GamingChairModel

The economics of it don't add up and the growth rate of the curve of improvement over time has already significativelly fallen which looking at the historical curves for other technologies is a very strong indication that it's approaching the limits of how far it will go even though it's nowhere close to the hype.

Yeah, I'm convinced that they've maintained the illusion of continued exponential improvement from 2024-2026 by sneaking in exponential increase in resources (hardware complexity, power consumption), to prop things up past what should have been a plateau.

AI has an interesting economic trait in that it's very, very expensive to deploy, and made very fast progress from 2022 to 2024. That caused investors with money to believe that:

• Pushing the frontier was going to cost a lot of money. More than any other purported revolutionary tech.
• Extrapolation of past improvement meant that whoever was on the cutting edge may end up with a product with a huge paying market.
• So whoever wins this race would be rich, and the investment would have been worth it for them.

But since 2024, we've seen that the cutting edge got even more expensive much faster than expected, and much of the improvements in performance now come from inference rather than training, which represents a high ongoing cost.

Now, if we extrapolate from that trend line, we'll see that the market will be much smaller for AI services at the cost it takes to provide that service, and the question then becomes whether the industry can make its operations cheaper, fast enough to profitably provide a service people will pay for.

I have my doubts they'll succeed, and we might just be looking at the industry like supersonic flight: conceptually interesting, technically feasible, but just a commercial dead end because it's too expensive.

ActivityPub is the fediverse protocol, lemmy and piefed are software implementations of that protocol.

In a similar way, email is a protocol, and Gmail and Exchange/Outlook are software implementations of that protocol. You can use Gmail to send email to Outlook users. Different people can administer their own Exchange servers on their own domains.

And some features of the software work best with other people who use the same version of the same software, although most things kinda work between different software. Like how calendar invites sometimes act weird between users of different software, but for the most part the core functions work OK.

So lemmy and piefed (and mbin and sublinks and some others) are different software trying to speak to other fediverse services through the ActivityPub protocol. It mostly works, but some of the details don't work exactly the same between each type of software.

One real concern I have is that there are now automated tools that can read a patch, and the maintainer's release notes with a description of a security vulnerability fixed by that patch, and then create a working exploit of the pre-patch vulnerability.

In that particular moment, you know that a vulnerability exists and that it was serious enough to be described in release notes, and you can compare two code versions, one that is secure and one that is not. From there, any AI coding agent is working towards something that definitely exists, with a bunch of description of what it might be.

So that means that the window between when a patch is released and when users actually apply that patch is going to be more important than ever. Downstream maintainers will be under a lot of time pressure to implement changes from upstream, because every new security patch will create a race to create 1-day exploits for everyone using that software.

Don't they put plutonium reactors in space?

The ones that power spacecraft generate less than 5000W of heat at max power (while producing 300W of usable electricity).

In order to power a single server rack of 72 Blackwell GPUs, which takes about 130,000 watts, you'd need about 430 of those RTGs, and need to manage cooling requirements of 430 times as much (plus however much additional power will be required by the cooling system itself, too).

Companies are building entire workflows around AI, but they are building them under the assumption that they won't ever be charged per token.

Or worse, where the AI models underpinning a workflow breaks or degrades in some way to reduce token usage and then starts behaving in unexpected ways, in a process/workflow that assumes a particular type of behavior.

Counterpoint: sometimes the best still shot requires a particular moment captured with a particular, consciously arranged setup.

This interview of a veteran NBA photographer breaks it down of how he only has a single shot per shot because of how he necessarily relies on strobes set up to not distract the players or interfere with the broadcast. As a result, he scouts/studies each player and team so that he knows when the right moment is to actually capture the shot, because he can't exactly ask players to do it again.

If you read interviews of Pulitzer photography winners, they'll often say a lot of the same things: being prepared and being lucky and having that convergence of having incredibly high skill/expertise/understanding of the setting, while being able to capture in every opportunity presented.

You should capture a lot of photos and examine them to understand how to make them better, and increase your skill level and understand your subject so that you can still optimize for the very best shot possible.

Original reporting by Bloomberg is here or here for an archive.is version.

Sounds like the talks are stalled about revenue guarantees from the Kenyan government, if demand for the data center's capacity never shows up. The power infrastructure isn't really an issue yet, since the first phase is going to be 100MW and there are plans to build geothermal plants sufficient to cover several multiples of the country's current power usage, including whatever demand comes from this data center.

I used to carry around an 11" laptop when I had to give a bunch of presentations in unfamiliar conference rooms. It was the main reason why I switched to Apple around 15 years ago for my travel laptop (couldn't get Linux-friendly hardware with good battery life and seamless display/audio support over DVI/DP/HDMI and whatever audio setup they'd have for me) while still keeping a "main" Linux laptop for around the house and a headless server sitting next to my router.

I'd love to have that 11" form factor again, with modern thunderbolt/USB4 docking stations at my work desk, home office, and whatever desk I might hotel at or whatever. I rarely used the small screen or keyboard but it was nice to have that option on the move (like in an economy plane seat).

Five star rating system was dumb because almost every rating was 1 or 5 stars. It was right to replace with a thumbs up/thumbs down system.

That assumes that the only use for ratings is for averaging the aggregate votes across all users. Nope. Sometimes for a specific user they like to be able to see the granularity of their own ratings for their own use. And even if it is a public aggregated thing the rating service can still treat all 1-2 stars as downvotes and 4-5 stars as upvotes while it's easier to use the simpler algorithms, but to still store the more precise data for analyzing correlations at greater detail.

Big tech covered the world in trillion-parameter AI models and couldn't even figure out what to do with 5-star ratings differently from upvotes/downvotes? It's ridiculous.

Yeah if I were starting now I'd be looking at jellyfin. But I paid the lifetime plex pass, and inertia/laziness what it is, so I haven't found a reason to actually switch yet.

Transformers are like blockchain: an interesting use of mathematical principles to solve certain problems in a novel way, where the hype around that core attracts charlatans and scammers and combinations of the two traits who claim that it will go on to solve totally different problems in such a way as to revolutionize the world we live in.

NFTs were the end of that line for blockchain where the machine started to eat itself. I can see a future, stable use of blockchain in some limited contexts, but cryptobros have always overstated the contexts in which that particular type of digital ledger can be more useful than other types of digital ledgers.

We'll see where the end of the road is for transformers, and what's left at the end. I believe that computer inference will always be useful in some contexts, and that the advances in huge models with absurdly large numbers of parameters have unlocked some previously impractical tasks, but I could also see that settling into a general background existence as just another technological tool for doing things in a world that still looks pretty similar to the world today.