I think we gotta get people to see past the false dichotomy: part of their increased cost of living is due to climate change:

- your home insurance is more expensive b/c fire/hurricane/etc risk is worse in your state

  - and you probably don't have flood insurance but the risks there are worse too

- your electricity bill is worse b/c you're using AC more b/c it's hotter

- climate change does have healthcare impacts, including expanded geographic range of a bunch of vector-borne illnesses, as well as acute issues during heat events. Even if you're not directly one of these patients, your health insurance costs will increase in part due to these risks.

- replacing key infrastructure which is damaged by extreme weather is expensive

- during extreme weather events, your ability to earn may be disrupted

- and every business you spend at also has increased costs due to the same factors, which they pass on to you

It turns out that multiple generations of emitting without paying attention to the externalities has created literal costs that we _all_ now bear, and these costs will continue to increase.

> I strongly believe that video games have a higher ceiling for storytelling quality. There are several reasons underlying my newfound evangelism: a larger built-in audience, a more robust market with hundreds of games appealing to many different types of fans, and, most importantly, demographic variability.

So none of the things listed here are clearly related to "storytelling quality" -- those are marketing advantages.

I think the real questions for _quality_ for comics vs games are things like:

- do games, which force players to explore and interact, forcing better world-building by front-loading some consideration of internal logic and mechanics?

- do games, which put players more directly in the perspective of characters, at the level of having to choose actions, force writers to create more compelling dilemmas?

- do comics, which have to give consideration to static visual images, make for better posters than films?

- do comics, which world-build over long sequences, make for stories that feel too compressed in films?

I think also it's extremely hard to fairly judge high level decisions whose outcomes may not materialize for a very long time. This makes it genuinely hard for humans to get better (and one gets the impression that most of them don't) with more experience at the helm of a large and complex org. But it also means that it's hard to evaluate or train a machine on the task. You can maybe automate getting something plausible out, but how would you know if it was _good_ in a timely way? So how do you review a configuration or prompt change in this repo?

By using historic data.

You should strictly segregate training and testing data, to be sure that your model has internalised decision-making principles. [0]

It is definitionally true that any given moment in history is unprecedented, and that old thinking is invalidated by paradigm shifts. But not every single variable is randomised. The launch of the PC didn't embarrass every executive, for example.

0: https://www.owlposting.com/p/an-ml-drug-discovery-startup-tr...

Wait, wait, gerrymandering messes with the House, but how does gerrymandering impact control of the Senate? Don't senators need to be elected by their whole state?

I think he's just using "gerrymandering" (incorrectly) to vaguely refer to anything that's anti-democratic, such as a chamber that isn't proportionally elected.

So, maybe this is not quite a fair analogy but a lot of famous modern artists don't do a lot of the actual execution of their work. If Jeff Koons relies on a team of artisans and technicians to make a balloon dog, and if Dale Chihuly depends on a workshop of glass blowers to make a chandelier, and if Paul Cummins used a team of ceramicists to make poppies, what did the headlining artist contribute? Not everything, certainly, but also not nothing. Ideas, vision, feedback, guidance?

I think we're used to the idea in math of generally every idea coming from a specific contributing human. In code, maybe less so, but still we generally we find it useful to attribute at least _lines_ to who touched them last. But maybe, if Claude were just less annoying in the prose it made, and could better imitate an actual human, we'd be able to get used to the idea of humans claiming credit for something that the human guided the software to create?

I appreciate the connection to artists guiding their teams. I think that's a good analogy.

At the same time, when Koons or Chihuly or Cummins sign their work I do have that expectation that they guided the piece in a meaningful and material way or that the people who built it did it in such a way that owes lineage and authorization to the style Koons/Chihuly/Cummins developed. If I asked one of them about their work and it was clear that they had become so disconnected from it that they couldn't be seen as the authority on it, that they'd delegated that away, then I'd also feel them signing it had a mark of dishonesty about it.

To that end, I genuinely don't know Mr. Gomila's engagement here. Worse, it, to my ear, very clearly is written in a style that's extremely reminiscent of LLMs. In that way, it directly invokes that feeling of inauthenticity when he claims authorship.

This reminds me of academic writing there there's sometimes a convention in author lists that the first author(s) did more of the work and the last author(s) were the PIs and guides. This anchors the work amidst all the authors, at least loosely. I understand that if I want to ask a question about the details of the procedure I can reach out to the first author and if I'm trying to understand the larger research objectives of the lab I can investigate the last author.

Personally, I think I'd feel more comfortable with this piece if it were attributed in that style.

