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I replaced the front page with AI slop and honestly it's an improvement

https://slop-news.pages.dev/slop-news
1•keepamovin•1m ago•0 comments

Economists vs. Technologists on AI

https://ideasindevelopment.substack.com/p/economists-vs-technologists-on-ai
1•econlmics•3m ago•0 comments

Life at the Edge

https://asadk.com/p/edge
1•tosh•9m ago•0 comments

RISC-V Vector Primer

https://github.com/simplex-micro/riscv-vector-primer/blob/main/index.md
2•oxxoxoxooo•12m ago•1 comments

Show HN: Invoxo – Invoicing with automatic EU VAT for cross-border services

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A Tale of Two Standards, POSIX and Win32 (2005)

https://www.samba.org/samba/news/articles/low_point/tale_two_stds_os2.html
2•goranmoomin•17m ago•0 comments

Ask HN: Is the Downfall of SaaS Started?

3•throwaw12•18m ago•0 comments

Flirt: The Native Backend

https://blog.buenzli.dev/flirt-native-backend/
2•senekor•20m ago•0 comments

OpenAI's Latest Platform Targets Enterprise Customers

https://aibusiness.com/agentic-ai/openai-s-latest-platform-targets-enterprise-customers
1•myk-e•22m ago•0 comments

Goldman Sachs taps Anthropic's Claude to automate accounting, compliance roles

https://www.cnbc.com/2026/02/06/anthropic-goldman-sachs-ai-model-accounting.html
2•myk-e•25m ago•3 comments

Ai.com bought by Crypto.com founder for $70M in biggest-ever website name deal

https://www.ft.com/content/83488628-8dfd-4060-a7b0-71b1bb012785
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Big Tech's AI Push Is Costing More Than the Moon Landing

https://www.wsj.com/tech/ai/ai-spending-tech-companies-compared-02b90046
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The AI boom is causing shortages everywhere else

https://www.washingtonpost.com/technology/2026/02/07/ai-spending-economy-shortages/
2•1vuio0pswjnm7•29m ago•0 comments

Suno, AI Music, and the Bad Future [video]

https://www.youtube.com/watch?v=U8dcFhF0Dlk
1•askl•31m ago•2 comments

Ask HN: How are researchers using AlphaFold in 2026?

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Running the "Reflections on Trusting Trust" Compiler

https://spawn-queue.acm.org/doi/10.1145/3786614
1•devooops•39m ago•0 comments

Watermark API – $0.01/image, 10x cheaper than Cloudinary

https://api-production-caa8.up.railway.app/docs
1•lembergs•41m ago•1 comments

Now send your marketing campaigns directly from ChatGPT

https://www.mail-o-mail.com/
1•avallark•44m ago•1 comments

Queueing Theory v2: DORA metrics, queue-of-queues, chi-alpha-beta-sigma notation

https://github.com/joelparkerhenderson/queueing-theory
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GPT-5.3-Codex System Card [pdf]

https://cdn.openai.com/pdf/23eca107-a9b1-4d2c-b156-7deb4fbc697c/GPT-5-3-Codex-System-Card-02.pdf
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Atlas: Manage your database schema as code

https://github.com/ariga/atlas
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Geist Pixel

https://vercel.com/blog/introducing-geist-pixel
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Show HN: MCP to get latest dependency package and tool versions

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The better you get at something, the harder it becomes to do

https://seekingtrust.substack.com/p/improving-at-writing-made-me-almost
2•FinnLobsien•1h ago•0 comments

Show HN: WP Float – Archive WordPress blogs to free static hosting

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Show HN: I Hacked My Family's Meal Planning with an App

https://mealjar.app
1•melvinzammit•1h ago•0 comments

Sony BMG copy protection rootkit scandal

https://en.wikipedia.org/wiki/Sony_BMG_copy_protection_rootkit_scandal
2•basilikum•1h ago•0 comments

The Future of Systems

https://novlabs.ai/mission/
2•tekbog•1h 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.