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The HydroGym reinforcement learning platform for fluid dynamics

https://www.nature.com/articles/s41586-026-10917-6
1•loiseaujc•3m ago•0 comments

Build a Reasoning Model, Scratch 2: Base, Text Gen, KV Caching [Seb Raschka][YT]

https://www.youtube.com/watch?v=BJua0yjO5dk
1•mdp2021•3m ago•0 comments

Jeff Bezos and the Age of Amazon (2014)

https://medium.com/galleys/the-everything-store-6ce05e08ed08
1•tosh•6m ago•0 comments

India Eradicated Polio

https://altermag.com/articles/how-india-eradicated-polio
1•trojanalert•10m ago•0 comments

Neural Canvas: a fruit fly connectome demo in the browser

https://huggingface.co/spaces/Xenova/fruit-fly-simulation
1•codelion•10m ago•0 comments

The binary I ship is the binary I want to test

https://blog.maxgio.me/posts/the-binary-i-ship-is-the-binary-i-want-to-test/
1•maxgio92•12m ago•1 comments

England's teens outperform peers in most countries in maths, reading and science

https://www.theguardian.com/education/2026/sep/08/england-teenagers-outperform-peers-in-most-coun...
2•defrost•14m ago•0 comments

Logitech launches MX Keypad for developers

https://news.logitech.com/press-releases/news-details/2026/Logitech-Unveils-MX-Keypad-for-Develop...
1•fourfire•15m ago•0 comments

Is the UK government the new training ground for AI execs?

https://www.theguardian.com/technology/2026/sep/07/architect-uk-ai-policy-quits-anthropic-conflic...
1•nixlaz•16m ago•0 comments

CERN LHCb upgrade under threat after UK pulls funds

https://www.researchprofessionalnews.com/rr-news-europe-infrastructure-2026-8-lhcb-upgrade-still-...
1•g6pdh•18m ago•0 comments

Atoonk/packetio: high-performance packet I/O library for Go

https://github.com/atoonk/packetio
1•pjf•19m ago•0 comments

Please consider running a NTP server in the NTP Pool

https://dreamstation.systems/personal/ntppool.html
4•robinpie•19m ago•0 comments

Show HN: EdgePad – tool for configuring edge touchpad gestures on Linux laptops

https://github.com/assembledev/edgepad
2•dev-e•19m ago•0 comments

Isthmus: History as an Answer Key in Cross-Field Retrieval [pdf]

https://darksigma.com/cross-field-retrieval-benchmark-isthmus.pdf
1•LumiTharMan•20m ago•0 comments

The firms turning recruitment into X Factor-style competitions

https://www.bbc.co.uk/news/articles/cgk43mn42g7o
2•baloki•21m ago•0 comments

Two children died from gene therapies in China: where the field goes next

https://www.nature.com/articles/d41586-026-02497-2
3•sbulaev•27m ago•1 comments

Python Turtle Graphics

https://docs.python.org/3/library/turtle.html
2•gebt•27m ago•0 comments

DeepSeek v4.1 Flash is now available for internal beta testing

3•dares2573•29m ago•0 comments

Machine learning of artistic fingerprints in jazz

https://www.nature.com/articles/s42256-026-01279-9
1•tobr•31m ago•0 comments

"Hammock Driven Development" (2010)

https://www.youtube.com/watch?v=f84n5oFoZBc
1•birdculture•36m ago•0 comments

A Unified Benchmark for Egocentric Human-to-Robot Dexterous Hand Image Editing

https://github.com/HandEdit/HandEdit
1•kaonashi-tyc-01•38m ago•0 comments

Refine Cycle: self-improvement plugin for Hermes Agent

https://github.com/Bergschloss/Refine-Cycle-for-Hermes-Agent
1•1134taras•39m ago•0 comments

Show HN: Use Strava's official MCP with other chatbots

https://github.com/leecjohnny/strava-mcp-gateway
1•leecmjohnny•40m ago•0 comments

I talked to deep buddy about AI solving Navier Stokes rumors

https://www.echohive.ai/deep-talk-buddy/navier-stokes
1•echohive42•43m ago•0 comments

How AI based programming could work (2016)

https://bjenik.com/AIBasedProgramming/
1•andsoitis•47m ago•1 comments

A Zero-Dark-Matter Mechanical Model of Cosmology

https://github.com/IoannisKousoulakos/THE-KOUSOULAKOS-MODEL-OF-COSMOLOGY-WIP/tree/main
1•ppkuio•50m ago•0 comments

US attacks UK plans to boost traditional media on social platforms

https://www.theguardian.com/us-news/2026/sep/07/trump-administration-attacks-uk-social-media-plans
5•beardyw•53m ago•2 comments

Why Taiwan's Silicon Shield Is Failing

https://nationalinterest.org/blog/techland/why-taiwans-silicon-shield-is-failing
2•baud147258•55m ago•1 comments

Show HN: Hybrid Nav2 and PPO RL for indoor Lidar-only robot navigation

https://github.com/Sourav29-2/ppo-lidar-navigation-
1•Ros_Sourav•59m ago•0 comments

Stable Singularity of the Euler Equations on R^3 without forcing – Anima on AI

https://anima-ai.org/2026/09/07/stable-singularity-of-the-euler-equations-on-r3-without-forcing/
1•bjenik•59m 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.