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17 Years Later, Valve Admits They Staged the Left 4 Dead 2 Trailer Leak

https://80.lv/articles/17-years-later-valve-admits-they-staged-the-left-4-dead-2-trailer-leak
1•Baldak1•35s ago•0 comments

Making Tentacle Robots Useful [video]

https://www.youtube.com/watch?v=BvGphB0iaHE
1•fortran77•1m ago•0 comments

I made a series of creative/fake captchas

https://robots.nuth.ing
1•SouthWestAtlas•2m ago•0 comments

Show HN: Homebutler – reports what changed on your server, not what's running

https://github.com/Higangssh/homebutler
1•swq115•3m ago•0 comments

GeoGolfr

https://geogolfr.com/
1•sparkling_rage•5m ago•0 comments

Has OpenAI model solved 80-year-old Navier-Stokes problem?

https://www.firstpost.com/tech/has-openai-model-solved-80-year-old-navier-stokes-problem-mathemat...
3•bsilvereagle•5m ago•0 comments

The Legend of Zelda: Ocarina of Time – Gameplay [video]

https://www.youtube.com/watch?v=PQvD3p2yGwc
1•HelloUsername•6m ago•1 comments

What the Zelda: Ocarina of Time Remake Looks Like

https://kotaku.com/heres-what-the-zelda-ocarina-of-time-remake-looks-like-2000732136
1•mikhael•7m ago•0 comments

Reverse engineering the 2008 LogiCola, a logic drill program

https://logicola.org/blog/the-new-logicola
1•kotk•7m ago•0 comments

The new Go JSON API: twice as fast, or 1.5x slower?

https://lemire.me/blog/2026/08/29/the-new-go-json-api-twice-as-fast-or-1-5x-slower/
2•surprisetalk•7m ago•0 comments

Boots and Bullets

https://bootsandbullets.com/
1•doener•9m ago•0 comments

Canonical Evolution of Enterprise Open Source RISC-V at Hot Chips 2026

https://www.servethehome.com/canonical-evolution-of-enterprise-open-source-risc-v-at-hot-chips-2026/
2•rbanffy•9m ago•0 comments

AI Scraping on the Cheap

https://www.olafalders.com/2026/09/08/ai-scraping-on-the-cheap/
1•oalders•11m ago•0 comments

Google DeepMind Releases AlphaGenome Atlas

https://blog.google/innovation-and-ai/models-and-research/google-deepmind/alphagenome-atlas/
6•utiiiD•12m ago•0 comments

Nepal disaster is a wake-up call to take compound climate risks seriously

https://www.nature.com/articles/d41586-026-02794-w
3•Brajeshwar•13m ago•0 comments

iPod Classic 6G in QEMU

https://www.reddit.com/r/emulation/s/VL4Au2HGxq
2•dmonterocrespo•13m ago•1 comments

Is Cloudflare Down?

https://www.pasteboard.co/CulUq20USXKE.png
2•sanroot_Owl•13m ago•1 comments

ZX Spectrum: Experimenting with 1-Bit Sound

https://bumbershootsoft.wordpress.com/2026/09/05/zx-spectrum-experimenting-with-1-bit-sound/
7•ibobev•13m ago•0 comments

Show HN: Roomantic – See if that piece furniture fits before buying it

https://apps.apple.com/us/app/roomantic-furniture-planner/id6759999318
1•jfrbfbreudh•13m ago•0 comments

There's no such thing as Just a Tool

https://deadsimpletech.com/blog/no-such-thing-as-just-a-tool
1•ibobev•14m ago•0 comments

Show HN: Edge-AI device that analyzes my cannabis grow, nothing leaves the LAN

https://croplock.com/blog/
1•gullywompr•14m ago•1 comments

What Has to Arrive for Us to Call It AGI?

https://twitter.com/RcityKun/status/2097333970207932859
1•Caelus9•15m ago•0 comments

Why the Harness Matters More Than the Model [video]

https://www.youtube.com/watch?v=n9xKblqyQ28
1•wslh•15m ago•0 comments

Color Horse: The automatic color scheme generator

https://color.horse/
1•passive•15m ago•1 comments

Apple and Atari Connections

https://www.goto10retro.com/p/apple-and-atari-connections
2•ibobev•15m ago•0 comments

Show HN: EndFrame – Demos, launch videos, shorts from the AI plan you pay for

https://endframe.ai/
3•endframe•16m ago•0 comments

Two cats, two dogs, four vendors, and the model the AI couldn't find

https://victoriametrics.com/blog/two-cats-two-dogs-four-vendors-and-the-model-ai-couldnt-find/ind...
2•valyala•16m ago•0 comments

ASML Gets TSMC and Samsung Excited about High-NA EUV

https://www.techzine.eu/news/devices/144122/asml-gets-tsmc-and-samsung-excited-about-high-na-euv/
2•pieterr•16m ago•0 comments

Trump's new gold-trimmed phones in historical perspective

https://www.electrospaces.net/2026/09/trumps-new-gold-trimmed-phones-in.html
2•Luc•16m ago•0 comments

Hospital-Level Changes in Obstetric Services Availability, 2010-2024

https://rhrc.umn.edu/publication/annual-overview-of-hospital-level-changes-in-obstetric-services-...
2•toomuchtodo•16m ago•1 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.