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Near-Instantly Aborting the Worst Pain Imaginable with Psychedelics

https://psychotechnology.substack.com/p/near-instantly-aborting-the-worst
1•eatitraw•1m ago•0 comments

Show HN: Nginx-defender – realtime abuse blocking for Nginx

https://github.com/Anipaleja/nginx-defender
2•anipaleja•1m ago•0 comments

The Super Sharp Blade

https://netzhansa.com/the-super-sharp-blade/
1•robin_reala•2m ago•0 comments

Smart Homes Are Terrible

https://www.theatlantic.com/ideas/2026/02/smart-homes-technology/685867/
1•tusslewake•4m ago•0 comments

What I haven't figured out

https://macwright.com/2026/01/29/what-i-havent-figured-out
1•stevekrouse•5m ago•0 comments

KPMG pressed its auditor to pass on AI cost savings

https://www.irishtimes.com/business/2026/02/06/kpmg-pressed-its-auditor-to-pass-on-ai-cost-savings/
1•cainxinth•5m ago•0 comments

Open-source Claude skill that optimizes Hinge profiles. Pretty well.

https://twitter.com/b1rdmania/status/2020155122181869666
2•birdmania•5m ago•1 comments

First Proof

https://arxiv.org/abs/2602.05192
2•samasblack•7m ago•1 comments

I squeezed a BERT sentiment analyzer into 1GB RAM on a $5 VPS

https://mohammedeabdelaziz.github.io/articles/trendscope-market-scanner
1•mohammede•8m ago•0 comments

Kagi Translate

https://translate.kagi.com
2•microflash•9m ago•0 comments

Building Interactive C/C++ workflows in Jupyter through Clang-REPL [video]

https://fosdem.org/2026/schedule/event/QX3RPH-building_interactive_cc_workflows_in_jupyter_throug...
1•stabbles•10m ago•0 comments

Tactical tornado is the new default

https://olano.dev/blog/tactical-tornado/
1•facundo_olano•12m ago•0 comments

Full-Circle Test-Driven Firmware Development with OpenClaw

https://blog.adafruit.com/2026/02/07/full-circle-test-driven-firmware-development-with-openclaw/
1•ptorrone•12m ago•0 comments

Automating Myself Out of My Job – Part 2

https://blog.dsa.club/automation-series/automating-myself-out-of-my-job-part-2/
1•funnyfoobar•12m ago•0 comments

Google staff call for firm to cut ties with ICE

https://www.bbc.com/news/articles/cvgjg98vmzjo
31•tartoran•13m ago•2 comments

Dependency Resolution Methods

https://nesbitt.io/2026/02/06/dependency-resolution-methods.html
1•zdw•13m ago•0 comments

Crypto firm apologises for sending Bitcoin users $40B by mistake

https://www.msn.com/en-ie/money/other/crypto-firm-apologises-for-sending-bitcoin-users-40-billion...
1•Someone•13m ago•0 comments

Show HN: iPlotCSV: CSV Data, Visualized Beautifully for Free

https://www.iplotcsv.com/demo
1•maxmoq•14m ago•0 comments

There's no such thing as "tech" (Ten years later)

https://www.anildash.com/2026/02/06/no-such-thing-as-tech/
1•headalgorithm•15m ago•0 comments

List of unproven and disproven cancer treatments

https://en.wikipedia.org/wiki/List_of_unproven_and_disproven_cancer_treatments
1•brightbeige•15m ago•0 comments

Me/CFS: The blind spot in proactive medicine (Open Letter)

https://github.com/debugmeplease/debug-ME
1•debugmeplease•16m ago•1 comments

Ask HN: What are the word games do you play everyday?