Or, again, if this is genuinely work done in the majority by Mr. Gomila and the writing feels LLM-derived for some other reason then it's merely an unfortunate side-effect of this writing register.

> Worse, it, to my ear, very clearly is written in a style that's extremely reminiscent of LLMs. In that way, it directly invokes that feeling of inauthenticity when he claims authorship.

I get that and also find the style annoying. But, e.g. when I wear a garment that was clearly machine sewn, sit on furniture made with powertools, look at a photo (where a mechanical process determined what pigments appear where, with what intensity), if I eat a taco whose tortilla was industrially rolled ... none of those things seems like a reason to challenge someone taking credit and responsibility for creating a thing, even if 250 years ago they would have had to engage in a much more onerous manual process to create something similar.

So what is it about writing that feels so inauthentic when the human delegates the word choice and sentence structure to a machine? Is it just cultural expectations, and we'll get used to it as LLMs exist longer?

I wonder if partly there's a feeling of disrespect on the part of the reader -- if the author couldn't be bothered to write every word, it's presumptuous to think that other people's time is less valuable and they should read word by word.

Cummins doesn't expect anyone to examine the details of every poppy; we look at the overall effect and maybe admire the detail on one or two flowers. Koons doesn't leave enough evidence of the individual welds for audiences to inspect them; that would destroy the effect. But the default way to consume a language based work is at the word level, and you can't just take in the gestalt in a moment, so the implied demands on attention are greater?

I think it’s because it’s reasonable to believe that the human author had no meaningful contribution. If he’d written “by Claude with direction from me” then I’d feel more comfortable. If he’d hand written in his own voice a methods section that laid out exactly how he prompted the LLM then I’d have no trouble digesting.

But to take ownership over words and thought in this way reads as nearly fraudulent to me.

The issue is AI text is annoying to read, not that the human didn't work alongside the AI to get the result in the first place.

To be fair, that wasn’t my issue. I don’t find it annoying. I find it misleading and nigh fraudulent.

At best, annoying, at worst, what you said, yep.

Why should intelligence _other_ than motor-planning be tied to the degrees of freedom of their movement?

- snakes have a high number of degrees of freedom but aren't especially bright

- squid have 2 more limbs than octopuses and aren't as smart

I think the shallow-water vs deep-water thing mentioned in the article is important; reef and similar environments give a lot more opportunities for smart camouflage, complex navigation, tool-use opportunities etc than the open ocean.

So their photoscan bodyfat % has a lower RMSE in predicting (DXA) body fat than their BIA bodyfat % ... but what BIA estimation did they use? I've been told that not all BIA is equal. They tell us:

> Fitbit Sense 2 was used to measure BIA on the wrist. It implements a 4-wire sensing mechanism using a 50kHz excitation frequency and utilizes two bottom electrodes, two top electrodes, and TI’s AFE4500 chip.

... huh I wasn't aware that fitbit offered wrist-based BIA? And I've heard that systems that have sensors across a long path in your body are better (e.g. foot and hand contacts)? But most confusing, the specs for Fitbit Sense 2 [1] don't say anything about BIA, just cEDA. I'm not an expert by any means, but google's own AI tells me that EDA sensors cannot be used for BIA. So did they basically use an especially low quality BIA measurement?

[1] https://store.google.com/us/product/fitbit_sense_2_specs?hl=...

For what it's worth, the Navy method (https://www.omnicalculator.com/health/navy-body-fat) always matched my DEXA scan results much more closely than any BIA scale I used ever did. Given that, it would make sense that you could estimate it from photos.

> It has been exceptionally well preserved because it was reused as a Roman-era paving stone on a colonnaded street

The sculpture is very 3-dimensional. I don't get how it made a good paving stone, or how being used as a paving stone didn't end up conflicting with the "well preserved" part more.

The back side of it looks pretty flat - perhaps it was buried face down, in two pieces. The Romans were pretty crafty about re-using things.

Besides which, ever been to/seen the streets of Pompeii? Flat, level surfaces for road construction only seemed important to the Romans as a side quest. They would fill the gaps with stone and mortar - perhaps that is the case here.

> The statue was discovered in two parts

So maybe it was about one of those parts and the lower one looks like it could be a decent paving stone.

So the 1970s oil crisis caused a shift that included fuel efficiency rules. For like, the whole time I've been a software engineer, memory footprints of a lot of software have crept up, even when they aren't really doing more.

The memory situation currently is a mess. But ... is it bad enough to get us to _change_ how we build?

