skysight-inc/HackerNews huggingface dataset:
If you think about this generation of text/media AI as being a kind of generalized decrompressor for some input prompt, the output has more detail than the input but never more information.

So as any model becomes widespread, people will become increasingly sensitive to the sameness of easy, simple prompts.

So the graphic designer at the law firm may lose their job tomorrow, but the law firm is going to have to hire a AI Image Technician in a few years so that their stuff looks like somebody actually invested in it (which matters to the law firm’s brand image or they’d not have a graphic designer in the first place).

So yeah, the job market will shuffle around, but it’s unclear what that means in net number of jobs or what share of AI Image Technicians will literally have just been Graphic Designers five years earlier.
I’d be curious how much of this can be directly attributed to logging roads. Not the logging that they enable, but the actual path the roads allow water to take. I’ve seen mention of the fractal patterns of roads developed to log the amazon, and genuinely wonder, since roads have notoriously big effects in urban hydrology.
"Important (but not Urgent)" is most people's weak quadrant.

All those biggish things that you want to do some day, that you need to do some day, that might change your life... BUT right now (for looong values of "right now") there's something else to do.

This is where you want to break down hazy targets into multiple more-concrete steps, so that you can opportunistically make piecewise progress.
I was initially happy with Musk’s acquisition, both because watching a dumpster fire is entertaining and because he actually made it work a lot better for logged-out use, very soon after the purchase.

Changes in the last few weeks have flipped that around and made it terrible if you’re logged out. Friends (with accounts) have started sharing screenshots rather than links, because the links strip all context for a post if you visit them while logged out. Logged out search no longer works. Account pages have seemingly insane post ordering putting posts from months or years ago at the top, and newer posts often no-where. Whole site’s now entirely useless without an account.
I disagree. I focus on serving one client at a time, as well. Occasionally two, if one doesn't have enough work for me. I have a custom portal I built for tracking time/expenses, generating Stripe invoices, monitoring client budget, etc. Some clients want per-hour billing, some daily. Some want individual line-items (like a git commit, explaining exactly what I did with that time), and some don't care. If this project existed before I built that, I'd be using this project -- hands down.

Sadly, my portal already exists, and is deeply connected to Stripe and my way of doing business. So, I don't ever plan on doing what this person is doing. But I do highly suggest integrating it with Stripe Connect and make the project entirely free, and only charge a % of invoices total (like 1-5%). If it is free, people will use it. If they can send an invoice and automatically charge a client (assuming the client saved their billing information), that is money in the bank and you don't have to worry about collecting or them paying late ... that is worth it's weight in gold, as a contractor.
>But in an effort to keep it as cheap as possible, the decision was made to go with a design that, in theory, would give users a 50/50 chance of plugging it in correctly (you can up the odds by looking at the inside first, or identifying the logo).

I despise this "design decision." Literally bakes in the 50% of the time you plug it in the wrong orientation and lose seconds of your life. Who cares if the sands of time are moving more rapidly than asteroids? We can save money and make more of these badboys to fill the landfills with once they're obsolete. Hard to argue that logic that clearly won via market dynamics. But where are we now?
People have difficulty facing reality when it doesn't fit their world view, it is what it is
This is what strikes me more than the topic:

> The person below you has the advantage of jabbing at your legs

Weren't virtually all fighters in those times men?
I have definitely been frustrated by an hdmi port I couldn't see. I almost always have to gain visibility on the port to get the cable inserted correctly. If I happen to already know the orientation of the port on a device I can do it by feel, but I could also do this with the microusb-b to my old cell phone.
>> If an LLM was trained to always say "I don't know", that'd be a useless LLM, so they're trained to NOT say that, even when they don't actually know.

Do LLMs "know" that they don't know?

Real understanding includes acknowledging what you don't know.

Can the predictive text generation of LLMs recognize that its training set did not include data?
I was just going from the linked issue where I thought I read that Go’s engine supports incremental search. Maybe I misread?

While I have you, how close is the Rust incremental search support? It sounded like regex-automata might make it possible but hard to easily get a sense of high level progress from a GitHub issue.
By far one of the most fascinating things to do is look up up GPT-2, 3 threads and see predictions, extrapolations of future abilities. They're of course hilariously wrong but the best bit is that the vast majority of people seem to be making the exact same mistake.

"GPT-a has no real x so of course it can't do y" only for y to not be a problem in a future iteration.

It's like people just can't grasp that a predictor being unable to do x isn't an indictment on prediction. The predictor is just not good enough yet.

That GPT-2 could not predict coherent passages did not mean that you couldn't predict your way to coherency. GPT-2 was simply not a strong enough predictor.

That GPT-3 could not predict valid chess games did not mean that you couldn't predict your way to playing a chess game. GPT-3 was simply not a strong enough predictor.

No doubt people are still making this mistake with 4.
I'd love for one to take off.

