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Claude Code sends 33k tokens before reading the prompt; OpenCode sends 7k

https://systima.ai/blog/claude-code-vs-opencode-token-overhead
194•systima•1h ago•104 comments

I love LLMs, I hate hype

https://geohot.github.io//blog/jekyll/update/2026/07/12/i-love-llms.html
121•therepanic•1h ago•52 comments

The shingles vaccine may reduce the risk of dementia

https://www.economist.com/leaders/2026/07/09/a-no-brainer-for-protecting-your-brain
150•saikatsg•4h ago•110 comments

Old and new apps, via modern coding agents

https://terrytao.wordpress.com/2026/07/11/old-and-new-apps-via-modern-coding-agents/
361•subset•9h ago•103 comments

Automation Without Understanding

https://arxiv.org/abs/2607.06377
52•root-parent•3h ago•27 comments

The One-Step Trap (In AI Research)

http://incompleteideas.net/IncIdeas/OneStepTrap.html
12•jxmorris12•1h ago•3 comments

Don't you mean extinct?

https://fabiensanglard.net/extinct/index.html
142•zdw•4h ago•70 comments

Can We Understand How Large Language Models Reason?

https://cacm.acm.org/news/can-we-understand-how-large-language-models-reason/
30•adunk•2h ago•23 comments

Why write code in 2026

https://softwaredoug.com/blog/2026/07/09/write-code
36•softwaredoug•2d ago•90 comments

LARP – Revenue infrastructure for serious founders

https://www.larp.website/
56•BerislavLopac•3h ago•8 comments

Against Usefulness

https://www.motivenotes.ai/p/against-usefulness
37•supo•2h ago•9 comments

How to Read More Books

https://scotto.me/blog/2026-07-12-how-to-read-more-books/
188•silcoon•4h ago•104 comments

I Learned to Read Again

https://substack.magazinenongrata.com/p/how-i-learned-to-read-again
12•georgex7•1h ago•0 comments

Why study Diophantine equations?

https://hidden-phenomena.com/articles/modular
48•mb1699•4h ago•15 comments

Migrating a production AI agent to GPT-5.6: 2.2x faster, 27% cheaper

https://ploy.ai/blog/migrating-a-production-ai-agent-to-gpt-5-6
16•brryant•2h ago•3 comments

Deir El-Medina Strikes

https://en.wikipedia.org/wiki/Deir_el-Medina_strikes
21•mooreds•5d ago•2 comments

Understanding the Odin Programming Language

https://odinbook.com/
128•AlexeyBrin•8h ago•67 comments

The power of collaboration: How we can reduce traffic congestion

https://research.google/blog/the-power-of-collaboration-how-we-can-reduce-traffic-congestion/
38•raahelb•4h ago•27 comments

Show HN: Shirei, cross-platform GUI framework in native Go

https://github.com/hasenj/go-shirei/
58•hsn915•3h ago•32 comments

Show HN: Nectar, a Rust-like React that compiles to WebAssembly

https://buildnectar.com
14•blakeburnette•6d ago•7 comments

Ghostel.el: Terminal emulator powered by libghostty

https://dakra.github.io/ghostel/
241•signa11•11h ago•40 comments

Neocities: Create your own free website

https://neocities.org/
8•Tomte•21m ago•0 comments

Vint Cerf, “father of the Internet”, is retiring

https://techcrunch.com/2026/06/30/the-father-of-the-internet-is-finally-retiring/
259•compiler-guy•2d ago•148 comments

What xAI's Grok build CLI sends to xAI: A wire-level analysis

https://gist.github.com/cereblab/dc9a40bc26120f4540e4e09b75ffb547
364•jhoho•19h ago•145 comments

Unauthenticated RCE in Motorola's MR2600 Router

https://mrbruh.com/motorola/
70•MrBruh•8h ago•22 comments

AI boosts research careers but narrow the span of ideas explored: study

https://spectrum.ieee.org/ai-science-research-flattens-discovery
123•zaikunzhang•6h ago•90 comments

Morphometrics: Introduction to the Analysis of Shape

https://www.geol.umd.edu/~tholtz/G331/lectures/331biomech.html
19•num42•1w ago•0 comments

Croc: Securely transfer files and folders between two computers

https://github.com/schollz/croc/
19•gregsadetsky•4h ago•4 comments

Death of the Status Update: Why 55% of Americans Stopped Posting on Social Media

https://ca.pcmag.com/social-media/16790/the-death-of-the-status-update-why-55-of-americans-stoppe...
76•thunderbong•9h ago•82 comments

Autoresearch, Claude and Constrained Optimization

https://www.elliotcsmith.com/autoresearch-claude-and-constrained-optimization/
24•gmays•5h ago•4 comments
Open in hackernews

Can We Understand How Large Language Models Reason?

