MurphyA/hacker-news huggingface dataset:
by enasterosophes | 2025-05-05 20:52:11+00:00
It's a good question. It's easy to assume they're talking about R^126 (where R is the reals) but digging a bit deeper I don't think it's true.

The Kervaire invariant is a property of an "n-dimensional manifold", so the paper is likely about 126-dimensional manifolds. That in turn has a formal definition, and although it's not my specialization, I think means it can be locally represented as an n-dimensional Euclidean space.

A simple example would be a circle, which I guess would be a 1-dimensional manifold, because every point on a circle has a tangent where the circle can be approximated by a line passing through the same point.

So they're saying that there are these surfaces which can be locally approximated by 126-dimensional Euclidean spaces. This in turn probably requires that the surface itself is embedded in some higher-dimensional space such as R^127.
by throwawaymaths | 2025-05-05 20:52:12+00:00
Not expected but reasonable, if there is coupling between the concepts of malicious code and malicious other activities, through some sort of generalized understanding/information-conceptual-compression in the "knowledge ensemble"

One experiment could be to repeat this across models of varying size and see if the bigger models (assuming trained on ~similar dataset) are more capable of conceptual compartmentalization
by Ericson2314 | 2025-05-05 20:52:37+00:00
See the other comments. The point is not a specific new interface, but a separation of concerns, and leveling the playing field.

I'll try to do an example. The kernel doesn't currently know about SQL. Instead, you e.g. connect to a socket, and start talking to postgres. Imagine if FS stuff was the same thing: you connect to a socket, and then issue various command to read and write files. Ignore perf for a moment, it works right?

Now, one counter-argument might be "hold up, what is this socket you need to connect to, isn't that part of a file system? Is there now an all-userspace inner filesystem, still kernel-supported 'meta filesystem'?" Well, the answer to that is maybe the Unix idea of making communication channels like pipes and (to a lesser extent) sockets, was a bad idea. Or rather, there may be nothing wrong with saying a directory can have a child which may be such a communication channel, but there is a problem with saying that every such communication channel should live inside some directory.
by airylizard | 2025-05-05 20:52:45+00:00
1. What TSCE is in one breath

Two deterministic forward-passes.

1. The model is asked to emit a hyperdimensional anchor (HDA) under high temperature. 2. The same model is then asked to answer while that anchor is prepended to the original prompt.

No retries, no human-readable scratch-pad, no fine-tune.

---

2. What a hyper-dimensional anchor is

Opaque token sequence that the network writes for itself.

Notation: • X = full system + user prompt • A = anchor tokens • Y = final answer

Phase 1 samples `A ~ pθ(A | X)` Phase 2 samples `Y ~ pθ(Y | X,A)`

Because A is now a latent variable observed at inference time:

`H(Y | X,A) ≤ H(Y | X)` (entropy can only go down) and, empirically, E\[H] drops ≈ 6× on GPT-3.5-turbo.

Think of it as the network manufacturing an internal coordinate frame, then constraining its second pass to that frame.

---

3. Why the anchor helps (intuition, not hype)

4 096-D embeddings can store far more semantic nuances than any single “chain-of-thought” token stream. The anchor is generated under the same system policy that will govern the answer, so policy constraints are rehearsed privately before the model speaks. Lower conditional entropy means fewer high-probability “wrong” beams, so a single low-temperature decode often suffices.

---

4. Numbers (mixed math + calendar + formatting pack)

GPT-3.5-turbo – accuracy 49 % → 79 % (N = 300). GPT-4.1 – em-dash violation 50 % → 6 % (N = 300). Llama-3 8 B – accuracy 69 % → 76 % with anchor alone, 85 % when anchor precedes chain-of-thought (N = 100). Token overhead: 1.3 – 1.9× (two calls). One Self-Refine loop already costs ≥ 3×.

Diagnostic plots (entropy bars, KL-per-position, cosine-distance violin) are in the repo if you like pictures → `figures/`.

---

5. Why this isn’t “just another prompt trick”

The anchor never appears in the user-visible text. Gains replicate on two vendor families (OpenAI GPT and open-weights Llama) and on both reasoning and policy-adherence tasks. Visible chain-of-thought actually loses accuracy on 8 B models unless the anchor comes first; the mechanism changes internal computation, not surface wording.

