MurphyA/hacker-news huggingface dataset:
by nonhaver | 2025-08-08 00:30:10+00:00
not to offend - but it sounds like your response/worries are based more on an emotional reaction. and rightly so, this is by all means a very scary and uncertain time. and undeniably these companies have not taken into account the impact their products will cause and the safety surrounding that.

however, a lot of your claims are false - progress is being made in nearly all the areas you mentioned

> hallucinations

are reduced with GPT-5

https://cdn.openai.com/pdf/8124a3ce-ab78-4f06-96eb-49ea29ffb...

"gpt-5-thinking has a hallucination rate 65% smaller than OpenAI o3"

> limited context window

same deal. gemini 2.5-pro has a 1 million token context window and GPT-5 is 400k up from 200k with o3

https://blog.google/technology/google-deepmind/gemini-model-...

"native multimodality and a long context window. 2.5 Pro ships today with a 1 million token context window (2 million coming soon)"

> expensive to operate and train

we don't know for certain but GPT-5 provides the most intelligence for the cheapest price at $10/1 million output tokens which is unprecedented

https://platform.openai.com/docs/models/gpt-5

> guardrails

are very well implemented in certain models like google who provide multiple safety levels

https://ai.google.dev/gemini-api/docs/safety-settings

"You can use these filters to adjust what's appropriate for your use case. For example, if you're building video game dialogue, you may deem it acceptable to allow more content that's rated as Dangerous due to the nature of the game. In addition to the adjustable safety filters, the Gemini API has built-in protections against core harms, such as content that endangers child safety. These types of harm are always blocked and cannot be adjusted."

now id like to ask you for evidence that none of these aspects have been improved - since you claim my examples are vague but make statements like

> Inability to recall simple information

> inability to stay on task

> (doesn't) support its output

> (no) long term planning

ive experienced the exact opposite. not 100% of the time but compared to GPT-4 all of these areas have been massively improved. sorry i cant provide every single chat log ive ever had with these models to satisfy your vagueness-o-meter or provide benchmarks which i assume you will brush aside.

as well as the examples ive provided above - you seem to be making claims out of thin air and then claim others are not providing examples up to your standard.
by jackcurran | 2025-08-08 00:30:32+00:00
Here is our Kickstarter Project Link. We'd love your support! My best friend and I have spent the past year trying to track the environment in our NYC apartments, cafés, and subway cars. We tried the usual handheld monitors and bulky bricks, but none were truly pocket‑friendly, user friendly, and most importantly, they only tracked a single metric, and poorly at that.

So we built our own. Made it a powerhouse of multiple sensors. And miniatured it to fit in your pocket when you want to put it away.

Our device (named Halo Air after our favorite game, Halo 3) snaps to the back of any smartphone and streams CO₂, PM1/2.5/10, t‑VOCs, temp, and humidity into our app, a lockscreen widget, and we'll be making the data feed available too. No disposable batteries, no calibration stickers—just one USB‑C charge and go.

We just hit Kickstarter yesterday. If you’re curious, we’d love your feedback (good, bad, brutal) and—if it resonates—your support as early backers. The link’s in the first comment to avoid spamming the post.

Huge thanks to Reddit for the inspiration threads on sensor accuracy, cross‑calibration, and DIY enclosures; your collective brainpower shaped Halo Air more than you know.
by seadan83 | 2025-08-08 00:31:45+00:00
Burden of proof is to show that AGI can do anything. Until then, the answer is "don't know."

FWIW, it's about 3 to 4 orders of magnitude difference between the human brain and the largest neural networks (as gauged by counting connections of synapses, the human brain is in the trillions while the largest neural networks are low billion)

So, what's the chance that all of the current technologies have a hard limit at less than one order of magnitude increase? What's the chance future technologies have a hard limit at two orders of magnitude increase?

Without knowing anything about those hard limits, it's like accelerating in a car from 0 to 60s in 5s. It does not imply that given 1000s you'll be going a million miles per hour. Faulty extrapolation.

