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viksit

HN member
Joined
Thu, Apr 30, 2009, 11:51 PM UTC
HN karma
1,363
Public activity
396 items

About viksit

@viksit anywhere fine internet tools are sold.

2x founder. Independent AI researcher and startup advisor.

prev: led ai @dropbox, built language models @myralabs, worked on ml @bloomreach_inc

Recent public activity

  1. comment
    Comment #47938212

    > heavily-customized and terminal-heavy setup this exactly. most people can’t set it up that well.

  2. comment
    Comment #47343174

    underrated comment haha. made my day

  3. comment
    Comment #46839017

    I think the point here is the bot didn’t come up with the idea on its own, but was seeded by a human with an entrenched interest / experience in that space. The PR around Moltbook …

  4. comment
    Comment #45792487

    this is a great question. what are the main use cases that you have for this? i’ve been working on a library for something similar and exposing it via an mcp interface. would love …

  5. comment
    Comment #45551028

    Yes! thanks for the memory haha.

  6. comment
    Comment #45051983

    you definitely succeeded in your humorous endeavors ;) i snorted haha

  7. comment
    Comment #44825725

    In my fourth post in the series, I tackle how to make multi-step agent workflows learn behavior from data. Most agents today rely on vibes: prompt tuning, hand-written templates, a…

  8. story
  9. comment
    Comment #44752617

    mostly aligned on this. couple of thoughts: - raw accuracy is now a "vanity" metric. so the benchmarks need to get more sophisticated, and i think they're going to have to be far m…

  10. comment
    Comment #44752541

    vJEPA models, lecun's approach towards world models that have been derided by a lot of naysayers. (personally I think thats the way to go)

  11. comment
    Comment #44745290

    they’ve already written one! see omar’s x account for details!

  12. comment
    Comment #44663981

    Based on the feedback from my last HN post on differentiable routing, I ran a follow-up benchmark: local RNN vs GPT-4o for tool selection in LLM workflows. Same accuracy, 40% lower…

  13. story
  14. comment
    Comment #44554666

    Following up on my last post about optimizing tool selection with differentiable programming, I’ve been thinking about how to extend those ideas to full agent workflows. This post …

  15. story
  16. comment
    Comment #44501265

    would you have a link?

  17. comment
    Comment #44501264

    there's a world where the model could infer that as well!

  18. comment
    Comment #44501257

    yes, AFAIK right now, there are no easy ways of "slimming" context because no one knows what it should be or how.

  19. comment
    Comment #44501251

    great q. thats coming up as a future post in the series.

  20. comment
    Comment #44501248

    this is really interesting! yes, its my substack. also, if you're down, love to connect and talk more about what use cases / techniques you're using. I'm @viksit on X dms if that w…

  21. comment
    Comment #44477933

    for sure, there's a way here where I think we ought to be able to learn multiple tool calls and prompts together with real world data. investigating that next.

  22. comment
    Comment #44477927

    (author here, put the code in a gist here for reference) https://gist.github.com/viksit/c67d1d960c4cec89488290496defb...

  23. comment
    Comment #44477825

    +1 thanks for mentioning MCP! re: different tools (apis vs mcps). in my mind, there should be no real difference at what kind of tools is called at this moment since I model this a…

  24. comment
    Comment #44477807

    +1 - you can propagate the loss for a workflow across prompts + tools, which would make it much better to do resilient workflows. or "agents" as everyone calls them now ;)

  25. comment
    Comment #44477804

    this is my goal :) appreciate the feedback.