https://cacm.acm.org/news/can-we-understand-how-large-language-models-reason/
30•adunk•2h ago

Comments

JackSlateur•1h ago
Do they ?
throw310822•1h ago
Of course they do, how else do you think they manage to implement new features in large codebases, or to prove new theorems? But you don't even have to assume they do because of the results- you can read their chain of thought.
3848499449•34m ago
they don't tho
ToValueFunfetti•26m ago
For the love of all that is sacred, please stop doing this. I'm begging you. The whole social media landscape is dying and you are creating a throwaway to participate in ruining this small corner. I assume this is not your first. And no one is convinced by this! The guidelines are there for your benefit as well. You achieve nothing but hastening the destruction of one of the last half-decent communities. Sorry for the melodrama.
chrisjj•34m ago
The Eliza effect strikes.
throw310822•10m ago
It's indeed so powerful that even my compiler and my unit tests fell victim of this delusion.
azakai•54m ago
The article answers this question, at least to the extent it can be answered, at this time.

We see some signs of reasoning, but also we understand little about how they work.

michaelchisari•40m ago
Do we see actual signs of reasoning or is it anthropomorphism? We have an innate tendency to do so as humans.
blooalien•35m ago
> Do we see signs of reasoning or is it anthropomorphism?

This is the part that so many folks just don't seem to understand (probably because it's been labeled as "thinking" or "reasoning" mode, and people assume that words have meaning). It's not reasoning or thought. It's spewing tokens pretending to "think", but it's actually just generating extra "context" to help the final answer be more coherent. The model isn't doing anything it doesn't already do. It's just doing more of it to improve the quality of the final answer displayed to the user.

dataflow•7m ago
[delayed]
Leonard_of_Q•6m ago
You're describing a process by which a 'thinking' entity uses cognition to refine a solution to a stated problem. That's a lot of words so usually we shorten this to 'reasoning'.

Do LLMs 'think'? I 'think' they do in a way. I don't really know how I think myself but I know I do and therefore I am (thanks, Descartes). I have a somewhat better grasp of the way LLMs 'think'. They do so sequentially, building a chain of descriptors which best fit the problem and the preceding descriptors. I suspect I do something not entirely dissimilar- i.e. I imagine 'worlds' which are like the current one changed in some way so they the problem I'm working on is reduced, then refine those until it is resolved - but in a massively parallel way.

arcanemachiner•44m ago
Yes, there is an LLM feature that we have anthropomorphized as "reasoning" or "thinking", where an LLM has a scratch space where it can dump tokens that help to improve the final output.
otabdeveloper4•27m ago
> that help to improve the final output

Do they actually help? Are you sure?

analog31•1h ago
Do LLMs have Qualia?
chrisjj•35m ago
Clickbait article title.

The article body does not presume they reason.

otabdeveloper4•28m ago
They don't reason.
CrzyLngPwd•28m ago
My toaster doesn't reason, and neither do the current clankers.
calf•26m ago
One plausible reason I thought of that we may not understand neural nets is that by their nature their power grows with ever-more complex connections and weights.

So it is like the opposite of logical systems, in that the very design of neural net architecture is a mess of parameter "spaghetti code" which renders the entire thing a metaphorical encrypted black box. The more powerful an AI/AGI the more this would be the case, and this is analogous a complexity curve.

And so any effort to make sense of such black box computation would be like trying to reverse entropy, analogous to trying to recover information lost in waste heat. And that could be one fundamental barrier to understanding both human and artificial brains alike, relative to their internal complexity.

(Just thinking aloud my handwavy pet theory recently, I am not an expert and could be totally mistaken on this)

warumdarum•25m ago
They dont. They have input that runs through a invisible stochastic canyon. As long as there is previous experience the stochastic canyon never ends. If there is none or isignificant one, or it runs out of tokkens, it hallucinates and the illusion falls apart. There is no reasoning, just the invisible grand canyon of all of human experience and knowledge. PS: try to get it to retell you a clichee movie or book and you can see life near the end, how the delta of all the same movies opens up into wildly different endings.

To advance further it would need the ability to abstract away the general situation shape and pattern recognize similar situations.

red75prime•6m ago
Stochastic gradient descent can be likened to traveling down a canyon. But inference? Hardly.
gfody•15m ago
there's a 2MP about the related paper: https://www.youtube.com/watch?v=l72ufA-4SzE
azakai•33m ago
Yes, we do see signs of actual reasoning, see the papers linked in the article. (There are many others too.)

Yes, we have a tendency to anthropomorphize, but (most) researchers are aware of this.

michaelchisari•24m ago
The papers linked in the article discuss the mechanical operations that simulate reasoning. Intelligence is data efficiency and I don't see a strong argument that reasoning can exist if it requires a world's worth of data.

That doesn't mean that simulated reasoning isn't useful, it's wildly useful. But a thing is not its simulation.