That would be a great outcome of this situation. I doubt it will happen though: unlike fuel efficiency rules, there aren’t likely to be external pressures like that on software. Outside developer circles most users likely are unaware of memory usage and often just accept that computers are slow and unreliable sometimes. That’s different from drivers who see their fuel gauge and the corresponding cost of fuel, and are thus very aware of what fuel efficiency means.

The situation may be even more different from fuel. The memory shortage may be just a first of such crisis to come - the shortage of anything related to AI/robotics (from electricity to materials needed to produce robots and for the robots to produce even more robots). I think we have a runaway situation - the more of AI/robots produced, the more is demand for such production. The difference from classic production/manufacturing here is that AI/robots is a consumer itself. In the past the only consumers were people and human population growth is slow whereis AI/robots "population" is starting to explode. (Like Industrial Revolution on steroids - back then getting a steam engine to power your machinery was not just a jump in productivity, it was a jump without which you couldn't compete, and so everybody was getting it https://c8.alamy.com/comp/2RFT119/illustration-of-factories-... (and just for fun compare to https://www.reuters.com/resizer/v2/6BC2YPEXOZCGJKEO4LWH7CTLI... ) - fortunately for England back then getting a steam engine to produce more steam engines to thus make more and longer jumps in productivity didn't really work that fast and efficient whereis today the situation is becoming more favorable for such productivity multiplication)

Wrt. the memory efficiency - considering that AI is going to be the main workload by far and thus will vacuum in majority of the available optimization resources - be it humans or coding AI - i think it will be even less chances that any meaningful resources will be spent on optimizing on the fringe, ie. the users' OS/browser/etc.

This makes me think of Factorio. When you make a breakthrough like getting robots, what do you do with it? Use it to make more robot factories.

But in the real world, haven't we got to see whether all this investment will pay off? What happens if it turns out people actually don't want to pay for this?

We have been there before, for example: https://en.wikipedia.org/wiki/Railway_Mania

The companies go bankrupt their stuff is sold for pennies & investors loose their money.

The now super cheap stuff might get reused for something else, that is actually profitable. Or will just get dumped, like many unprofitable or never finished lines from the railway mania days.

People don't want to pay for it. It's fine when you can buy a monthly plan and get lots of usage at the company's loss, but that's not sustainable.

Once everyone has to pay enough for the usage to just break even, it's going to be a shitshow. And what's worse, they'll have to make up for all the debt they're accumulating now, so even pricier.

Basically, individuals will only stay at the current massive discount. Corporations that are paying token costs right now are dialing back as they realize it's not worth the expense.

We are going to have an AI crash, and the only thing left are going to be the efficient on-device or local models, which are already starting to bridge the gap.

It's even more hilarious because all along there has been this complaint, and then people have been like "no no who cares, features are important, dev time is important, just ship ship ship". And now memory is unaffordable and it takes 1GB RAM to display a plaintext file

The cost of producing memory IS low, and is continuing to fall.

It makes zero sense to rebase your mental model of the tradeoff between RAM versus developer time because of a temporary shortage.

In a few years time you’ll look silly for having wasted developer time on lowering BF memory consumption, while your built new features and waited for supply and demand to rebalance.

Sure, and in the meantime, we become less efficient at doing legitimately useful tasks and more efficient at making rent seeking slop that collects money for the upper classes. The real fix is get rid of the 90% slop tech and put that to better use (including more efficient use of hardware)

Or it’ll accelerate the push to the cloud even more making the client even thinner.

it isnt free but its easier to get 99.999% of the time usage out of it, vs having the client only sometimes have their machine on

Easier to monetize though ;)

it's cheaper considering they buy in bulk and can expense it against their taxes

1. Make shit inefficient software for basic tasks

2. Say it's infeasible to have enough compute locally to do basic tasks

3. Force usage of centrally controlled, subscription-based cloud software.

4. Capitalism win???!

I think this is legitimately (at least part of) the motivation for cornering the supply and driving up the price.

> It is the gradual end of general purpose computing you own, and the start of everything just being cloud compute that someone else owns and you rent.

A few thoughts...

(a) There've never been more general purpose computers than there are right now. Spec progress may stall for consumer products due to the price increases, but the demand for workstations is not going to go down that much; they're critical items to get work done. Many are hoping this means a return to memory efficiency; the 8GB Macbook Neo is a good sign that this is something Apple believes to some extent also.

(b) We've arguably been doing this since the 90s. A website (especially in the days of the heavy backend and more passive client) is cloud compute that someone else owns. You rent it by paying them in the form of looking at ads...

