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Hot surfaces during Europe's heatwave 'seen' by Sentinel-3

https://www.esa.int/ESA_Multimedia/Images/2026/05/Hot_surfaces_during_Europe_s_heatwave_seen_by_S...
1•simonebrunozzi•1m ago•0 comments

The operating cost starts after the demo

https://twoheads.net/the-promise-is-unattended-work/
2•hellokfk•2m ago•0 comments

Deferring tech choices to thought leaders

https://twitter.com/bentlegen/status/2069876565110898920
1•coloneltcb•5m ago•0 comments

The running list: major tech layoffs in 2026 where employers cited AI

https://techcrunch.com/2026/06/22/the-running-list-major-tech-layoffs-in-2026-where-employers-cit...
2•momentmaker•5m ago•0 comments

Show HN: VibeKilled.rip – a live world map of devs who just hit the rate limit

https://vibekilled.rip/
1•thomasgeelens•5m ago•0 comments

The US Government has requested a slow staggered rollout of GPT-5.6

https://twitter.com/AndrewCurran_/status/2070244303923007831
1•I_am_tiberius•6m ago•1 comments

Bluekit phishing kit adopts browser-in-the-middle for login theft

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Nb: Command line note‑taking, bookmarking, archiving, and knowledge base

https://xwmx.github.io/nb/
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Surprising lessons from my research scientist job search

https://yongzx.github.io/blog/2026/06/24/job-search/
3•sebg•13m ago•0 comments

Pipestage

https://github.com/openlab-x/pipestage
2•firetesterlab•14m ago•0 comments

The 'papers, please' era of the internet will decimate your privacy

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Show HN: Open-source app for UniNow QR code check in

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1•bixilon•16m ago•0 comments

The State of the AI Economy

https://intelligence.exponentialview.co/
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Ask HN: Haven't posts about web front end frameworks completely stopped?

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Another reason to get attached to Surebeans

https://surebeans.net/blog/2026/06/getting-attached-to-surebeans/
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Show HN:Every Team Is Building the Same Cache

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All you need is PostgreSQL

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CPUs Are Back: The Datacenter CPU Landscape in 2026

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6•karakoram•25m ago•3 comments

US says PRC trying to discourage states, businesses from engaging with Taiwan

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5•ilamont•26m ago•0 comments

Why Is Europe So Ill-Equipped to Handle Heat Waves?

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1•karakoram•30m ago•2 comments

Show HN: A Claude skill that prunes your AI's memory file, one diff at a time

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After a Personal Health Crisis, He Built a $500M Cottage Cheese Empire

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1•mooreds•32m ago•0 comments

Hospitals in UK Declare Critical Incidents as Machines, IT Systems Fail in Heat

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5•karakoram•35m ago•0 comments

How the Heck Do Synthesizers Work? (An Interactive Exploration)

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2•mooreds•36m ago•0 comments

Kremlin demands explanation from Apple after Russian apps removed from App Store

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The Coming Divide: AI-Native or Left Behind

https://danielmiessler.com/blog/ai-native-divide
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Some learnings from temporal.io building SDKs for 8 languages

https://www.infoq.com/presentations/rust-polyglot-sdk/
1•devdoshi•37m 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.