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Toroidal Logit Bias – Reduce LLM hallucinations 40% with no fine-tuning

https://github.com/Paraxiom/topological-coherence
1•slye514•29s ago•1 comments

Top AI models fail at >96% of tasks

https://www.zdnet.com/article/ai-failed-test-on-remote-freelance-jobs/
1•codexon•40s ago•1 comments

The Science of the Perfect Second (2023)

https://harpers.org/archive/2023/04/the-science-of-the-perfect-second/
1•NaOH•1m ago•0 comments

Bob Beck (OpenBSD) on why vi should stay vi (2006)

https://marc.info/?l=openbsd-misc&m=115820462402673&w=2
2•birdculture•5m ago•0 comments

Show HN: Glimpsh – exploring gaze input inside the terminal

https://github.com/dchrty/glimpsh
1•dochrty•6m ago•0 comments

The Optima-l Situation: A deep dive into the classic humanist sans-serif

https://micahblachman.beehiiv.com/p/the-optima-l-situation
1•subdomain•6m ago•0 comments

Barn Owls Know When to Wait

https://blog.typeobject.com/posts/2026-barn-owls-know-when-to-wait/
1•fintler•6m ago•0 comments

Implementing TCP Echo Server in Rust [video]

https://www.youtube.com/watch?v=qjOBZ_Xzuio
1•sheerluck•6m ago•0 comments

LicGen – Offline License Generator (CLI and Web UI)

1•tejavvo•10m ago•0 comments

Service Degradation in West US Region

https://azure.status.microsoft/en-gb/status?gsid=5616bb85-f380-4a04-85ed-95674eec3d87&utm_source=...
2•_____k•10m ago•0 comments

The Janitor on Mars

https://www.newyorker.com/magazine/1998/10/26/the-janitor-on-mars
1•evo_9•12m ago•0 comments

Bringing Polars to .NET

https://github.com/ErrorLSC/Polars.NET
3•CurtHagenlocher•13m ago•0 comments

Adventures in Guix Packaging

https://nemin.hu/guix-packaging.html
1•todsacerdoti•15m ago•0 comments

Show HN: We had 20 Claude terminals open, so we built Orcha

1•buildingwdavid•15m ago•0 comments

Your Best Thinking Is Wasted on the Wrong Decisions

https://www.iankduncan.com/engineering/2026-02-07-your-best-thinking-is-wasted-on-the-wrong-decis...
1•iand675•15m ago•0 comments

Warcraftcn/UI – UI component library inspired by classic Warcraft III aesthetics

https://www.warcraftcn.com/
1•vyrotek•16m ago•0 comments

Trump Vodka Becomes Available for Pre-Orders

https://www.forbes.com/sites/kirkogunrinde/2025/12/01/trump-vodka-becomes-available-for-pre-order...
1•stopbulying•17m ago•0 comments

Velocity of Money

https://en.wikipedia.org/wiki/Velocity_of_money
1•gurjeet•20m ago•0 comments

Stop building automations. Start running your business

https://www.fluxtopus.com/automate-your-business
1•valboa•24m ago•1 comments

You can't QA your way to the frontier

https://www.scorecard.io/blog/you-cant-qa-your-way-to-the-frontier
1•gk1•25m ago•0 comments

Show HN: PalettePoint – AI color palette generator from text or images

https://palettepoint.com
1•latentio•26m ago•0 comments

Robust and Interactable World Models in Computer Vision [video]

https://www.youtube.com/watch?v=9B4kkaGOozA
2•Anon84•30m ago•0 comments

Nestlé couldn't crack Japan's coffee market.Then they hired a child psychologist

https://twitter.com/BigBrainMkting/status/2019792335509541220
1•rmason•31m ago•1 comments

Notes for February 2-7

https://taoofmac.com/space/notes/2026/02/07/2000
2•rcarmo•33m ago•0 comments

Study confirms experience beats youthful enthusiasm

https://www.theregister.com/2026/02/07/boomers_vs_zoomers_workplace/
2•Willingham•40m ago•0 comments

The Big Hunger by Walter J Miller, Jr. (1952)

https://lauriepenny.substack.com/p/the-big-hunger
2•shervinafshar•41m ago•0 comments

The Genus Amanita

https://www.mushroomexpert.com/amanita.html
1•rolph•46m ago•0 comments

We have broken SHA-1 in practice

https://shattered.io/
10•mooreds•46m ago•4 comments

Ask HN: Was my first management job bad, or is this what management is like?

1•Buttons840•47m ago•0 comments

Ask HN: How to Reduce Time Spent Crimping?

2•pinkmuffinere•49m ago•1 comments
Open in hackernews

Paper shows scientific foundation model learns general abstract physics

https://arxiv.org/abs/2511.20798
2•iRoygbiv•2mo ago

Comments

iRoygbiv•2mo ago
PolymathicAl released a scientific foundation model (called Walrus) the other day.

Today they posted a follow up paper examining how the model represents the physical world.

Basically they look at the model's "thoughts" and show that it understands very abstract physical ideas (like speed, or diffusion).

To be clear Walrus itself isn’t yet a fully general purpose “physics AI” because it only works with continuum (fluid-like) data, but it feels like a big stepping stone because it is able to handle anything that is vaguely fluid like (e.g. plasma, gasses, acoustics, turbulence, astrophysics etc). It appears the model is looking at all these different systems and finding general laws/principles that underly everything.