---

6. Try it yourself

pip install tsce python -m tsce_demo "Rewrite this sentence without any em-dashes — can you?"

Repo (MIT) with benchmark harness, plots, and raw JSONL in Title!

---

7. Questions I’d love feedback on

Optimal anchor length vs. model size (64 tokens seems enough for < 10 B). Behaviour on Mixtral, Phi-3, Claude, Gemini — please post numbers. Red-team attempts: can you poison the anchor in Phase 1 and make the answer leak?

---
by caseyy | 2025-05-05 20:53:30+00:00
> Just to get things right. The big AI LLM hype started end of 2022 with the launch of ChatGPT, DALL-E 2, ....

GPT-2 was released in 2019, GPT-3 in 2020. I'd say 2020 is significant because that's when people seriously considered the Turing test passed reliably for the first time. But for the sake of this argument, it hardly matters what date years back we choose. There's been enough time since then to see the plateau.

> Most people in society connect AI directly to ChatGPT and hence OpenAI.

I'd double-check that assumption. Many people I've spoken to take a moment to remember that "AI" stands for artificial intelligence. Outside of tongue-in-cheek jokes, OpenAI has about 50% market share in LLMs, but you can't forget that Samsung makes AI washing machines, let alone all the purely fraudulent uses of the "AI" label.

> And there has been a lot of progress in image generation, video generation, ...

These are entirely different architectures from LLM/chat though. But you're right that OpenAI does that, too. When I said that they don't stray much from chat, I was thinking more about AlexNet and the broad applications of ML in general. But you're right, OpenAI also did/does diffusion, GANs, transformer vision.

This doesn't change my views much on chat being "not seeing the forest for the trees" though. In the big picture, I think there aren't many hockey sticks/exponentials left in LLMs to discover. That is not true about other AI/ML.
by tmnvix | 2025-05-05 20:54:10+00:00
Very similar to my experience.

From time to time I follow a policy of 'no idle screen time'. Essentially this means if I am using a screen I must have a definite purpose in mind. It really cuts down on how much time I spend on my phone or computer in general, but ironically increases the amount of work I get done (I work almost exclusively on a computer).

Some benefits I noticed after a short while include feeling much calmer (low level feeling of anxiety largely absent), actually actively listening to music again (instead of just using it for background noise), reading books again (even renewed my library card after 10+ years), keeping a more organised home, eating better, getting more exercise, and organising more time to spend with friends and family.
by timeinput | 2025-05-05 20:54:15+00:00
I'm with you entirely, and that is how I interact with youtube.

My wife likes to cast youtube videos from her phone to the TV, so the experience is nearly the same to her on her phone as it is watching on TV. Maybe if she only used the PC interface she wouldn't mind, but she likes to search / scan / scroll youtube on her phone, and cast the bits she's going to actually watch.

She was very frustrated by having to find the video she wanted to watch on her phone on the PC using the some what finicky mouse touch pad to get the cursor to open the web browser, navigate to youtube, enter the title in the search box (possibly) scroll to find the video, and then a couple more steps getting it playing full screen.

I'm happy we have options to block ads that aren't uBlock Origin in firefox, even though that works great, and better than other options.
by debrisapron | 2025-05-05 20:56:17+00:00
I was a bit surprised by this article as it actually contradicts the account I always heard, which was their main vocal effect was a Roland VP-9000. If you listen to e.g. Harder Faster the effect is somewhere in between a vocoder & autotune, so I assumed that was the VP-9000. That said, this guy has clearly done his homework (pun intended) so I'm inclined to accept his version of events.
by gbuk2013 | 2025-05-05 20:56:21+00:00
> give them more approachable/further from revenue work for which seniors would be an overkill

My experience suggests there is no such thing. There is work that seniors might not want to do, but if you hired well then they will be professional enough to do it, if it really needs to be done. And it takes some experience to determine which “non-revenue generating” work (e.g. tech debt) actually needs to be done, to advocate doing it to the stakeholders and to actually do it well.

