲
    Show HN: Where SF public transit breaks rules(oddball.eskibars.com)

    2 points by eskibars 11y ago|2 comments