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aldielshala

HN member
Joined
Sat, Apr 18, 2026, 10:54 AM UTC
HN karma
2
Public activity
13 items

About aldielshala

Research Engineer.

Recent public activity

  1. comment
    Comment #47889358

    Haven't tested on a Pi yet, llm.sql is still in alpha, focused on validating that SQLite can actually work for LLM inference and profiling memory usage. That said, 210MB peak RSS s…

  2. story
    Show HN: Llm.sql – Run a 640MB LLM on SQLite, with 210MB peak RSS and 7.4 tok/s

    Hi HN, I built llm.sql, an LLM inference framework that reimagines the LLM execution pipeline as a series of structured SQL queries atop SQLite. The motivation: Edge LLMs are getti…

  3. comment
    Comment #47884708

    Nice project. I'm also working on something that pushes SQLite well beyond its typical use case. It's encouraging to see more people exploring what SQLite can really do.

  4. comment
    Comment #47884208

    Curious how it handles 10K+ notes performance-wise, does it index everything or lazy-load?

  5. comment
    Comment #47873141

    Trying to use human attention, instead of Transformer attention.

  6. comment
    Comment #47873033

    Intent debt is a useful framing. A few comments explaining "why" instead of "what" would have saved hours of guessing.

  7. comment
    Comment #47871690

    Finally an AI that takes someone's job and nobody's upset about it.

  8. comment
    Comment #47871060

    My contribution today: fewer LLM calls, fewer GPU hours, less CO2.

  9. comment
    Comment #47862543

    Everyone's focused on Meta employees, but the real concern is normalization. If Meta does this and gets away with it, some companies may quietly roll out the same thing.

  10. comment
    Comment #47862107

    Yes, maybe context engineering (prompting is just one part of it) and soft skills.

  11. comment
    Comment #47862082

    Honestly, I doubt this data is as useful as they think. Half my workday is me browsing random tabs while an AI agent does the actual work. They're going to train a model on alt-tab…

  12. comment
    Comment #47857955

    $60B for a VSCode fork with AI integration... It may show the value of the gap between vanilla LLM output and production-ready applications.

  13. comment
    Comment #47850130

    Communication, with both human and AI.