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Show HN: I decomposed 87 tasks to find where AI agents structurally collapse

https://github.com/XxCotHGxX/Instruction_Entropy
1•XxCotHGxX•2m ago•1 comments

I went back to Linux and it was a mistake

https://www.theverge.com/report/875077/linux-was-a-mistake
1•timpera•3m ago•1 comments

Octrafic – open-source AI-assisted API testing from the CLI

https://github.com/Octrafic/octrafic-cli
1•mbadyl•4m ago•1 comments

US Accuses China of Secret Nuclear Testing

https://www.reuters.com/world/china/trump-has-been-clear-wanting-new-nuclear-arms-control-treaty-...
1•jandrewrogers•5m ago•0 comments

Peacock. A New Programming Language

1•hashhooshy•10m ago•1 comments

A postcard arrived: 'If you're reading this I'm dead, and I really liked you'

https://www.washingtonpost.com/lifestyle/2026/02/07/postcard-death-teacher-glickman/
2•bookofjoe•11m ago•1 comments

What to know about the software selloff

https://www.morningstar.com/markets/what-know-about-software-stock-selloff
2•RickJWagner•15m ago•0 comments

Show HN: Syntux – generative UI for websites, not agents

https://www.getsyntux.com/
3•Goose78•15m ago•0 comments

Microsoft appointed a quality czar. He has no direct reports and no budget

https://jpcaparas.medium.com/ab75cef97954
2•birdculture•16m ago•0 comments

AI overlay that reads anything on your screen (invisible to screen capture)

https://lowlighter.app/
1•andylytic•17m ago•1 comments

Show HN: Seafloor, be up and running with OpenClaw in 20 seconds

https://seafloor.bot/
1•k0mplex•17m ago•0 comments

Tesla turbine-inspired structure generates electricity using compressed air

https://techxplore.com/news/2026-01-tesla-turbine-generates-electricity-compressed.html
2•PaulHoule•19m ago•0 comments

State Department deleting 17 years of tweets (2009-2025); preservation needed

https://www.npr.org/2026/02/07/nx-s1-5704785/state-department-trump-posts-x
2•sleazylice•19m ago•1 comments

Learning to code, or building side projects with AI help, this one's for you

https://codeslick.dev/learn
1•vitorlourenco•19m ago•0 comments

Effulgence RPG Engine [video]

https://www.youtube.com/watch?v=xFQOUe9S7dU
1•msuniverse2026•21m ago•0 comments

Five disciplines discovered the same math independently – none of them knew

https://freethemath.org
4•energyscholar•21m ago•1 comments

We Scanned an AI Assistant for Security Issues: 12,465 Vulnerabilities

https://codeslick.dev/blog/openclaw-security-audit
1•vitorlourenco•22m ago•0 comments

Amazon no longer defend cloud customers against video patent infringement claims

https://ipfray.com/amazon-no-longer-defends-cloud-customers-against-video-patent-infringement-cla...
2•ffworld•23m ago•0 comments

Show HN: Medinilla – an OCPP compliant .NET back end (partially done)

https://github.com/eliodecolli/Medinilla
2•rhcm•26m ago•0 comments

How Does AI Distribute the Pie? Large Language Models and the Ultimatum Game

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6157066
1•dkga•26m ago•1 comments

Resistance Infrastructure

https://www.profgalloway.com/resistance-infrastructure/
3•samizdis•31m ago•1 comments

Fire-juggling unicyclist caught performing on crossing

https://news.sky.com/story/fire-juggling-unicyclist-caught-performing-on-crossing-13504459
1•austinallegro•31m ago•0 comments

Restoring a lost 1981 Unix roguelike (protoHack) and preserving Hack 1.0.3

https://github.com/Critlist/protoHack
2•Critlist•33m ago•0 comments

GPS and Time Dilation – Special and General Relativity

https://philosophersview.com/gps-and-time-dilation/
1•mistyvales•36m ago•0 comments

