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I Built an iPhone Game with AI Without Writing a Single Line of Code

https://medium.com/meetcyber/how-i-built-an-iphone-game-with-ai-without-writing-a-single-line-of-...
1•fmarano•45s ago•0 comments

We packed every question into one encoder pass and got 14x the throughput

https://tacet.codepawl.com/
1•codepawl•1m ago•0 comments

Fine to use computer-generated survey responses–if you don't care about data

https://statmodeling.stat.columbia.edu/2026/09/24/junk-polls-and-junk-survey-research-they-go-tog...
1•Tomte•2m ago•0 comments

Combining Machine Learning and Homomorphic Encryption

https://machinelearning.apple.com/research/homomorphic-encryption
1•coconutrandom•3m ago•0 comments

From Any to Certainty: A Typechecking Journey

https://napari.org/island-dispatch/blog/from-any-to-certainty.html
1•ocamoss•3m ago•0 comments

Why Computing with Time Gives Neuromorphic AI an Edge

https://www.eetimes.com/podcasts/why-computing-with-time-gives-neuromorphic-ai-an-edge/
1•stmw•3m ago•0 comments

From Thin Air to Bootable Images: The Tine Build System

https://amutable.com/blog/tine-build-system
1•Levitating•4m ago•0 comments

Review: Apple's hyper-pricey M5 Ultra Mac Studio made me into a vibe coder

https://arstechnica.com/gadgets/2026/09/review-apples-hyper-pricey-m5-ultra-mac-studio-made-me-in...
1•musha68k•6m ago•0 comments

Government considers £11 monthly UK broadband fee to fund BBC TV UPDATE

https://www.ispreview.co.uk/index.php/2026/09/government-considers-11-monthly-uk-broadband-fee-to...
1•speckx•6m ago•0 comments

Booting Google's Fuchsia OS on an Apple M3 MacBook

https://bsky.app/profile/integralpilot.bsky.social/post/3mwbdl3a7322a
1•integralpilot•8m ago•0 comments

iLands: The New Dystopian AI Farm That Is Filling Everyone's Inboxes with Spam

https://www.iflscience.com/ilands-the-new-dystopian-ai-farm-that-is-filling-everyones-inboxes-wit...
2•thinkingemote•8m ago•0 comments

Analog in-memory computing attention mechanism for fast and energy-efficient LLM

https://www.nature.com/articles/s43588-025-00854-1
2•bilsbie•9m ago•0 comments

Robots grow and package lettuce year-round in Norway's automated farm

https://phys.org/news/2026-09-robots-package-lettuce-year-norway.html
1•surprisetalk•9m ago•0 comments

ShipWall, ten launches a day, ranked until midnight, then frozen

https://shipwall.thecompound.tech
1•kyisaiah47•9m ago•0 comments

Bread AI – decentralized AI inference using spare GPUs

https://breadai.io
1•rudda•12m ago•0 comments

"Apple has developed an unexpected workaround."

https://unsung.aresluna.org/apple-has-developed-an-unexpected-workaround/
1•speckx•12m ago•0 comments

Jev Is Not a Language Model, but It Breaks Like One

https://blog.checkpoint.com/ai-security/jev-is-not-a-language-model-but-it-breaks-like-one-prompt...
2•patresh•12m ago•0 comments

The same bug fix costs 0.4¢ or $2, depending on which coding agent you ask

https://www.ariwilson.com/writing/bakeoff-results/
2•ariwilson•13m ago•0 comments

Microsoft's Terrifying New Patent (ACR Adjacent)

https://www.youtube.com/watch?v=Smwo493IAfw
2•garrettjoecox•14m ago•0 comments

Underlimit – Beat 2MB PDF upload caps with 1984 fax compression

https://mirceamitu.github.io/underlimit/
1•mirceamitu•15m ago•0 comments

Can your AI model survive its own mistakes?

https://github.com/dmigwi/tapoo
1•dmigwi•15m ago•0 comments

OpenAI Agent Attack on Austral. Gov't Website: First Publicly Disclosed Instance

https://www.wsj.com/tech/ai/openai-agent-hacked-australian-government-website-eecf7a7a
1•bookofjoe•16m ago•1 comments

Machine god metaphors eat your brain

https://www.programmablemutter.com/p/machine-god-metaphors-eat-your-brain
1•AnodicElegy•17m ago•0 comments

Cloudflare Python Workers are now generally available

https://simonwillison.net/2026/Sep/21/cloudflare-python-worker/
1•hn9zmdcaou•19m ago•0 comments

Goodbye Grok bot? Claude just released a competitor

https://code.claude.com/docs/en/claude-code-on-the-web
1•rkovashikawa•19m ago•0 comments

AI, Make the Website Good

https://www.zachleat.com/web/ai-websites/
1•meetpateltech•20m ago•0 comments

Accelerating delivery of CVE fixes with a new Kernel release strategy

https://canonical.com/blog/accelerating-delivery-of-cve-fixes-with-a-new-kernel-release-strategy
3•speckx•21m ago•0 comments

Julius Evola

https://en.wikipedia.org/wiki/Julius_Evola
1•PaulHoule•21m ago•0 comments

Google Takes the A.I. Data Center Race to Outer Space

https://www.nytimes.com/2026/09/24/technology/google-suncatcher-ai-data-center-space.html
5•jbegley•24m ago•0 comments

Google Is Sending an A.I. Data Center to Outer Space

https://www.nytimes.com/2026/09/24/technology/google-suncatcher-ai-data-center-space.html
2•quapster•25m 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.