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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•8s ago•0 comments

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

https://github.com/Anipaleja/nginx-defender
1•anipaleja•26s ago•0 comments

The Super Sharp Blade

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

Smart Homes Are Terrible

https://www.theatlantic.com/ideas/2026/02/smart-homes-technology/685867/
1•tusslewake•3m ago•0 comments

What I haven't figured out

https://macwright.com/2026/01/29/what-i-havent-figured-out
1•stevekrouse•4m 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•4m ago•0 comments

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

https://twitter.com/b1rdmania/status/2020155122181869666
2•birdmania•4m ago•1 comments

First Proof

https://arxiv.org/abs/2602.05192
2•samasblack•6m 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•7m ago•0 comments

Kagi Translate

https://translate.kagi.com
2•microflash•8m 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•9m ago•0 comments

Tactical tornado is the new default

https://olano.dev/blog/tactical-tornado/
1•facundo_olano•11m 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•11m 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•11m ago•0 comments

Google staff call for firm to cut ties with ICE

https://www.bbc.com/news/articles/cvgjg98vmzjo
30•tartoran•12m ago•2 comments

Dependency Resolution Methods

https://nesbitt.io/2026/02/06/dependency-resolution-methods.html
1•zdw•12m 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•12m ago•0 comments

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

https://www.iplotcsv.com/demo
1•maxmoq•13m 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•14m ago•0 comments

List of unproven and disproven cancer treatments

https://en.wikipedia.org/wiki/List_of_unproven_and_disproven_cancer_treatments
1•brightbeige•14m ago•0 comments

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

https://github.com/debugmeplease/debug-ME
1•debugmeplease•15m ago•1 comments

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

1•gogo61•18m ago•1 comments

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

https://paperinvest.io/arena
1•andrenorman•19m ago•0 comments

TOSTracker – The AI Training Asymmetry

https://tostracker.app/analysis/ai-training
1•tldrthelaw•23m ago•0 comments

The Devil Inside GitHub

https://blog.melashri.net/micro/github-devil/
2•elashri•23m ago•0 comments

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

https://github.com/ricardomoratomateos/distill
1•ricardomorato•23m 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•24m 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•25m ago•0 comments

Introduce the Vouch/Denouncement Contribution Model by Mitchellh

https://github.com/ghostty-org/ghostty/pull/10559
1•samtrack2019•26m ago•0 comments

Software Factories and the Agentic Moment

https://factory.strongdm.ai/
1•mellosouls•26m ago•1 comments
Open in hackernews

Anyone melding GPT-level intelligence with physical world?

2•iamnnk•5mo ago
The current state of LLMs (ChatGPT, Gemini) give the impression of having 'solved digital experience' completely. They are self contained to the extent that the 2023 technique of building wrappers on top of them to customise experiences seems redundant.

I intuitively sense scope for a meld of such intelligence with the physical world.

Are there startups that are building anything cool in this space?

Comments

ai_critic•5mo ago
What on earth ever gave you that impression?
gtirloni•5mo ago
That's an interesting question but the "AI wrappers" aren't going away because the LLMs 1) aren't totally deterministic and 2) feeding them the correct prompts and context is still very valuable. In other words, one-shotting doesn't work for every use case (which is essentially what your saying when you say they are "self-contained", right? Unfortunately, they aren't/can't be).

Regarding the physical world, that's a deeper question. You have people that say LLM's "understand", that they are "intelligent" and that this is an "emergent behavior" of all their weights. You also have people that say they are nothing more than a stochastic parrot or auto-complete on steroids.

I'm in neither camp but let's do a thought exercise. Multi-modal LLM's are training on text, video, and sound. They can know what a chair looks like, what sound it make if you drag it over a wooden floor, and what it would look like when you do that (from this mysterious PoV somewhere). Now take that "knowledge" and ask it to give you 3D coordinates to move a chair right now in the room you're standing in: it simply can't. It's lacking a lot of information about the actual measurements of the room, its own movement capabilities (or those of the human to carry out the task), etc.

There are AI that can do this, but they aren't good for text. We have self-driving cars and factory robots doing things constrained to those domains.

If you say "meld" as in "let's combine a bunch of different AI technologies together with each one doing what it does best", I'm sure people are working on this already. But LLM's are but a small part of solving that problem.

EDIT: if you still can, please add "Ask HN: " to your title here.

iamnnk•5mo ago
That's insightful.

Yes, I had moving-the-chair-in-physical-space class of capabilities in mind: robots guided by multimodal intelligence, cars 'surprising me' on a day I'm idle, etc. The challenge here may be in what can be achieved at the edge, the feedback control system for correction of successive prompts.