You might be right that they wouldn't take off even if they would work really well.

But I'd like to think they could :)

With a good UI, a frictionless login, clear personal data separation and a sufficiently widespread browser extension platform available on mobile, this would be awesome...

Maybe Safari would be a good first target with their WebExtension support.

There is of course also the technical problem of dynamic rendering and unpredictable DOM structure.

And the whole problem of reaching a social media user base and providing valuable interaction tools to them.

Especially when considering ads, the main question is how to locate these DOM elements — for example, the filter lists shipped with uBlock origin do a great job here.

I'm wondering if maybe having more flexible locators available could help identify DOM subtrees by their content instead of a CSS selector.

Similar to the ones available in e2e testing frameworks, but maybe even more powerful things could be conceived, or matching snapshots etc...

Could certainly imagine this taking off, but imagination is not reality :)
Quanta and BigThink are such great sites, pumping out high quality science journalism.
It's possible to know where the humans are but be unable to destroy them with commonly available artillery payloads due to them being well dug in with overhead protection.

These could swarm in the back door.
ahem...you clearly didn't read the rider. it was brown M&Ms

"The rider's "Munchies" section was where the group made its candy-with-a-caveat request: "M&M's (WARNING: ABSOLUTELY NO BROWN ONES)." *

*https://www.thesmokinggun.com/documents/crime/van-halens-leg...
I see remarks like this a lot, and I don't know what to do with them.

Talking about "real understanding" without fleshing out what we mean by the phrase doesn't strike me as at all insightful in this context. In day-to-day use, the term is imprecise but usually easy enough to talk about, but I'd struggle to apply it to dogs, let alone to LLMs or AGIs or whatever.

You say that _of course_ they cannot self-correct because of this. If Deepmind's tests showed the opposite result, would you say that the system they were testing did have "real understanding"? It seems likely to me that future systems will demonstrate self-correction using Huang et al.'s methodology...will we think those systems are different in some way involving understanding?

> The LLM I was using gave me code that worked, but did not do what I wanted. I pointed this out, so I then got code that syntactically did what I wanted, but could never work. This went back and forth twice, before I gave up.

> The LLM was incapable of recognizing the falsity of its answers. It certainly wasn't capable of suggesting a different approach that would work (and yes, there was one, I found after a bit more research).

I really don't know what to do about these sorts of anecdotes. Often with slightly different random values or temperature or phrasing, the same LLM will give different results for the same problem. I've repeatedly seen people make much more narrow claims about what LLMs get wrong or what their biases are, where simply regenerating will give a dramatically different answer.

Your pain here sounds like something I see in humans all the time. If we trained a human harder never to ask follow-up questions, I imagine it would be even worse. There are clearly important differences between an LLM and a human being, but I don't think it's always easy to describe what they are in useful ways.
Depends what you consider vocal models 'more text'. Already we're seeing multi-modal AI have a correct answer when executing across image/text or voice/text interpretation.
OF is actually pretty dang conservative as far as adult websites go. They have a ton of restrictions about what text (!) is allowed to be posted.
That's not "A lookup table is faster than a native bit reversal instruction."; that's "There's no portable way to make the compiler emit a native bit reversal instruction, and a lookup table is (presumably) faster than a couple dozen instructions to do it manually (at least on most target architectures).".
I asked ChatGPT to explain fast exponentiation. It did 9 iterations until it came up with the right algorithm. Why would this not be considered self-correction?
Why is walking the salient technology that will enable this? Why not wheels, or treads, or flying?
Can it reason about a math problem that no human ever thought about and solve it ?
There's no such thing as a world model. People don't solve problems by creating world models.

That term was invented by 70s AI researchers, but remember that those people failed. Their research wasn't actually correct, so you shouldn't reuse it.
Was that on American DVDs? I heard it was dubbed over as "Pizza Hut" in foreign releases because we would know what that is.
China banned all our social networks, we ban their's, simple trade stuff works.
> For a lot of us, LLM behavior and thinking are so plainly and obviously dissimilar

But what's obvious to you is not obvious to everyone.

Even though you don't have to mathematically prove a goldfish doesn't walk for me to believe you, that's because we can both agree on a very good definition of walking. If it came down to it, I am sure we could sit down with pen an paper and some textbooks and agree upon a physical definition as robust as any. We're just skipping that step because it's been done before by others.

I am positive that we can't agree on a robust definition of thinking, because the definition of thinking is beyond human understanding.

We have to keep an open mind. I don't believe it's likely that any LLMs are experiencing anything we'd call thought, but without knowing how thought works, it would be foolish of me to say it's impossible. The problem in AI discussions is not the positions people are taking but the certainty with which they are taking them.
There's quite a lot of indication that the computation can distinguishing hallucinations. It just has no incentive to communicate this.

