Viewing profile — aldielshala
aldielshala
HN member- Joined
- Sat, Apr 18, 2026, 10:54 AM UTC
- HN karma
- 2
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- 13 items
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About aldielshala
Recent public activity
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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…
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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…
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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.
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Comment #47884208
Curious how it handles 10K+ notes performance-wise, does it index everything or lazy-load?
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Comment #47873141
Trying to use human attention, instead of Transformer attention.
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Comment #47873033
Intent debt is a useful framing. A few comments explaining "why" instead of "what" would have saved hours of guessing.
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Comment #47871690
Finally an AI that takes someone's job and nobody's upset about it.
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Comment #47871060
My contribution today: fewer LLM calls, fewer GPU hours, less CO2.
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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.
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Comment #47862107
Yes, maybe context engineering (prompting is just one part of it) and soft skills.
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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…
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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.
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Comment #47850130
Communication, with both human and AI.