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HBO Max is making paying subscribers watch AI casino slop

https://adguard.com/en/blog/ai-casino-ads-hbo-streaming.html
2•DeepLogin•1m ago•0 comments

Ask HN: What belongs in production logs when customer data is involved?

1•Securelytixdev•3m ago•0 comments

EU sides with Big Tech over right to know about the impact of AI build-out

https://www.lighthousereports.com/investigation/data-centre-silence/
1•janandonly•4m ago•0 comments

Laserdisc Format

https://techdocs.exodusemulator.com/Console/PioneerLaserActive/Laserdisc.html
2•tosh•5m ago•0 comments

France sees US tech fines as piggy bank for EU spending, minister reveals

https://www.msn.com/en-us/news/other/france-sees-us-tech-fines-as-piggy-bank-for-eu-spending-mini...
1•nickslaughter02•6m ago•0 comments

Oído: Open-vocabulary speech recognition on a $5 ESP32-S3 (3.7% LibriSpeech WER)

https://github.com/lokutor-ai/oido
1•dani-lokutor•7m ago•0 comments

Daxis – a cross-platform desktop editor for Microsoft Fabric semantic models

https://github.com/AFetisa/daxis
1•afetisa•7m ago•0 comments

State of Devs 2026

https://2026.stateofdevs.com/en-US/
1•olalonde•8m ago•0 comments

Edge Cases

https://debarshibasak.github.io/readables/blogs/edgecases
1•debarshri•10m ago•0 comments

Show HN: A semantic fuzzer for Obsidian Sync... in spite of Claude

https://github.com/hmijail/ObsSyncBugHunt
1•hmijail•12m ago•0 comments

AI-Torture-Chamber

https://github.com/terrafying/ai-torture-chamber
1•rozumbrada•13m ago•1 comments

Codex GPT-6 Sol Performance Tracker

https://marginlab.ai/trackers/codex/
1•sscaryterry•13m ago•0 comments

Show HN: Gryphana – an IDE that runs in the browser

https://gryphana.com/
1•gryphana•15m ago•0 comments

ChatGPT Pro 20x now 10x for the same price

https://nerdschalk.com/chatgpt-pro-100-vs-200-vs-500-prices-usage-limits/
1•probst•15m ago•0 comments

OpenBSD's ports tree keeps GPL coreutils and rejects uutils (Rust rewrite)

https://www.mail-archive.com/ports@openbsd.org/msg143892.html
2•signa11•17m ago•0 comments

Local AI Models: The Catalyst for the Great Reset

https://breadcrumb.vc/local-ai-models-the-catalyst-for-the-great-reset-2b93ece0687e
1•sameer_singh17•19m ago•0 comments

Radio Waves Coming from an Alien Planet May Be a Cosmic First

https://www.nytimes.com/2026/09/29/science/space/exoplanet-magnetic-field.html
2•pseudolus•25m ago•0 comments

Mitos – personal helix fork with bunch new features

https://www.reddit.com/r/HelixEditor/comments/1wpt22a/mitos_personal_helix_fork_with_bunch_new_fe...
1•philonoist•26m ago•0 comments

Tiny System One decision models that run in the browser (29MB)

https://huggingface.co/spaces/hotchpotch/bekko-system-one-in-browser
1•hotchpotch•27m ago•1 comments

A personal opinion on the Zig programming language

https://macias.info/entry/202609300900_zig.md
3•mariomac•28m ago•1 comments

The whole animal: what I learned about debugging in a hospital

https://thecoder.io/blog/debugging-in-a-hospital/
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Spark-X2.5

https://github.com/XHToken/Spark-X2.5
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The Secret Monopoly Making Everything More Expensive

https://economicpopulist.substack.com/p/the-secret-monopoly-making-everything
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Three takeaways from Trump's 'Super Intelligence' summit

https://www.bbc.com/news/articles/cme30dz5vkzko
3•10xDev•36m ago•0 comments

Making AI an asset, not an expense

https://www.technologyreview.com/2026/09/29/1145186/making-ai-an-asset-not-an-expense/
2•joozio•36m ago•0 comments

Show HN: Privacy-First Natural Language to SQL, No LLMs, No Uploads

https://www.clientvirt.com/
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mrustc – Alternative Rust Compiler

https://github.com/thepowersgang/mrustc
1•peter_d_sherman•37m ago•1 comments

Leveraging Lessons Learned Developing Internet Protocols

https://cacm.acm.org/opinion/leveraging-lessons-learned-developing-internet-protocols/
1•adunk•38m ago•0 comments

Practical ways to use ChatGPT Pro 500

https://vercel.com/i/chatgpt-pro-500-use-cases
1•flashbrew•39m ago•0 comments

Trump announces vague AI deal among tech CEOs for 'tremendous self-policing'

https://www.theguardian.com/us-news/2026/sep/29/trump-ai-deal-tech-ceos-superintelligence
3•10xDev•39m 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.