Juniors need a lot of supervision and that is not free. Which is not a reason not hire them in the first place, just that that it should be done mindfully.
by projektfu | 2025-05-05 20:56:28+00:00
The Apple Desktop Bus Mouse II was pretty bad, worse than these. It frequently got dirty and wasn't ergonomic.

The Sun optical mice managed to be both annoying and clever - they didn't get too dirty but the effect was often the same, skipping around when they should have been smooth.

I was a fan of the Logitech TrackMan marble. (I preferred the one with the thumb wheel).
by Muromec | 2025-05-05 20:57:17+00:00
>TM SGNL changes the trust required to, "do I also trust this 3rd party not to share the contents of any of my communications, possibly inadvertently due to poor security practices".

That's the same level of trust really. Signal provides a guarantee that message bearer (i.e. Signal) can't see the contents, but end users may do whatever.

You can't really assume that counterparty's device isn't rooted by their company or they are themselves required by law to provide written transcripts to the archive at the end of each day. In fact, it's publicly known and mandated by law to do so for your counterparty that happens to be US government official.

The people who assume that they are talking with one of the government officials and expect records not to be kept are probably doing (borderline) illegal, like talking treason and bribes.

No, this is not a "nothing to hide argument", because those people aren't sending dickpics in their private capacity.
by SirensOfTitan | 2025-05-05 20:57:19+00:00
It's a commodity technology and VCs are investing as if this were still a winner-takes-all play. It's obviously not, if there were any doubt about that, Deepseek's R1 release should have made it obvious.

> But it’s a shallow dismissal to make the unnuanced comparison, especially when we’re talking about a brand new technology - who knows what the cost optimization levers are. Who knows what the market will bear after a few more revs.

You're acting as-if OpenAI is still the only player in this space. OpenAI has plenty of competitors who can deliver similar models for cheaper. Gemini 2.5 is an excellent and affordable model and Google has a substantially better capacity to scale because of a multi-year investment in its TPUs.

Whatever first mover advantage OpenAI had has been quickly eliminated, they've lost a lot of their talent, and the chief hypothesis they used to attract the capital they've raised so far is utterly wrong. VCs would be mad to be continuing to pump money into OpenAI just to extend their runway -- at 5 Bln losses per year they need to actually consider cost, especially when their frontier releases are only marginal improvements over competitors.

... this is a bubble despite the promise of the technology and anyone paying attention can see it. For all of the dumb money employed in this space to make it out alive, we'll have to at least see a fairly strong form of AGI developed, and by that point the tech will be threatening the general economic stability of the US consumer.
by eggy | 2025-05-05 20:57:28+00:00
You're right: Shen's mathematical underpinnings (sequent calculus, dependent type theory) can intimidate programmers without a formal logic background. I bought the "The Book of Shen" (TBOS) revision 1 and revision 3. Revision 4 is available on the website. It's a great book with some CS history, logic, and development of Shen from Qi as well as how everything works in Shen including the type system.

Shen uses a dependently typed Sequent-Calculus based Type System (SCTS). It uses type rules vs. type classes, and type checking is optional, you can turn it on or off. Haskell's type inference makes things a bit simpler, and is a battle-tested static type system with excellent type inference which lends itself better for functional programming and large-scale software engineering (for the moment). Shen's TC is more expressive, but requires more effort.

Aditya Siram has some old but goody YT videos on Shen.
by JumpCrisscross | 2025-05-05 20:57:35+00:00
> AGI can't really be a winner take all market. The 'reward' for general intelligence is infinite as a monopoly and it accelerates productivity

The first-mover advantages of an AGI that can improve itself are theoretically unsurmountable.

But OpenAI doesn't have a path to AGI any more than anyone else. (It's increasingly clear LLMs alone don't make the cut.) And the market for LLMs, non-general AI, is very much not winner takes all. In this announcement, OpenAI is basically acknowledging that it's not getting to self-improving AGI.
by dimal | 2025-05-05 20:57:56+00:00
I wish we called hallucinations what they really are: bullshit. LLMs don’t perceive, so they can’t hallucinate. When a person bullshits, they’re not hallucinating or lying, they’re simply unconcerned with truth. They’re more interested in telling a good, coherent narrative, even if it’s not true.