(c) There are a lot of companies and people working on making sure you have every chance to run your AI locally. It's surprisingly good now and keeps getting better. At some point we'll see the same oscillation that we always do from thin client to fat client as the latency advantage of working at the edge starts to win out. How long until I have a laptop with a Talaas chip in it running a basic local model at 16000 tok/sec that is just good enough to use A2A to reach a more powerful agent running elsewhere if I need it?

I agree with the sentiment, but there is a devils' advocate argument:

Most compute loads are bursty. Most PCs and phones sit idle almost all the time. It's an inefficient use of capital. In the cloud you can be idle and then suddenly command 1000X more power than any affordable PC could ever have... for 10 seconds... then be idle again. Those kinds of work loads aren't possible to realize on a PC without massively overbuying hardware.

I'd like to see more research on secure private cloud computing. Homomorphic encryption has gotten better but is still very slow, but there's other approaches that can help quite a bit but don't require much of a performance hit. Look into secure multiparty computation, reversible anonymization, etc.

I don't think personal computing will die, but I think it'll go back to being a hobbyist and pro thing like it was from its birth in the 1970s up until the middle 1990s. In the 1980s the average person did not own a computer, or if they did it was just to play some games. The average person was not loading BASIC programs off bootleg tapes and calling BBSes.

BTW I've been thinking a lot lately about how AI could save personal computing by allowing us to create an off-ramp from the present rats nest of complexity to something saner and simpler. Just thoughts right now but it's interesting.

Sure, scale of cloud systems has some interesting properties, that can be sometimes beneficial.

At the same time you are at the mercy of whoever runs the cloud, they can spy on your data or even manipulate your workloads, they can renegotiate the terms of use at any time - including price hikes or booting your from their cloud at any time.

Generative AI is definitely creating political will for simpler, more purposely-designed computer systems, but it's certainly not going to directly create help them in any meaningful way. AI-generated codebases are the posterchild of rat's nests of complexity.

I'd say the code I see coming out of leading models today is okay. Not great, but not terrible. It's also easy to get LLMs to code in more efficient languages, and you can also goad them via prompts and CLAUDE.md type stuff into prioritizing performance and simplicity.

It's sort of like what I say about self driving cars. Are they better than good human drivers? Not yet. Are they better than bad, drunk, or texting drivers? Yes.

LLMs are already better than bad coders and honestly most coders are bad coders.

In a world where we no longer have the rat's nest of complexity, we pretty much no longer need to produce code. All the software we will ever need for the next century could fit on books in one, single-floor library, if we exclude art projects like video games. An operating system with full driver support for every I/O peripheral (if those devices use standard protocols, allowing for a https://xkcd.com/927/ constant of 5), and support for every standard document format (again, assuming 5 bitmap image formats, 5 vector image formats, 5 kinds of print-ready document, 5 kinds of hypertext document…), could easily fit in 2GiB, and that would be done: everything anyone could possibly need out of a computer, apart from art, mathematics and science, for… I don't even know how long. We're still using the Latin alphabet, more or less unchanged since the late 15th century. Working technology doesn't need to change.

Being able to automatically generate large quantities of code that is worse than a good human programmer can produce is not helpful in this world you're envisioning.

You might be a fan of kelvin versioning: https://wiki.xxiivv.com/site/kelvin_versioning.html

It's interesting to note that the total compute forecast to be deployed in 2026-2027 is more than the amount that has been deployed during human history.

Nobody cares what Claude said. Why not tell us what you think?

A hard hit on Google Chrome users for sure!

All browsers are memory hogs.

It's the price you pay for having an application delivery platform that also needs to be hugely sandboxed running one of the most difficult languages to run efficiently in such large amounts as so the plaintext minified versions are a dozen megabytes in size.

I don't envy browsers even slightly, peoples expectations of them are ludicrous.

The major problem is that nobody is genuinely looking at using more efficient languages, lessening the amount of required inefficient language use or gasp producing native applications. (which, is definitely an order of magnitude harder to produce, I'll grant).

They don't have to become self conscious to want to write more memory efficient software or grow.

Running slack just once will do it.

When even the large AI labs that supposedly sit on (/with) the best of the best can't even ship native cross-platform desktop applications and instead ship some bloated Electron monsters, I'm not sure what kind of hope there is. The ones who were publishing lightweight apps continue to do so, the ones who didn't care, still don't care.

writing native gui code is atrocious, add to that llms being horrible with ui dev and you end up with with what you describe. but at least if we get more non-ui stuff written in more efficient languages there is going to be some benefit.

> writing native gui code is atrocious

Compared to what though? It's not nearly as horrible as it used to be, and you can do it fairly neatly today, and end up with something much better. Requires you to actually have skill and knowledge about there being other alternatives to Electron though, which seems like knowledge hard to come by these days.