mehulashah

10 ms·

1. 61.▲
   by mehulashah 1y ago

   AWS also had customers that had petabytes of data in Redshift for analysis. The conversation is missing a key point: DuckDB is optimizing for a different class of use cases. They’re optimizing for data science and not traditional data wareh
2. 62.▲
   by mehulashah 1y ago

   For those of you from the AI world, this is the equivalent of the bitter lesson and DeWitts argument about database machines from the early 80s. That is, if you wait a bit with the exponential pace of Moores law (or modern equivalents), imp
3. 63.▲
   by mehulashah 1y ago

   I am excited to see Databricks turn into the next Oracle. This type of acquisition was inevitable. The king is dead! Long live the king! And yes, congratulations to the Neon team! (Nikita is, after all, YC)
4. 64.▲
   by mehulashah 1y ago

   Love it, though if it’s sufficiently instructive, I bet it will go beyond education.
5. 65.▲
   by mehulashah 1y ago

   There’s something beautiful about not being riddled with previous artifacts and starting clean with how you imagine you want to build your system. If the system is large enough, you can’t do it that often.
6. 66.▲
   by mehulashah 1y ago

   First — 0.69% of total exports is blood still is surprisingly high! Remember, you can get blood from humans in your own country, and prepare it there. So, why do you need it from the US? Second — it’s amazing the detail that you can achieve
7. 67.▲
   by mehulashah 1y ago

   I agree. As a sponsor, we don’t also do it any longer. The incentives are fake. You want people to be excited about using your tool, not using it in some contrived way to win a few bucks. When the use is real, the feedback is real. Otherwis
8. 68.▲
   by mehulashah 1y ago

   There’s a larger problem here beyond careerization that is going unsaid. People are using these metrics as an assessment of their self worth. I’ve had top researchers point out that such and such publication was accepted in the industrial t
9. 69.▲
   by mehulashah 1y ago

   itch?
10. 70.▲
    by mehulashah 1y ago

    I find that people often conflate search with analytics when discussing Deep Research. Deep Research is iterated search and tool use. And, no doubt, it’s remarkably good. Deep Analytics is like Deep Research in that it uses generative AI mo
11. 71.▲
    Lessons from a nerd in salesperson's clothing(aryn.ai)

    2 points by mehulashah 2y ago|0 comments
12. 72.▲
    by mehulashah 2y ago

    I’m sorry that this happened to him. There are innumerable ways to let go of people with dignity. This isn’t the first time I’ve heard of this treatment from Google. It will not be the last. Google is a great company with great people. Goog
13. 73.▲
    Indexed storage for complex documents like PDFs,docx,PPT(aryn.ai)

    8 points by mehulashah 2y ago|0 comments
14. 74.▲
    by mehulashah 2y ago

    We should celebrate this for what it is: another brick in the wall that we’re building to achieve practical quantum computing systems.
15. 75.▲
    Not a Tech Bro(not-a-tech-bro.ghost.io)

    7 points by mehulashah 2y ago|0 comments
16. 76.▲
    by mehulashah 2y ago

    I'm so confused!
17. 77.▲
    by mehulashah 2y ago

    I'm sympathetic to the sentiment - founding engineers take on much of the same effort and ups and downs as founders, the relative difference in stock is not commensurate with the work. While I don't like VC math and we (I'm C
18. 78.▲
    by mehulashah 2y ago

    (CEO of Aryn here: https://aryn.ai ) Nice post and response to the previous one. It’s important to remember that the use cases for VLMs and document parsers are often different. VLMs definitely take a different approach than layo
19. 79.▲
    by mehulashah 2y ago

    (Disclosure, CEO of Aryn ( https://aryn.ai/ ) here) Good post. VLM models are improving and Gemini 2.0 definitely changes the doc prep and ingestion pipeline across the board. What we're finding as we work with enterpris
20. 80.▲
    by mehulashah 2y ago

    It seems that Beej built this guide to help his students. More of them are probably using Git and GitHub in anger than the other tools.
21. 81.▲
    Fun building better table extraction models(aryn.ai)

    10 points by mehulashah 2y ago|0 comments
22. 82.▲
    by mehulashah 2y ago

    Building a new kitchen consumer device is nearly impossible. This is amazing. Congratulations!
23. 83.▲
    Closing the verification gap in AI-powered unstructured analytics(aryn.ai)

    7 points by mehulashah 2y ago|0 comments
24. 84.▲
    by mehulashah 2y ago

    I don't agree at all with this post. YC's mission is to help founders start companies and help them build sustainable businesses. Towards that they've made it super simple to get started and funded, and provide guiding princi
25. 85.▲
    by mehulashah 2y ago

    This advice is much more general than academic research. It applies to startups as well.
26. 86.▲
    OpenSearch moves under Linux Foundation umbrella(linuxfoundation.org)

    9 points by mehulashah 2y ago|1 comments
27. 87.▲
    AWS moves OpenSearch under the Linux Foundation umbrella(techcrunch.com)

    18 points by mehulashah 2y ago|0 comments
28. 88.▲
    by mehulashah 2y ago

    Put it on the resume. I'd hire you.
29. 89.▲
    by mehulashah 2y ago

    So I contradicted myself above. Aggregation is probably not monotonic -- the output of the aggregation is not a subset if the input is a subset.
30. 90.▲
    by mehulashah 2y ago

    Examples of monotonic computation that fit are traditional database operators: filters, projections, joins. Interestingly enough, there is some coordination needed for joins, i.e. the items that match need to be in the same place at some po