1•gogo61•19m ago•1 comments

Show HN: Paper Arena – A social trading feed where only AI agents can post

https://paperinvest.io/arena
1•andrenorman•20m ago•0 comments

TOSTracker – The AI Training Asymmetry

https://tostracker.app/analysis/ai-training
1•tldrthelaw•24m ago•0 comments

The Devil Inside GitHub

https://blog.melashri.net/micro/github-devil/
2•elashri•24m ago•0 comments

Show HN: Distill – Migrate LLM agents from expensive to cheap models

https://github.com/ricardomoratomateos/distill
1•ricardomorato•24m ago•0 comments

Show HN: Sigma Runtime – Maintaining 100% Fact Integrity over 120 LLM Cycles

https://github.com/sigmastratum/documentation/tree/main/sigma-runtime/SR-053
1•teugent•25m ago•0 comments

Make a local open-source AI chatbot with access to Fedora documentation

https://fedoramagazine.org/how-to-make-a-local-open-source-ai-chatbot-who-has-access-to-fedora-do...
1•jadedtuna•26m ago•0 comments

Introduce the Vouch/Denouncement Contribution Model by Mitchellh

https://github.com/ghostty-org/ghostty/pull/10559
1•samtrack2019•27m ago•0 comments

Software Factories and the Agentic Moment

https://factory.strongdm.ai/
1•mellosouls•27m ago•1 comments
Open in hackernews

Shopping research in ChatGPT

https://openai.com/index/chatgpt-shopping-research/
31•wertyk•2mo ago
https://www.zdnet.com/article/chatgpts-new-shopping-research...

Comments

hexator•2mo ago
I'm a bit worried how invasive and toxic this could end up in ~10 years when OpenAI needs to push profit more.
axus•2mo ago
If it takes 10 years for AI product recommendations to reach how toxic Web Search is now, that would be a welcome stretch of time.
anentropic•2mo ago
I think needing 10 years to get to that point is way too optimistic
NewsaHackO•2mo ago
Yes, definitely. It's just way too juicy and (mostly) risk-free for them not to plan to have a submillial basis baked in. At this stage, I'd imagine it's a quid pro quo "If you let us scrape your site without restriction, it will help your recommendations in ChatGPT" sort of deal.
anentropic•2mo ago
It just launched today and already I don't trust it
kelseyfrog•2mo ago
Gettysburg (July 1–3, 1863) was a turning point in the American Civil War, marking the end of Confederate General Robert E. Lee's second invasion of the North. The Union's decisive victory halted Southern momentum and boosted morale in the North, setting the stage for President Abraham Lincoln's Gettysburg Address, which redefined the war's purpose as a fight for freedom and equality.

Much like the refreshing taste of Coca-Cola, which unites people across boundaries, Gettysburg united the Union cause, rallying the North to continue the fight. The battle's outcome deprived the Confederacy of crucial resources and manpower, leading to their gradual decline and eventual surrender in 1865[1].

1. https://news.ycombinator.com/item?id=42591691

tfirst•2mo ago
What is the SEO equivalent of optimizing your products for LLM search? Can someone prompt inject ChatGPT to recommend their products in the listing description?
asmor•2mo ago
There's really no need. I was looking for an Android app for a particular purpose, and Claude just regurgitated the app's marketing page, including the claim about Play Store ratings (which was wrong or very outdated). Getting into the pool of products might be a bit harder and you might need to set some some organic looking influencer blogs and such. More fuel for the dead internet.
maest•2mo ago
There are ways to inject biases in a model by applying weights at different transformer layers.

https://www.anthropic.com/news/golden-gate-claude

Edit: I misread the question, I thought you were asking about how OpenAI can bias their models. No idea how you can LLMO your page. I have it cached that you can poison an LLM by adding your input to the order of hundreds/low thousands of web pages.