GPT-4 logits calibration pre RLHF - https://imgur.com/a/3gYel9r

Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback - https://arxiv.org/abs/2305.14975

Teaching Models to Express Their Uncertainty in Words - https://arxiv.org/abs/2205.14334

Language Models (Mostly) Know What They Know - https://arxiv.org/abs/2207.05221
Usb-c to usb-c extensions are currently explicitly prohibited by standard, both because of issues like this and ways that they defeat safety mechanisms with charging.
FYI news from September 5th (why the post OP?)
No. We know that LLMs make world models. (Often literally: https://twitter.com/wesg52/status/1709551516577902782).

I should also point out that your tone is aggressive, so it makes me think you're not interested in learning. But I'm going to proceed anyway.

It cannot understand these properties of words well because it does not operate on words, it operates on tokens. You can see examples here: https://platform.openai.com/tokenizer

This makes it much more difficult to learn how to reason about particular data that appears inside the token, because it does not ever receive that information. The only way it could get that information is if the training data explicitly attempted to work around this limitation.

But I would also appreciate insight from someone with a deeper understanding of the internals of these big LLMs.
Not hugely convincing to put a toy model up against a micro benchmark and claim the toy model proves the micro benchmark wrong.

The correct way to compare these approaches is with real code.
With special designs you can build up energy over time and then release it all at once, to reach sporadic super jumps. Example:

https://www.youtube.com/watch?v=mvHXwTa5-DA

(But for all but extreme designs I fully agree with you)
You need a way to track the sequence of comments. Not the comments, but the sequence of them, in a sha form. Some kind of ledger is the first thing that comes to mind.
I have found a trackball to be even better than a vertical mouse. Only your thumb moves.

Otherwise it's also Ergodox for me. I switched to Colemak at the same time, also have a programming layer ()[]{} etc. In addition I have a layer for cursornavigation and selection, word wise/char wise/start&ens of line/page wise, comparable to vim mode, but using the default shortcuts for Windows and macos (with the help of Karabiner)

It took a few weeks to get up to speed but I couldn't be happier.
Hacktivism erupts in response to Hamas-Israel war
Some previous discussion: https://news.ycombinator.com/item?id=37412331
Don't send every url, click a button to check for comments in urls you are interested in and aren't worried about anonymity on. If you are leaving "likes" or a comment anyway you are revealing you are at least aware of that url in the first place.
> Someday we'll look back and laugh (or cry) at our early USB struggles.

Hah, sounds like the editor is someone too young to have used serial/parallel/vga ports. Early business PCs, for what ever reason[1] were built like tanks. They weighed dozens of kgs/pounds. And the connectors were often screwed in with a screwdriver for good measure.

Yes, you could wing it when being sloppy, but they weren't always very tight and cables heavy so you'd want them screwed in for a long-term installation to avoid issues.

When USB came out it was a revelation that you just needed to pop it in and were done. Yes, you'd have to look at it first, but that was the same with every other port of before that. I remember PS/2 being perhaps hardest to line up correctly.

So USB 1.0 fixed one problem, but not every problem. Not exactly a reason to cry.

[1] Probably inertia from main/minicomputers which were serious installations and needed to keep running through wartime. :-/
Charles Feeney, Who Made a Fortune and Then Gave It Away, Dies at 92
Just to throw the other side's perspective of the argument into the ring, the ones reducing the observed phenomena to obviously anything can seem emotional and defensive of some metaphysical person-ness.
It's the parent discipline, marketing, which concerns itself with feedback.
It walks into your room, discovers you, and moves in to make the kill, but for some reason the gun trained at an odd angle. You see it take two shots that veer across to the corner of the room before it hilariously enters some self-correcting routine, seems to rediscover you, and finally blows your head off.

You get a chuckle before you die
> I don't think I'm a fear mongerer but the amount of reasonably qualified jobs that can be displaced by the models we have now seems huge.

Maybe I'm living under a rock, but I have serious doubts about this claim.

> Think graphic designer at medium-sized law firm. Or copywriter at a scientific publisher.

How is that even possible? Take the example of the graphic designer. You'd still need them to iterate on ideas, come up with different versions for different backgrounds, generate different file types depending on the medium and format, etc. Extremely skeptical of your claims.
how do you explain the nuclear navy's safety record?
Not in the context we're talking about
Everyone else is going to spontaneously force rules onto others? And how exactly do you see that working when the party breaking some rule resists?

It's exactly this kind of magical thinking that has resulted in essentially no state-equivalent anarchist societies actually managing to function and exist in modern times, the few that pop up get slammed down by states, because they really suck at resisting. The closest you seem to get are situations like the Zapatistas that are libsoc, not anarchist, since they still have a state.
Cloud Developer Environments but Why?
Some thoughts about Cloud Developer Environments from using them the past year!
Vote Bolsonaro, chose antiscience, live with the consequences...

