supern0va

imagine thinking than people actually care about truthness

I think they actually care about "truthness" when it comes to how others will perceive them. You might filter your face for an online photo.

However, you're not going to want to look at yourself through your selfie camera with a filter that hides your imperfections when you're checking to see if something is stuck in your teeth on a date, don't you think?

There's nuance. People will fudge the truth to be perceived better, but don't want to be lied to when gathering data about how to be perceived better.

I find it easy to envision a world, maybe 50 years from now, in which the very concept of "truth in advertising" is viewed as a lost, idyllic fantasy. Something people are nostalgic for, but feel powerless to regain.

Alternatively, perhaps we'll see models fine-tuned or steer-able towards accuracy that customers can themselves use to get a more honest view on what the product would look like in person.

The funny thing about these tools is that they can go either direction, but it sure seems like there's the potential for it empower individuals and shift the balance. Clothing sales shifting online has given sellers the advantage/ease to deceive without much customers can do other than hope the reviews aren't manipulated (they are) even before AI. Maybe this can turn things around as people start to shop with personal agents.

Here's a better question: as we've had nearly as large of a data center build-out happen between 2005 and 2020 for non-AI purposes, with similarly high electricity and water demands...where has the concern been? Why is it only in the last 2-3 years that people are suddenly up in arms, as a very specific application is being deployed?

Not exactly. There are some data centers being built in places that don't have the power and water to support them, and obviously it's rational for the locals to oppose them.

But I live in a place where we have plenty of water and relatively cheap power (lots of renewables). There's not much risk to data center construction, but people are opposing it here, too. Because for most people, it's not actually about that.

People are scared about the personal impact from AI, then backfill in justifications without even realizing they're doing it.

If the equivalent numbers for electricity and water usage were being being used for streaming video, I seriously doubt people would be demanding no more Netflix data centers. The news story would immediately die.

Yeah, Cognition's work is interesting in that regard, but it still doesn't obviate the need for the chips--it just enables training on them when they're spread across multiple data centers.

The Plan A proposal estimates that the ownership of ~96% of AI relevant compute hardware can have its ownership traced, since the companies selling are very few.

I recommend actually reading their recommendation, because they get into the weeds about precisely how the US and China could address this in a trustless/auditable way. The TL;DR is that basically all of the relevant compute can be tracked.

Edit: Also, definitely not a Chinese op. The authors are prominent Americans, and are the folks responsible for the AI 2027 forecast that has pretty accurately predicted the current state of affairs today: https://ai-2027.com/

You want to be a child forever, amazed by your toys or the new things you can do.

I don't think having a child-like sense of wonder at the world, or continued human ingenuity, is a sign that one wants to be a child forever.

I'm genuinely sorry if you've lost that spark.

You don't need take a dog for a walk, if you live in a normal place that allows dogs to roam freely.

I love my dog and love walking him, even though he can freely roam on my property. I also love walking with my wife, and I don't think her agency has much reason for why I might enjoy it?

Your mind is a servant of your body. And your body never asked you for that.

...are you okay, friend?

It's coming from a place of objecting to burnout/overwork culture.

Sure, but that's not everyone. I want this because it's hard to carve out time for my fun side projects. :)

Also, not everyone feels burnt out or overworked, and may find their actual work enjoyable. I've definitely had many showers where I've been thinking about interesting work problems and never felt particularly burdened by it (quite the opposite, in fact).

I'd argue what you're suggesting is more like trying to ban syringes, which have multiple valid uses, in order to stop dirty syringes being left in the street.

As someone with a GLP-1 user at home, responsibly depositing their syringes in an approved container that we dispose of safely at a drop site, I'd rather not have bad users inhibit my access to a tool that makes our lives better.

I'm curious, do you have an example of a level of "woke" extremeness demonstrated by the "rest of them" that is on par with Mecha-Hitler? Because yes, all views on reality are indeed political, but the tendency of most of the models is actually toward the middle, with perhaps some left bias.

I can't help but think you're conflating cause and effect. People are using a tool (AI) to apply a band-aid to a widespread social problem (loneliness and isolation).

It's possible that an "AI boyfriend" might make someone less prone to put in the continued effort to keep rolling the dice on dating apps, but the reality is that there's a more fundamental problem driving this.

Also, I want this tool for work. Just because society is fubar and people are using this tool as a crutch for their inability to find a partner, doesn't mean I should lose better tooling that makes my life easier.

Focus on fixing the actual problem.

Every time something along these lines is posted, comments like this show up.

The thing I don't get is...no one would say this about listening to a podcast or audiobook on a walk.

I'm not sure why people choose to demonize this specific use of time during walks.

Counter-point: I love that my rubber duck can talk (quack?) back, as well as record and summarize my thoughts on topics I'm working or stuck on.

I've wanted a good voice mode for precisely this reason. When I take my dog on a walk and I'm thinking about a bunch of problems/ideas, I'd love to have feedback and a record, or perhaps to even kick off research or ask questions to fill in gaps that would otherwise have me debating pulling out my phone to try to get an answer.