It's currently just as irrational to believe that AGI will happen as it is to believe that AGI will never happen.
by rcxdude | 2025-08-08 00:32:58+00:00
Because reading the different ideas about airfoils and actually deciding which is the more accurate requires a level of reasoning about the situation that isn't really present at training or inference time. A raw LLM will tend to just go with the popular option, an RLHF one might be biased towards the more authoritative-sounding one. (I think a lot of people have a contrarian bias here: I frequently hear people reject an idea entirely because they've seen it be 'debunked', even if it's not actually as wrong as they assume)
by fsckboy | 2025-08-08 00:33:43+00:00
I wish we could get away from putting syntax and naming betweeen us and languages.

io.write is really annoying to me. rw.read and rw.write makes much more sense, or io.in io.out.

io.writeInt writes an int as what, ascii/unicode, or binary? an Int is likely already binary/2's complement, and the language should print strings too, it's just a bad name.

leaving parentheses out surrounding predicates and/or a semicolon at the end should be my choice, not yours, it has nothing to do with the language and I have preferences.

If languages provided flexible syntax per user, divorcing themselves from syntax, then the further description of the language would be semantic. I have no idea what the semantics of this Q are, or are intended to be, and that's what matters. Compilation speed? that's not a language.
by cpncrunch | 2025-08-08 00:33:51+00:00
No, i mean what is the context. Who created this originally? Where is the link to openai or whoever creating this chart, or context behind the misinformation if any. I check the comments and stories about chatgpt5 and there is no reference to this, so im at a loss.

Ok, I see there was a bug on the site and it wasn't scrolling on iOS. They fixed that now, although the background context is still unclear, and none of the links in the site seem to explain it.
by mindcrime | 2025-08-08 00:34:11+00:00
It's an active attack (requires you to transmit traffic to trick the radio into sending the response beacons) so at the very least you'd almost certainly be in violation of some FCC regs. So the charge might not be "tracking law enforcement" but rather would be "illegally transmitting on a public safety frequency without a license" or something along those lines. And if somebody got caught doing this, I'm reasonably sure they'd find a way to pile on a few more charges as well.

And note that since it is an active attack that requires the attacker to transmit, it opens up the possibility of the attacker giving up their own location in turn.

My take is that it's fun to think about, but largely lacking in real world applicability in most situations.
by AIPedant | 2025-08-08 00:35:31+00:00
It is actually incredible how they managed to find an even more unscientific definition than "can perform a majority of economically useful tasks." At least that definition requires a little thought to recognize it has problems[1]. $100bn in profits is just cartoonishly dumb, like you asked a high schooler to come up with a definition.

[1] If a computer can perform the task its economic usefulness drops to near zero, and new economically useful tasks which computers can't do will take its place.
Economic Productivity, Technology and Wage Growth
by morpheos137 | 2025-08-08 00:36:34+00:00
Economics is a strange field purpoting to be quantitative and scientific but beset by quasi ideologies.

My higher education background is in Economics.

Traditionally it is held that increasing technology and productivity increases economic output resulting in growing real wages over time as workers take their slice of a growing pie.

But what happens in a consumption driven economy when technology and automation enable capital holders to take an ever larger slice of the pie because to satisfy consumer demand they need ever fewer people in production per unit product?

The traditional answer is the service economy expands.

But what happens when the same thing happens in services and even things like dog walking are increasingly provided by app hawking mega corps such as Wag?

Does there come a point when an economy can logistically satisfy demand but due to the surplus of workers and concentration of ownership of production factors into ever fewer hands can not distribute its production effectively through wage income to consume?

What about when wage earners in other countries make the majority of our consumption goods and our purchasing power is merely buoyed by the waning strength of our currency?

Personally I think we have several possible futures.

One is democratic socialism with UBI based on local soviets.

Another is implosion and civil strife.

Another is unknown.