I think this need to bullshit is probably inherent in LLMs. It’s essentially what they are built to do: take a text input and transform it into a coherent text output. Truth is irrelevant. The surprising thing is that they can ever get the right answer at all, not that they bullshit so much.
by quesera | 2025-05-05 20:58:08+00:00
I won't go too far out on this limb, because I kind of agree with you... but to be fair -- 1980s-1990s nanotech did not attract this level of investment, nor was it visible to ordinary people, nor was it useful to anyone except researchers and grant writers.

It seems like nanotech is all around us now, but the term "nanotech" has been redefined to mean something different (larger scale, less amazing) from Drexler's molecular assemblers.
Show HN: X-Terminate, a Chrome extension to remove politics from your X feed
by ChadNauseam | 2025-05-05 20:58:18+00:00
Hi HN, I made a chrome extension that removes all politics from Twitter. The source code and installation instructions are here: https://github.com/wafer-inc/x-terminate

A description of how it works technically is here: https://chadnauseam.com/coding/random/x-terminate. Indeed, I mostly made the extension as a demo for the underlying tech: Rust libraries for data labelling and decision tree inference.

All libraries involved are open-source, and there are instructions for how can make your own filter (e.g. if you want to remove all Twitter posts involving Rust or AI).
by zaggynl | 2025-05-05 20:58:36+00:00
Neat! I'm already using openwebui/ollama with a 7900 xtx but the STT and TTS parts don't seem to work with it yet:

2025-05-05 20:53:15,808] [WARNING] [real_accelerator.py:194:get_accelerator] Setting accelerator to CPU. If you have GPU or other accelerator, we were unable to detect it.

Error loading model for checkpoint ./models/Lasinya: This op had not been implemented on CPU backend.
by michaelt | 2025-05-05 20:58:45+00:00
The explanation seemed pretty obvious to me: They set up a nonprofit to deliver an AI that was Open.

Then things went unexpectedly well, people were valuing them at billions of dollars, and they suddenly decided they weren't open any more. Suddenly they were all about Altman's Interests Safety (AI Safety for short).

The board tried to fulfil its obligation to get the nonprofit to do the things in its charter, and they were unsuccessful.
by smileysteve | 2025-05-05 20:59:23+00:00
Distractions aren't new; but they are more 24/7

24 hour "news" is a great example; we leave it on in the background, as Radio or TV, but we're not listening to gain information, we're listening to be entertained - amygdala activated.

With AM radio and broadcast TV, low efforts were mostly limited to 2 hour segments from the 80s-90s; then in the late 90s, cable tv became standard, then in the 2000s the internet (chats, reddit, hacker news), and then the smartphone...
by JumpCrisscross | 2025-05-05 20:59:28+00:00
> It's not a redefinition, it's a refinement

It's really not. The Space Shuttle isn't an emerging interstellar spacecraft, it's just a spacecraft. Throwing emerging in front of a qualifier to dilute it is just bullshit.

> By the same reasoning, so is a person. They are just auto completing words when they speak.

We have no evidence of this. There is a common trope across cultures and history of characterising human intelligence in terms of the era's cutting-edge technology. We did it with steam engines [1]. We did it with computers [2]. We're now doing it with large language models.

[1] http://metaphors.iath.virginia.edu/metaphors/24583

[2] https://www.frontiersin.org/journals/ecology-and-evolution/a...
by hermitcrab | 2025-05-05 20:59:32+00:00
>The license entitles you to receive lifetime updates for the major version.

Where does it say that?

That is common and it is the model I use for my own software. But that isn't what I understood from their website.

Home page: "Pay Once, Use Forever. We hate needless subscriptions as much as you do. TextQuery comes with a perpetual license with free updates."

