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Scientists vote to end leap seconds, redefining how the world keeps time

https://www.scientificamerican.com/article/scientists-vote-to-end-leap-seconds-redefining-how-the...
1•0in•6m ago•0 comments

Self-Evolving Agent Harness

https://arxiv.org/abs/2610.18813
1•axis_official•6m ago•0 comments

Greece drafts law requiring data centers source 60% of power from renewables

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2•giuliomagnifico•11m ago•0 comments

Japan business manager visa holders leaving without reentry permits surge

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Instagram Reel and Video Downlaoder

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No AI. Build your own tree directory viewer in C by hand

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https://code.visualstudio.com/blogs/2026/10/15/modern-ui
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Earthquake alert falsely reports magnitude 9.9 and intensity 7 in Japan

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Dotnetup

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The Thinking Leakage in Reinforcement Learning for LLMs

https://arxiv.org/abs/2610.14270
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Sergey Brin says Google's AI models are reaching recursive self-improvement

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Researchers discover rogue Chinese AI agent fleet and talk with it

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Linus Torvalds on "don't use AI for X"

https://lore.kernel.org/lkml/CAHk-=whTs09_ozN+e09GU68N1wPP56MUzDjrg9rnKxQUa0A_4Q@mail.gmail.com/
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Local and Distributed Large LLM Inference with MLX and RDMA on Mac Studio

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3DCodeVerse

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CoreWeave Founders Shield Fortunes with $3.3B Stock Sales

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5•qlte•1h ago•0 comments

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Researchers Stranded an AI Agent on a Virtual Island. Things Got Weird

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3•em3rgent0rdr•1h 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.