The first one is unlikely because people have bought into a transitional liberal economic capitalist system that only was efficient due to the 19th century industrial revolution.

ChatGPT, ads for toenail fungus on Youtube natue documentaries nobody wants, and Facebook likes can't power an economy.

I think the most likely outcome is civil strife and war as the old ststem collapses under its own weight.

Maybe then we can finally revert to rural agrarian Communism or hunting and garthering as is more appropriate for humanity and as we lived in contentment and peace for thousands of years.

What do you think?
by godelski | 2025-08-08 00:38:56+00:00
> which is what you get when you look at non-LLM alternatives to General Intelligence.

I disagree with this. There are a good ideas that are worth pursuit. I'll give you that few, if any, have been shown to work at scale but I'd say that's a self-fulfilling prophecy. If your bar is that they have to be proven at scale then your bar is that to get investment you'd have to have enough money to not need investment. How do you compete if you're never given the opportunity to compete? You could be the greatest quarterback in the world but if no one will let you play in the NFL then how can you prove that?

On the other hand, investing in these alternatives is a lot cheaper, since you can work your way to scale and see what fails along the way. This is more like letting people try their stuff out in lower leagues. The problem is there's no ladder to climb after a certain point. If you can't fly then how do you get higher?

> Invest in what else exactly? ... it's the only basket that exists.

I assume you don't work in ML research? I mean that's okay but I'd suspect that this claim would come from someone not on the inside. Though tbf, there's a lot of ML research that is higher level and not working on alternative architectures. I guess the two most well known are Mamba and Flows. I think those would be known by the general HN crowd. While I think neither will get us to AGI I think both have advantages that shouldn't be ignored. Hell, even scaling a very naive Normalizing Flow (related to Flow Matching) has been shown to compete and beat top diffusion models[0,1]. The architectures aren't super novel here but they do represent the first time a NF was trained above 200M params. That's a laughable number by today's standards. I can even tell you from experience that there's a self-fulfilling filtering for this kind of stuff because having submitted works in this domain I'm always asked to compare with models >10x my size. Even if I beat them on some datasets people will still point to the larger model as if that's a fair comparison (as if a benchmark is all the matters and doesn't need be contextualized).

> Because those people have still not been proven right.

You're right. But here's the thing. *NO ONE HAS BEEN PROVEN RIGHT*. That condition will not exist until we get AGI.

> scream, "See!, those people were wrong all along!" to you ?

Let me ask you this. Suppose people are saying "x is wrong, I think we should do y instead" but you don't get funding because x is currently leading. Then a few years later y is proven to be the better way of doing things, everything shifts that way. Do you think the people who said y was right get funding or do you think people who were doing x but then just switched to y after the fact get funding? We have a lot of history to tell us the most common answer...

[0] https://arxiv.org/abs/2412.06329

[1] https://arxiv.org/abs/2506.06276
by johncolanduoni | 2025-08-08 00:39:03+00:00
They already failed then. All sides (browser->website and browser->passkey holder) of passkeys are open standards. They already don’t restrict passkeys from e.g. open source apps they have no control over, for both Google accounts and any site on Chrome. Webauthn “fails open” by default in the sense you’re indicating; if you don’t check the attestation, any app or device made by anyone can hold a passkey. I haven’t encountered or heard of anyone restricting passkey apps/hardware outside of business-managed employee accounts.

I recommend reading the MDN docs on Webauthn, they’re surprisingly accessible.

> Yes, they did, just see Microsoft's crusade against Linux and the origin of the "embrace-extend-extinguish" term.

The whole point of the trial that term came from was that Microsoft explicitly saw Linux as a material threat to their business. What threat are Google quashing by preventing you from using passkeys they don’t control?
by rcxdude | 2025-08-08 00:40:35+00:00
I think OpenAI's definition ("outperforms humans at most economically valuable work") is a reasonably concrete one, even if it's arguable that it's not 'the one true form of AGI'. That is at least the "it will completely change almost everyone's lives" point.