I have to admit that I'm curious why this is the case. I almost wonder if the pseudo-anthropomorphizing of these models is partially what helps here, similar to how I don't take it personally when I give instructions to a junior engineer and they fuck it up (though, I probably should to at least some degree more than I do).

The same reason we had them before? A few juniors can be productive with oversight and guidance. Half the battle is learning what good work looks like, and figuring out what it is that you should even really be building, and those are skills you develop.

Same here. Honestly, there's also a bunch of human friction that goes away. I can tell a junior that a change needs to be significantly refactored (or even thrown away entirely) without the psychological damage of discarding days/weeks of work from them.

Previously, I would need to do the trade-off calculation. How urgently does this need to ship, and do we have time to rework this? What are the deal breakers that need to be addressed, versus what things are best practice/ideal for maintainability? How did their last code review go and do they need a small win right now?

There's no more "nit" comments tagged as nits: just things to fix. It's de-personalized in the sense that we can both at least pretend/have plausible deniability and blame the model for being dumb, as opposed to the person making mistakes. I flat out told someone that a PR was not solving the right problem earlier, and neither of us thought it was a big deal. I could give the technical guidance and suggest a path forward to "help Claude understand better".

First year CS student excited to learn about a thing puts together a small website of academic papers, posts it to HN to share with others.

Then someone makes a shitty comment. Is that correct?

Honestly, I'm puzzled that people don't intuit that "understanding" itself is merely ideas in relation to other ideas.

They never are. Ever.

And even when they are: they sure seem to bet against Moore's Law or just the general tendency for things to get better/efficient over time.

It's frankly remarkable how capable the models have become that we can run locally now on a decent laptop.

The same thing happened with image generation. I've had arguments with people that image generators are killing the environment, but I can do it in 20-30 seconds on my GPU. No one bats an eyelash when I play 20-30 minutes or even hours of a video game on my GPU, but the images are burning down the planet.

It's slightly maddening.

and even if it requests another angle and is given it, it lacks the capacity to learn that new information permanently.

I'd argue this isn't true today, but that the loop for incorporation is long (ie, the next training or finetuning run).

A multimodal model knows about images of pipes and facts about pipes, but doesn't know pipes; it doesn't have literally first-hand experience with them.

Wouldn't this mean that any human who hasn't seen a pipe in person or interacted with it, similarly doesn't "know" a pipe? Most of us haven't interacted with the vast majority of "things" in the world, yet we're still able to build a model and abstractions for them such that we can reason about them, right?

And even then, it's just sampling. Much of what we "see" is a prediction, and there are plenty of optical illusions out there premised on that (plus VR techniques like foveated rendering that take advantage).

I've been using it to do this for 2 years now. And many people with me. The change you mention is one of is primarily one of Overton windows, of vibes.

I suspect this may have depended on the specific framework. I quite literally could not get Claude (in Cursor) to give me a basic Micronaut setup in a fresh workspace with essentially a "hello, world" API. I would guess that if you're using something like Python and FastAPI, it might have been an easier task or better represented in the data.

The difference that I observed in the Opus 4.5 era is that Claude could take a service framework it has never seen before (proprietary corp) and figure it out.

I was worried this time last year that by this time this year, companies would have slashed their engineering teams down to a handful and everything would be driven by mostly autonomous agents with human guidance. But it just hasn't happened.

I find this somewhat puzzling. I thought things were moving quickly, but at this time last year I couldn't even get Claude (using Cursor) to spin me up a service skeleton that would compile, let alone do anything meaningful.

I know it feels like a long time somehow, but it was only between November and February that things started to actually somewhat work without significant hand holding. Even now, it seems like we're still figuring out how to fully leverage the current models and tooling, even in organizations that have largely gotten on board.

This is really fascinating to me. I was reading this article and originally agreed with you, "I mean, under the covers it's got to be converting to text tokens at some point, so there is no way it's actually cheaper for Claude itself to execute."

It'd be weird if they were doing this, since it would mean the context window size was a lie and that the API would presumably reject requests whose expanded form went over the 1m limit. For someone using pxpipe with an effective context compression of 90% in some instances, it'd hit the limit at barely 100k.

There is just no way to go past what we have already observed by their behavior since dogs can't talk or write.

There are many dogs that have been trained to press buttons corresponding to words, in the extreme case tens/hundreds of buttons/words, and they can even construct rudimentary sentences. It doesn't seem insane to me that we could perhaps do a very rudimentary version of this for dogs, given a large enough training set.

It's currently broke people chat.

Also the article could be trying to normalize thinking that these are more than matrix multiplication gadgets good at compression.

Honestly, I think it's less so (for some of us) that we think they're "more than matrix multiplication gadgets good at compression", so much as thinking that perhaps what our brains are doing is not so dissimilar.

A materialist view of the world could support the idea that intelligence itself may just be a series of predictions from a big compressed multi-modal dataset. That's not to say that LLMs are doing it in a way that is even close to how our brains are doing it, but we also don't understand how different it may be, and how much utility we can get out of them even with the current architecture.

You're right, there is an all powerful wizard who can take away all the world's computers. You got me.

There's a reason Yudkowsky only thinks AI can be stopped by literal missile strikes against data centers.

It's famously difficult to find people willing to rent you time on big computers over the internet.