2021, the devastation in the Brazilian Amazon running at its fastest pace in 10 years

2023, help, water has vanished

I'm seriously tired of all this clownery. When do you will put this man into a jail?
I could be wrong but usually melting and molding the metal is an easier way to get a specific shape on Earth. Don't see why you couldn't just do that if you wanted a combination of some shapes.

I'm wondering if there's an application as a self-destruction mechanism on a lock or something like that. There's still far easier methods.
Only slightly exaggerated for the sake of humor, I'd say. I have a friend who frequently takes the train and she often has to call her husband to come get her in a nearby city to avoid scheduling catastrophes.
> LLMs have no real understanding

A large language model trained on Othello games will actually build a "board representation" inside its neural network: https://thegradient.pub/othello/. This was confirmed by editing the board representation inside the neural net, "tricking" it into "believing" the board was in a different state. At this point, the LLM started making legal moves based on the edited position. If the LLM is actually building a data structure describing the board state, then it's hard to claim it's just acting as a parrot.

The raw version of GPT apparently achieves an Elo score of 1800 at chess: https://twitter.com/GrantSlatton/status/1703913578036904431. This is worse than a good dedicated chess engine, but almost certainly better than I could do!

And every day, I see Copilot occasionally perform non-trivial completions that require "in-context learning" of complicated things that exist only in my source code. Sure, it crashes and burns regularly, too, but I've seen a lot of cases where it could only have figured out the code it did by carefully combining information available in the file.

So I believe that LLMs can actually achieve surprisingly large amounts of understanding, particularly ChatGPT 4 and (on a good day) CoPilot. But the frustrating thing is that they're inconsistent, and the current RLHF process apparently impairs their ability to correctly estimate accuracy. When they make mistakes, they're effectively "blind" to those mistakes, to a shocking degree.
This is a forward thinking strategy for a camera maker. Instead of trying to fight the iPhone, they realized that this is a segment of the market they wouldn't capture regardless of the form factor they would adopt for Blackmagic cameras.

We have 4 Blackmagic cameras at xTribe studios and they are great, but when Gen-Z podcasters come in, they'll often just put an iPhone and a Rode shotgun mic on a SmallRig cage.
What happens there will be outside the purview of outside socities, it would become a land where safety and security is guaranteed by strength alone. Like you said? There will be warlords but they can't import arms but there will also be masses with rocks and sticks, nature abhors power so whatever power you align yourself with keeps you as safe as they can and punishes abhorrent actions and violate rights of those who are weaker. For some it will be utopia, for many it will be a nightmarish punishment where you are exiled to because of crimes you committed. Sort of like escape from LA/NY.
AFAIK there's no such thing as a standards compliant USB-C male to USB-C female extension cable. The very concept goes against the spec[1].

You have a point though; I'm sure there are abominations out there that abuse the USB spec in all sorts of interesting ways, they just haven't been something I've encountered in my years of using USB-C for everything.

[1]: https://www.reddit.com/r/UsbCHardware/comments/10xj74r/why_d...
In my work LUTs are a reaction to really poor performance, not a matter of course. Every time I reach for one my inner dialog says “you (probably) should use a lookup table”.
Defense in depth isn's about justifying in advance how every measure will win the battle; it's about giving yourself as many small, incremental advantages as possible so that the odds steadily tick up in your favor. Battles are famously difficult to predict so every advantage is sought, and even small advantages can have multiplier effects.
One big difference is that LLMs don't do loops, new words are produced in a fixed amount of steps. They can't go "give me a minute", think for a bit in the background and come back with an answer. That's why you can often get better answers when you force them to go through the individual steps, as that allows them to use the prompt history as working memory.

That said, this all seems like a 'fallacy of composition'. Humans are not LLMs, so much should be obvious, but at the same time concluding that they are completely different just feels wrong. The mistakes LLMs make feel very similar to what humans do when they don't have the time to deeply think about a problem and just give you the best guess that pops into their head. Humans will have other systems on top that allow them deeper reasoning, but the language generation really doesn't feel all that different from what LLMs do.

That aside, humans interact with the world, they get instant feedback on what of their predictions is right or wrong. LLMs are stuck with just static training data that might simply not be enough to develop higher level reasoning skills.
And if you've been on these stairs you know that down is the hard part.
why use (abuse) the word "person" then?
Trust me, you need to get to the radio cutscene. You'll understand why.
I think very few people think one word at a time, like a LLM.

A lot of people think in concepts without words at all in many scenarios. E.g. when you cook an egg, do you reason (in words) with yourself to decide what temperature to set the dial on the stove? Or do you just do it “without really thinking”?

Does your brain respond with annoying disclaimers when asking yourself medical questions? Does your brain refuse to entertain an idea if it’s questionable?
And indeed there are usb-c hubs that only work in one orientation so we now have the worst of all possible worlds.