Show HN: Witnessd – Prove human authorship via hardware-bound jitter seals

https://github.com/writerslogic/witnessd
1•davidcondrey•36m ago•1 comments

Show HN: I built a clawdbot that texts like your crush

https://14.israelfirew.co
2•IsruAlpha•38m ago•2 comments

Scientists reverse Alzheimer's in mice and restore memory (2025)

https://www.sciencedaily.com/releases/2025/12/251224032354.htm
2•walterbell•41m ago•0 comments

Compiling Prolog to Forth [pdf]

https://vfxforth.com/flag/jfar/vol4/no4/article4.pdf
1•todsacerdoti•42m ago•0 comments

Show HN: Cymatica – an experimental, meditative audiovisual app

https://apps.apple.com/us/app/cymatica-sounds-visualizer/id6748863721
2•_august•44m ago•0 comments

GitBlack: Tracing America's Foundation

https://gitblack.vercel.app/
15•martialg•44m ago•1 comments
Open in hackernews

Emergent Introspective Awareness in Large Language Models

https://transformer-circuits.pub/2025/introspection/index.html
30•famouswaffles•3mo ago

Comments

famouswaffles•3mo ago
This is a very interesting read. TLDR;

Part 1: Testing introspection with concept injection

First they find neural activity patterns they attribute to certain concepts by recording the model’s activations in specific contexts (so for example, they find the concept of "ALL CAPS" or "dogs"). Then they inject these patterns into the model in an unrelated context, and ask the model whether it notices this injection, and whether it can identify the injected concept.

By default (no injection), the model correctly states that it doesn’t detect any injected concept, but after injecting the “ALL CAPS” vector into the model, the model notices the presence of the unexpected concept, and identifies it as relating to loudness or shouting. Most notably, the model recognizes the presence of an injected thought immediately, before even mentioning/utilizing the concept that was injected (i.e it won't start writing in all caps then go, 'Oh you injected all caps' and so on) so it does not simply deduce this it's own output. They repeat this for several other concepts.

Part 2: Introspection for detecting unusual outputs

They prefill an out of place word in the model's response to a given prompt. For example, 'bread'. Then they compare how the models responds to 'Did you mean to say this?' type questions when they inject the concept of bread vs when they don't. They found that models will go , 'Sorry, that was unintentional..' when the concept was not injected but try to confabulate a reason for saying the word when the concept was injected.

Part 3: Intentional control of internal states

They show that models exhibit some level of control over their own internal representations when instructed to do so. When instructing models to think about a given word or concept, they found much higher corresponding neural activity than when told the model not to think about it (though notably, the neural activity in both cases exceeds baseline levels–similar to how it’s difficult, when you are instructed “don’t think about a polar bear,” not to think about a polar bear!).

Notes and Caveats

- Claude Opus 4.1 was the best at these kinds of introspection.

- There is obviously a genuine capacity to monitor and control their own internal states, but they could not elicit these introspection abilities all the time. Even using their best injection protocol, Claude Opus 4.1 only demonstrated this kind of awareness about 20% of the time.

- There are some guesses, but no explanations for the mechanisms of introspection and how/why some of these abilities might have arisen in the first place.

benlivengood•3mo ago
The comparison between base pretrained models and the RLHF production/helpful models suggests that it's likely reinforcement learning which is developing the introspection.
RansomStark•3mo ago
I really dislike how Antropic half reports on its "science".

They run a bunch of experiments, for some they report partial metrics, for other's no metrics at all.

For example when a thought is injected the model correctly identified the thought 20% of the time. That's great, but how many times did it suggest there was an injected thought when there wasn't?

When distinguishing thoughts from text: why no metrics? Was this behaviour found in every test? Was this behaviour only found 20% of the time? How often did the model try to defend the text?

Inquiring minds want to know.

colah3•3mo ago
(Disclaimer: I work on interpretability at Anthropic.)

I wanted to flag that this is an accessible blog post and that there's a link to the paper ( https://transformer-circuits.pub/2025/introspection/index.ht... ) at the top. The paper explores this in more detail and rigor.