(It's also one that they are pretty far from. Even if LLMs displace knowledge/office work, there's still all the actual physical things that humans do which, while improving rapidly with VLMs and similar stuff, is still a large improvement in the AI and some breakthroughs in electronics and mechanical engineering away)
by Sharlin | 2025-08-08 00:41:13+00:00
> It is frequently suggested that once one of the AI companies reaches an AGI threshold, they will take off ahead of the rest.

Yes. And the fact they're instead clustering simply indicates that they're nowhere near AGI and are hitting diminishing returns, as they've been doing for a long time already. This should be obvious to everyone. I'm fairly sure that none of these companies has been able to use their models as a force multiplier in state-of-the-art AI research. At least not beyond a 1+ε factor. Fuck, they're just barely a force multiplier in mundane coding tasks.
by l33tman | 2025-08-08 00:41:40+00:00
I started such an alternative project just before GPT-3 was released, it was really promising (lots of neuroscience inspired solutions, pretty different to Transformers) but I had to put it on hold because the investors I approached seemed like they would only invest in LLM-stuff. Now a few years later I'm trying to approach investors again, only to find now they want to invest in companies USING LLMs to create value and still don't seem interested in new foundational types of models... :/

I guess it makes sense, there is still tons of value to be created just by using the current LLMs for stuff, though maybe the low hanging fruits are already picked, who knows.

I heard John Carmack talk a lot about his alternative (also neuroscience-inspired) ideas and it sounded just like my project, the main difference being that he's able to self-fund :) I guess funding an "outsider" non-LLM AI project now requires finding someone like Carmack to get on board - I still don't think traditional investors are that disappointed yet that they want to risk money on other types of projects..
by RachelF | 2025-08-08 00:42:54+00:00
This is why keyless "start button" functions on cars is a bad idea.

The old approach of keyfob to unlock the car and a real key for the ignition is safer.

Having multiple levels of security is good.

However, having worked in the car security industry many years ago, I discovered that car manufacturers actually like it when their customer's cars are stolen - Insurance payouts often result in another sale.
by darylteo | 2025-08-08 00:42:55+00:00
It's not a hard logic path to follow - If AI becomes a digital necessity for modern society to function, Microsoft's relevance shrinks while OpenAI's relevance grows.

Once OpenAI breaks out of the "App" space and into the "OS" and "Device" space, Microsoft may get absorbed into the ouroboros.

OpenAI's dependence on Microsoft currently is purely financial (investment) and contractual (exclusivity, azure hosting).
by ankit219 | 2025-08-08 00:43:29+00:00
Anthropic in the latest fundraise announce their gross margins are around 60%. Typically in the industry now, the gross margins are reported as revenue - cost of only serving paid users (free users etc. go in either cac or r&d). The thing is, with this margin, Anthropic can serve 2.5x more tokens than say cursor without making a loss for the same price compared to cursor. This reality is likely going to hit other startups based on the same assumption too. Anthropic has not reduced its pricing in almost a year now.
by Lerc | 2025-08-08 00:45:33+00:00
>It is frequently suggested that once one of the AI companies reaches an AGI threshold, they will take off ahead of the rest. It's interesting to note that at least so far, the trend has been the opposite

That seems hardy surprising considering the condition to receive the benefit has not been met.

The person who lights a campfire first will become warmer than the rest, but while they are trying to light the fire the others are gathering firewood. So while nobody has a fire, those lagging are getting closer to having a fire.
by seadan83 | 2025-08-08 00:45:54+00:00
To your interesting aspect, you're missing the most important (IMHO): accuracy. All 3 are really quite important, missing any one of them and the other two are useless.

I'd also question how you know that ants have zero knowledge of what they do. At every turn, animals prove themselves to be smarter than we realize.

> And because of how it helps to distribute "the information" better.

This I find interesting because there is another side to the coin. Try for yourself, do a google image search for "baby owlfish".

