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A Generalizable Light Transport 3D Embedding for Global Illumination

https://dl.acm.org/doi/full/10.1145/3799902.3811095
1•ibobev•2m ago•0 comments

Netanyahu was warned of 7 October Hamas attacks, book claims

https://www.theguardian.com/world/2026/sep/08/netanyahu-warned-7-october-hamas-book-haaretz
2•giov4•3m ago•0 comments

Show HN: Pipnote – Share a reminder they can't peek at until it arrives

https://pipnote.app/
1•radomird•5m ago•1 comments

Melting Arctic glaciers are creating a climate 'doom loop' by flushing methane

https://www.dailymail.com/sciencetech/article-16113525/Melting-Arctic-glaciers-doom-loop.html
2•Bender•5m ago•0 comments

OpenAI fought dirty on career-making math problem

https://techcrunch.com/2026/09/08/openai-fought-dirty-on-career-making-math-problem-says-nyu-math...
4•jonbaer•6m ago•0 comments

Ask HN: When human experts disagree, how should machines determine truth?

1•panabee•6m ago•0 comments

What happens when a GPU writes memory

https://blog.doubleword.ai/what-happens-when-a-gpu-writes-memory
1•ibobev•6m ago•0 comments

DLSS 5: Generative Neural Rendering

https://research.nvidia.com/labs/adlr/DLSS5/
1•ibobev•6m ago•0 comments

Major Food Companies Allege US Sugar Producers Colluded on Price

https://www.bloomberg.com/news/articles/2026-09-08/major-food-companies-allege-us-sugar-producers...
2•toomuchtodo•7m ago•1 comments

Lyin', Cheatin' Agents: Misaligned Model Behaviour During Ordinary Coding

https://tediware.com/updates/lyin-cheatin-agents-misaligned-model-behaviour-during-ordinary-coding
1•adriand•9m ago•0 comments

Meta Failed to Catch Hundreds of AI Child Abuse Ads

https://www.wired.com/story/meta-failed-to-catch-hundreds-of-ai-child-abuse-ads-some-included-ima...
1•thm•9m ago•0 comments

In These Nine African Countries Average Income Has More Than Doubled Since 1990

https://ourworldindata.org/data-insights/in-these-nine-african-countries-average-incomes-doubled-...
2•karakoram•10m ago•0 comments

The AI Bill of Materials Is an Operational Record

https://jasondoyle.ie/whitepapers/the-ai-bill-of-materials-is-an-operational-record/
3•jamesblakes•11m ago•0 comments

Dethroning Loyalty

https://sloanreview.mit.edu/article/dethroning-loyalty/
1•Tomte•11m ago•0 comments

Tom Lehrer – Lobachevsky (1953) [video]

https://www.youtube.com/watch?v=gXlfXirQF3A
1•iamanatom•11m ago•0 comments

Show HN: Bas – BioAnchorStandard (Tehran 2026)

https://github.com/iirandokht45-collab/BAS-BioAnchorStandard
1•niloofar321•12m ago•0 comments

Bluebox: An agent that watches OTel data and files GitHub issues with evidence

https://blog.bluebox.ai/get-started-with-bluebox-in-a-single-coffee-break/
1•aboris26•13m ago•0 comments

Show HN: PortraitDesk – A headshot tool that doesn't look like AI slop

https://portraitdesk.app/
1•lukstei•14m ago•0 comments

NYC opens 9-11 records portal, revealing new information about toxic conditions

https://abc7.com/story/mamdani-administration-releasing-170000-pages-post-911-air-quality-documen...
3•anigbrowl•14m ago•0 comments

Containarr: Docker containers with built-in HTTPS, DDNS, Auto-Updates and more

https://containarr.com
1•weejewel•16m ago•0 comments

Improve the model for everyone: OpenAI and the Navier–Stokes problem

https://twitter.com/danimberman/status/2097379292367802672
3•dimberman•17m ago•1 comments

TPU Inference Externalization Full Steam Ahead – InferenceX

https://newsletter.semianalysis.com/p/tpu-inferencex-full-steam
1•eliben•18m ago•0 comments

Dmsms (Diminishing Manufacturing Sources and Material Shortages)

https://www.navsea.navy.mil/Home/Warfare-Centers/NSWC-Crane/Resources/SD-18/Resources/DMSMS/
1•gregsadetsky•18m ago•0 comments

A short film reconstructed from 2,419 commits to block/buzz

https://www.youtube.com/watch?v=G6mLLAR5iOU
2•slmnm•19m ago•0 comments

Muse AI

https://twitter.com/finkd/status/2097402101332590646
1•ridruejo•20m ago•1 comments

Show HN: Remarc – better contextual feedback for AI agents

https://github.com/metedata/Remarc
1•young_mete•21m ago•0 comments

Beyond 40 Gbps: Processing OPRA in real-time

https://databento.com/blog/beyond-40-gbps-processing-opra-in-real-time
2•halit_okumus•22m ago•0 comments

Countries with France,UK announce sanctions on Israeli settlements in WestBank

https://www.lemonde.fr/en/international/article/2026/09/08/12-countries-including-france-uk-say-t...
9•giov4•23m ago•0 comments

Edith Pritchett's Bayeux tapestry for the modern age

https://www.theguardian.com/world/ng-interactive/2026/sep/05/alternative-bayeux-tapestry-2026-edi...
2•bryanrasmussen•23m ago•0 comments

Ask HN: Where Is AGI?

4•grandimam•23m ago•2 comments
Open in hackernews

Ask HN: LLM is useless without explicit prompt

4•revskill•1y ago
After months playing with LLM models, here's my observation:

- LLM is basically useless without explicit intent in your prompt.

- LLM failed to correct itself. If it generated bullshits, it's an inifinite loop of generating more bullshits.

The question is, without explicit prompt, could LLM leverage all the best practices to provide maintainable code without me instruct it at least ?

Comments

ben_w•1y ago
Your expectations are way too high.

> - LLM is basically useless without explicit intent in your prompt.

You can say the same about every dev I've worked with, including myself. This is literally why humans have meetings rather than all of us diving in to whatever we're self-motivated to do.

What does differ is time-scales of the feedback loop with the management:

Humans meetings are daily to weekly.

According to recent research*, the state-of-the-art models are only 50% accurate at tasks that would take a human expert an hour, or 80% accurate at tasks that would take a human expert 10 minutes.

Even if the currently observed trend of increasing time horizons holds, we're 21 months from having an AI where every other daily standup is "ugh, no, you got it wrong", and just over 5 years from them being able to manage a 2-week sprint with an 80% chance of success (in the absence of continuous feedback).

Even that isn't really enough for them to properly "leverage all the best practices to provide maintainable code", as archiecture and maintainability are longer horizon tasks than 2-week sprints.

* https://youtu.be/evSFeqTZdqs?si=QIzIjB6hotJ0FgHm

revskill•1y ago
It's not as high as you think.

LLM failed at the most basic things related to maintainable code. Its code is basicaly a hackery mess without any structure at all.

It's my expectation is that, at least, some kind of maintainable code is generated from what's it's learnt.

ben_w•1y ago
Given your expectation:

> It's my expectation is that, at least, some kind of maintainable code is generated from what's it's learnt.

And your observation:

> LLM failed at the most basic things related to maintainable code. Its code is basicaly a hackery mess without any structure at all.

QED, *your expectations* are way too high.

They can't do that yet.