Pricing page: "Perpetual license Lifetime updates"

Which strongly implies every update is free, forever.
by johanyc | 2025-05-05 21:00:00+00:00
Verbatim is not the point. “Transformative” is. You added nothing to the work when you film a movie at the theater. Google Books (Authors Guild v. Google, 2015) literally shows you photocopies of the pages but is considered transformative and fair use because they offer an easily searchable digital database (and also not harming the book selling market).
by llm_nerd | 2025-05-05 21:01:00+00:00
And indeed, Howard "Barking Carnival Huckster" Nutlick went on Fox News to attack Canada having a film industry. It is exactly what I said.

One of the most amazing things about the Idiocracy administration in place in the US is this belief that everything is the domain of Americans, and if any other nation is doing it, clearly they're stealing it. Canada had an automotive industry as long as the US did. We used to have the AutoPact before NAFTA, and we need to bring it back. Canada has a robust film industry on its own.

So when Howard Nutlick does his embarrassing "why does Canada make our films" act, there is a point there -- zero US media should be allowed into Canada. None. All IP rights on US products should be abolished. All patents and other.
by christiangenco | 2025-05-05 21:01:22+00:00
I've had the same sort of difficulty with phrases like "most" or "almost all" or "hardly any"—I crave for these to map to unambiguous numbers like the probability yardstick referenced in this article.

I spun up a quick survey[1] that I sent out to friends and family to try to get some numbers on these sorts of phrases. Results so far are inconclusive.

1. https://www.vaguequantifiers.com/
by jjulius | 2025-05-05 21:03:11+00:00
Totally! But then you've got to make sure all notifications are turned off from every app that might hit you up - not just silenced, but so that they don't even appear over top of the book. And then, of course, there's the temptation to swipe over to a different app that's right there.

A book, however, is just a book.
by nobody9999 | 2025-05-05 21:03:16+00:00
>Don't turn it off in your browser. If you have control of that setting just install an ad blocker. The point of DNS block lists is to get rid of ads on phones, TVs, and other non configurable things.

Yes, and...It's not just to block ads. It's also to block various trackers and unwanted/surreptitious "telemetry" and "updates" to those devices you can't control/configure.
by lukan | 2025-05-05 21:04:17+00:00
[You can click the timestamp to reply directly to any comment]

And there are still native tribes doing hunting and warfare with bows, that were and are studied. And some reenactment freaks are in a way better shape than their ancestors ever were, due to heavy training and better food.

Nobody is shooting in the air with an arrow to distract like you would a snowball. You shoot straight.
by magicalist | 2025-05-05 21:04:34+00:00
> This is really one of the hugest divides I've seen in the discourse about this: anti-LLM people saying very obviously untrue things, which is uh, kind of hilarious in a meta way.

> https://bsky.app/profile/caseynewton.bsky.social/post/3lo4td... is an instance of this from a few days ago.

Not sure why this is so surprising? ChatGPT search was only released in November last year, was a different mode, and it sucked. Search in o3 and o4-mini came out like three weeks ago. Otherwise you were using completely different products from Perplexity or Kagi, which aren't widespread yet.

Casey Newton even half acknowledges that timing ("But it has had integrated web search since last year"...even while in the next comment criticising criticisms using the things "you half-remember from when ChatGPT launched in 2022").

If you give the original poster the benefit of the doubt, you can sort of see what they're saying, too. An LLM, on its own, is not a search engine and can not scan the web for information. The information encoded in them might be ok, but is not complete, and does not encompass the full body of the published human thought it was trained on. Trusting an offline LLM with an informational search is sometimes a really bad idea ("who are all the presidents that did X").

The fact that they're incorrect when they say that LLM's can't trigger search doesn't seem that "hilarious" to me, at least. The OP post maybe should have been less strident, but it also seems like a really bad idea to gatekeep anybody wanting to weigh in on something if their knowledge of product roadmaps is more than six months out of date (which I guarantee is all of us for at least some subject we are invested in).
by evelant | 2025-05-05 21:06:30+00:00
No I don’t. I just created an account for the first time. I just wanted to point out augment since nobody had mentioned it and it seemed relevant. Roo code is another very good alternative that’s better than cursor but it requires a bit more manual work to get good results. I’ve spent a lot of time trying out all of these tools, augment is the best one IMO but was also the last one I discovered. I figured sharing it here might spare others the searching and frustration I went through with cursor/windsurf/roo/pear/trae and so on.