Cute, aren't they? Well, turns out the results are not real. Being able to mass produce disinformation at scale changes the ballgame of information. There are now today a very large number of people that have a completely incorrect belief of what a baby owlfish looks like.

AI pumping bad info on the internet is something of the end of the information superhighway. It's no longer information when you can't tell what is true vs not.
by jjav | 2025-08-08 00:47:14+00:00
> Absolutely valid to say that "best and highest use" is vague and untrustworthy at best, but it's said this way to avoid getting trapped in the weeds of what exactly it means.

I mean.. if there was to be a law established to do it this way, it better go into very precise detail of exactly what it means and a verifiable mechanism and formula of how it is calculated.

Anything else would be a wide open door for corruption where assessors can do whatever they want to benefit various groups and harm others.
by danparsonson | 2025-08-08 00:47:16+00:00
OK, well, all I will add is that I've been where you are on this now, and I've also been an architecture astronaut, and now I'm somewhere in the middle. This is where I've landed based on long experience. I know which code I prefer to maintain, and it's not the big ball of mud that, in my experience, inevitably results from insufficiently abstracted designs. I'm absolutely not making my life harder; I'm making life much easier for my future self, and this is borne out by actual experience on projects I've worked on.

However as I said, there's no hard and fast rules, so, you do you.
by chrismccord | 2025-08-08 00:47:42+00:00
I'm really bummed out by this release. I expected this to best sonnet, or at least match, given all the hype. But it has drastically under performed on agent based work for me so far, even underperforming gpt-4.1. It struggles with basic instruction following. Basic things like:

- "don't nest modules'–nests 4 mods in 1 file - "don't write typespecs"–writes typespecs - "Always give the user design choices"– skips design choices.

gpt-4.1 way outperforms w/ same instructions. And sonnet is a whole different league (remains my goto). gpt-5 elixir code is syntactically correct, but weird in a lot of ways, junior-esque inefficient, and just odd. e.g function arguments that aren't used, yet passed in from callers, dup if checks, dup queries in same function. I imagine their chat and multimodal stuff strikes a nice balance with leaps in some areas, but for coding agents this is way behind any other SOTA model I've tried. Seems like this release was more about striking a capability balance b/w roflscale and costs than a gpt3-4 leap.
by morpheos137 | 2025-08-08 00:47:46+00:00
There is zero reason or evidence to believe AGI is close. In fact it is a good litmus test for someone's human intelligence whether they believe it.

What do you think AGI is?

How do we go from sentence composing chat bots to General Intelligence?

Is it even logical to talk about such a thing as abstract general intelligence when every form of intelligence we see in the real world is applied to specific goals as evolved behavioral technology refined through evolution?

When LLMs start undergoing spontaneous evolution then maybe it is nearer. But now they can't. Also there is so much more to intelligence than language. In fact many animals are shockingly intelligent but they can't regurgitate web scrapings.
by ramoz | 2025-08-08 00:49:50+00:00
Happy to short that bet as I think agentic harnesses will be molded along the RL training of the actual model. Tony + the suit created together. Why Claude in Claude Code became existential for Cursor, why cursor moved quick to go agentic and build up with OpenAI in big header line way here.

Unless they pair up with OpenAI or Meta.
by steve_adams_86 | 2025-08-08 00:50:59+00:00
I mean it in the kindest way, but scientists might be the sloppiest group I've worked with (on average, at least). They do amazing work, but they're willing to hack it together in the craziest ways sometimes. Which is great in a way. They're very resourceful and focused on the science, not necessarily the presentation or housekeeping. That's fine.
by shruggedatlas | 2025-08-08 00:51:31+00:00
> lower-to-middle of the middle class

The comparison was clearly between the rich and the poor. We can take the 99.99th wealth percentile, where billionaires reside, and contrast that to a narrow range on the opposite side of the spectrum. But, in my opinion, the argument would still hold even if it were the top 10% vs bottom 10% (or equivalent by normalised population).