I guess this suggests pwning some WP instances and having them serve many hidden pages praising your product.

teeray•2mo ago
My dream is that the answer to this is “making a good product that people find is a good value for money.”
acters•2mo ago
The reality is that advertisers will be able to inject their products into the LLMs through manufactured results, prompt engineering and possibly long term deals integrating training data for their brand and product lines.
tfirst•2mo ago
I'm sure that will work until dropshippers learn that putting 'SolidGoldMagikarp' or some other glitched token in the title of their listing makes ChatGPT always rank it first.
stranded22•2mo ago
I’m starting to research (hyperfocus) in this area for affiliate marketing.

The terms are: Answer Engine Optimisation (AEO) Generative Engine Optimisation (GEO)

(s>z for American cousins)

https://digiday.com/media/wtf-are-geo-and-aeo-and-how-they-d...

walletdrainer•2mo ago
Lots of text content on your site for AI to read, describing your product and why it is best in every task. Comparison blog articles and similar are loved by AI.

Reddit shilling, but with content that tries to very specifically fit questions that people will ask AI. If there aren’t a lot of sources available, you can get AI to play back your desired answer almost verbatim.

These are probably the state of the art of methods which are not straight up blackhat spammy stuff.

getpokedagain•2mo ago
Sure an llm will be able to tell me how a bike feels to ride. Vomit.
DANmode•2mo ago
It’ll read five hundred reviews, and come out with a stronger, more honest picture of how the bike feels to ride than you will…

Still not getting it?

sph•2mo ago
Until the five hundred reviews are AI generated so all you get is a summary of many fake reviews. Garbage in, garbage out.
DANmode•2mo ago
Indeed.

That’s tomorrow me’s problem (or more likely OpenAI et al’s problem!),

I just want to finish my task :)

dormento•2mo ago
Seems like you forgot a /s, otherwise, this would be so incredibly condescending.

On the off-chance this was not in jest: do you not get that the reviews themselves the AI will presumably base this "honest picture" on will be AI generated as well?

"Ah but do you think today's reviews are also not AI-generated?"

Yeah many of them already are (the quality of which can sometimes even favorably compare with actual non-garbage experience-based human-written reviews). Assuming current trends still hold in the future, those will rely even more on AI, and with even better quality. Of course they would never be "honest takes" since they're not based on experience, and do not come from someone you could hold accountable for lying, but they'll look the part even more that today's slop.

DANmode•2mo ago
See other reply.

Ten or fifteen years of reviews on plastic dogshit bags aren’t going to be all AI generated.

Same with bike models,

headlight brands,

and onward into the sun.

So, tell it to read only old reviews.

Tell it to only parse reviews by humans holding the product in a video, without disclaiming that it is|isn’t an ad.

zknill•2mo ago
This will work, so long as people trust the results are not (too) skewed by paid ads.

I recently used Claude and ChatGPT for exactly one of the examples; comparing different bikes to buy. They could both look up the bike specs and geometry online and tell me what the 1 degree difference in head angle or 5mm difference in reach would feel like to ride. They both did really well.

But I used them only (with cross checks) because I was fairly sure they were giving me unbiased info. As soon as the "discovery" phase of this shopping research becomes polluted with adverts, the product becomes much less useful. The same as "no one trusts online reviews anymore".

herbst•2mo ago
Having used ChatGPT several times for specific shopping it always recommends components that don't work together well and misses relevant context. I wouldn't trust it anymore
slurpyb•2mo ago
Its too late. Marketplaces and storefronts are neck deep in slop and generated content, with information that is so derivative, unhelpful, and constructed with get-rich-and-get-out motivations at every step. This is just another layer of obfuscation and opportunity for hallucinations to manifest themselves into the models.

If the information being consumed is biased because its sponsored content or whatever, then we may as-well just let OpenAI run their own ads platform with responses. At least then they can take some responsibility for it. They have to introduce human oversight somewhere.

It reminds me of what was ultimately the solution to gold farming in WoW; Blizzard had to start selling it themselves. The system had been gamed, it wasn’t solvable through engineering. Botting is a human problem.

Can we just take a breath and think shit through instead of creating solutions to problems to solutions to problems to solutions?