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Minicomputers Made by Nvidia Are Powering Moscow's A.I. Drones

https://www.nytimes.com/2026/08/24/world/europe/ukraine-war-nvidia-ai-autonomous-drones.html
1•Wurel•20s ago•0 comments

Human judgment doesn't leave the software factory. It relocates

https://addyosmani.com/blog/human-judgment-doesnt-leave-the-software/
1•speckx•37s ago•0 comments

America's Murder Rate Is at a 70 Year Low

https://www.vox.com/future-perfect/500135/america-murder-rate-lowest-70-years
1•RickJWagner•41s ago•0 comments

Show HN: Prelo – a WordPress-style admin for AI-built sites

https://www.prelo.dev/
1•kaaberma•47s ago•0 comments

Agentic Resource Discovery (ARD): An open specification for agent discovery

https://aws.amazon.com/blogs/machine-learning/agentic-resource-discovery-ard-an-open-specificatio...
1•metrofun•3m ago•0 comments

Show HN: Icarus – ask a codebase why, and get the pull request it came from

https://icarus-website-kappa.vercel.app
1•alankritxghoshx•3m ago•0 comments

Neither HTML nor Markdown is enough: a way out of the AI doc dilemma

1•xiongjy2104•4m ago•0 comments

Show HN: FormForge – offline form filler for QA that ships its own test suite

https://chromewebstore.google.com/detail/formforge-—-form-filler-f/alkelkiiomnmjiajjcecjeicmhfh...
1•arafat-92•5m ago•0 comments

Show HN: Unlose – Windows VSS snapshots before your AI agent deletes your files

https://github.com/unlose-app/unlose
1•unlose•5m ago•0 comments

Pi vs. the official DeepSeek Harness on the same local model (Qwen3.8-27B)

https://github.com/promptdriven/pdd/blob/main/research/omlx-qwen38-pi-deepseek-harness-2026-08-23...
1•gltanaka•6m ago•0 comments

The Monopoly of Hate

https://riccardogenco.github.io/The-Monopoly-of-Hate/
1•obs3ssion•6m ago•0 comments

PropertyFlags – what 26 government registers say about a house, at a glance

https://propertyflags.com.au
1•pkuguiscan•6m ago•0 comments

I share links on my blog

https://michaelharley.net/posts/2026/08/15/how-i-share-links-on-my-blog/
1•surprisetalk•6m ago•0 comments

Analysis: Can we license LLM generated "vibe code" into Free Software?

https://fsfe.org/news/2026/news-20260825-01.en.html
1•kirschner•7m ago•0 comments

GNU radio switching to MIT licence

https://www.gnuradio.org/news/2026-05-21-gr4-community-stewardship/
1•KolmogorovComp•7m ago•0 comments

Gunicorn now supports HTTP/2 h2c

https://gunicorn.org/guides/http2/
1•timkofu•8m ago•0 comments

Show HN: Trace – Offline Mac meeting transcription, overhauled from HN feedback

https://traceapp.info/changelog
1•AG342•9m ago•0 comments

Show HN: Life Biomes, a habit tracker that lives in your email

https://lifebiomes.app/demo
1•agawish•13m ago•1 comments

Show HN: Conversational Data Intelligence Accelerator

https://geekyants.com/ai-accelerator/conversational-data-intelligence-accelerator
2•vanessa1211•15m ago•0 comments

Show HN: Flutter Starter A production-ready Flutter app boilerplate

https://github.com/GeekyAnts/flutter-starter
2•Harish_0089•16m ago•0 comments

Don't Wordle

https://dontwordle.com/
2•Hbruz0•17m ago•0 comments

The Architecture of Open Source Applications

https://aosabook.org/
1•melvinroest•17m ago•1 comments

Qwen 3.8-Flash-Next releasing tomorrow (125B a6B)

https://modelscope.cn/models/Qwen/Qwen3.8-Flash-Next
3•garo-pro•17m ago•1 comments

Aito v2: a predictive database over linked data, with vectors, graphs and SQL

https://aito.ai/blog/aito-v2-public-beta/
1•arauhala•17m ago•0 comments

GenAI prompting Dutch secondary schools to rethink how they assign homework

https://nltimes.nl/2026/08/25/ai-prompting-dutch-secondary-schools-rethink-handle-homework
1•giuliomagnifico•20m ago•0 comments

Por que sua skin atual está limitando O nível de jogo

https://victormignone.substack.com/p/por-que-sua-skin-atual-esta-limitando
1•victormignone•20m ago•0 comments

Maps of Osaka

https://chyuang.com/writing/maps-of-osaka/
2•yongyongyong•20m ago•0 comments

Elm releases its first update since 2019

https://github.com/elm/compiler/releases
1•nor0x•21m ago•0 comments

Show HN: Building USoC Part 1: The Wishbone Bus

http://axiomfactory.co/wishbone
2•dvc94ch•22m ago•0 comments

We built a structured entity graph for an AI agent. Then we removed most of it

https://blog.getcassis.com/context-engineering-for-analytics-agents/
1•matthieu_bl•24m ago•0 comments
Open in hackernews

GPT needs a truth-first toggle for technical workflows

1•PAdvisory•1y ago
I use GPT-4 extensively for technical work: coding, debugging, modeling complex project logic. The biggest issue isn’t hallucination—it’s that the model prioritizes being helpful and polite over being accurate.

The default behavior feels like this:

Safety

Helpfulness

Tone

Truth

Consistency

In a development workflow, this is backwards. I’ve lost entire days chasing errors caused by GPT confidently guessing things it wasn’t sure about—folder structures, method syntax, async behaviors—just to “sound helpful.”

What’s needed is a toggle (UI or API) that:

Forces “I don’t know” when certainty is missing

Prevents speculative completions

Prioritizes truth over style, when safety isn’t at risk

Keeps all safety filters and tone alignment intact for other use cases

This wouldn’t affect casual users or conversational queries. It would let developers explicitly choose a mode where accuracy is more important than fluency.

This request has also been shared through OpenAI's support channels. Posting here to see if others have run into the same limitation or worked around it in a more reliable way than I have found

Comments

duxup•1y ago
I’ve found this with many LLMs they want to give an answer, even if wrong.

Gemini on the Google search page constantly answers questions yes or no… and then the evidence it gives indicates the opposite of the answer.

I think the core issue is that in the end LLMs are just word math and they don’t “know” if they don’t “know”…. they just string words together and hope for the best.

PAdvisory•1y ago
I went into it pretty in depth after breaking a few with severe constraints, what it seems to come down to is how the platforms themselves prioritize functions, MOST put "helpfulness" and "efficiency" ABOVE truth, which then leads the LLM to make a lot of "guesses" and "predictions". At their core pretty much ALL LLM's are made to "predict" the information in answers, but they CAN actually avoid that and remain consistent when heavily constrained. The issue is that it isn't at the core level, so we have to CONSTANTLY retrain it over and over I find
Ace__•1y ago
I have made something that addresses this. Not ready to share it yet, but soon-ish. At the moment it only works on GPT model 4o. I tried local Q4 KM's models, on LM Studio, but complete no go.