Katie Porter??

I’m pretty sure anyone who visits to see family or similar is considered tourist, because they’d have a tourism visa. So the real percentage of I guess discretionary tourism is probably down much more than 5.5%.

The market can remain irrational longer than you can remain solvent.

A guild wars 2 to guild wars, if you will. Both still active.

I think they meant on these neo competitors, you could install Linux, which they thinks is better than macOS.

I have a MacBook Pro and agree. I just wish I could get iMessage on Linux for my family that can’t / won’t change to signal or similar.

There are anaerobes that reduce perchlorates (dissimilatory perchlorate reduction). Lack of moisture is a problem, but there will be some supplied by this sweet potato or whatever we’ve deposited on the planet. If we deposited it somewhere where ice was, there probably exists a region of habitability for a long enough period to induce the potential for microbial adaptation in a certain time frame.

It is hostile to life, but microbes would absolutely have a much better chance of growing there than humans, especially spore formers that could endure cyclic periods of high radiation and lack of water, followed by a very brief almost sublimating thaw, followed by freezing temperatures. That’s just if we didn’t provide more seeding material or more hospitable subterranean environs.

There is a significant (not meaning magnitude, meaning statistically reasonably) non zero chance that microbes are actively already living on the planet, not necessarily introduced by us but very possibly. Microbes have extremophiles in their ranks. Life finds a way.

Sort of. Anaerobes with co2 fixing pathways could very conceivably live and grow on Mars. They would grow slowly, but still orders of magnitude faster than human timescales. There’s also significantly more radiation on mars, so you’ll accumulate more mutations quicker. Time was ill defined here, but you could easily pick up adaptive mutations in as little as hours for fast growing earth based bacteria (because they have a new generation literally every 20 minutes). This would obviously be slower on mars with anaerobes (probably) but the speed at which microbes accumulate adaptive mutations could reasonably be described as “not long” and not at all be in the realm of marvel.

Currently, due to recent litigation, importers and companies are able to request tariff refunds. So if you paid a tariff directly, then you can request a refund and the government is required to pay you back. This is already decided and there is a refund request website.

Current lawsuits like this one are saying that Amazon requested the refund because they have the tariff receipt, and they’ll get the refund. Folks are suing Amazon because while they have the receipt, they passed on the charge, meaning they didn’t really pay the tariff in actuality. So they’re arguing that if the tariffs are illegal (already decided), and that tariff refunds are being sent out (already decided), then companies should also be required to refund their customers for the increased costs they passed along (lawsuits like this one).

It’s common sense. If a company charged 10 dollars for a product before the tariffs, charged 15 after the tariffs because it cost them 5 dollars in tariffs, then they still made the same profit after the consumer bought the product, and the consumer paid the tariff. So when a refund goes out, companies should have to return that tariff charge to the consumer. They’ll literally make the same profit and the consumer will be reimbursed then for the tariff charge they paid. This is the precedent we want to set, because otherwise consumers get screwed both ways while large companies get to pocket tariff costs. This is class warfare; working class and small business owners are losing.

I think we’re in the “how long for Taiwan to develop a nuke” waiting room right now.

A data center that will employ like 100 people and destroy their local air quality (probably), blast tons of light at night (definitely) and otherwise destroy the local ecology.

They really want to put us on hardware as a service. Eventually you won’t be able to buy hardware, digital ownership will be eroded, and you’ll pay more for it than if we’d kept the hardware market alive. Better to just cut the cord now and if it doesn’t run on your old pc just don’t run it. Don’t pay for streaming services.

If a company adds a tariff charge to its bill when a consumer pays, or it can be shown that they passed along a charge by raising the price by the tariff amount or similar, then it is clear the consumer paid. The party paying the tariff is the consumer. Suing for a refund sets precedent, and how the current round of tariffs were deemed illegal in the first place.

I guarantee they’re already navigating an AI hellscape. The problem are not insurance workers or working class wage workers, it is the system that is designed in such a way that instead of these folks facilitating actual care, which would be good and right (let’s catch fraud and such, and also make sure we have efficient claims services even with single payer so that treatment is even more cost effective). Better we have solidarity and convince the workers of these companies that they could still have jobs in public sector with equal pay and better benefits with a single payer system.

There are vanishingly few people getting mega wealthy off of insurance in the US. It’s not the wage workers. It’s the wealthy class siphoning our money and stealing while we die from preventable diseases.

Thanks for sharing this, though I still can’t get this to properly work (errors with bad vulkan layer / some swap chain error). I’ve installed gamescope with 25.08 and mango is also 25.08. Used proton up qt to install proton ge 10.34. Alas, until 64 bit comes out I prefer steam flat pak but it’s a little sad not to have hdr.

Traditional software was developed by humans as an artifact that, and to the degree that humans improved the software for some task, got better, but it was not guaranteed. Windows 11 is proof of that, and there are a laundry list of regressions and bugs introduced into software developed by humans. I acknowledge you say usually and especially for open source — I lukewarm agree with that statement but disagree that large LLMs or other generative models will follow this trend, and merely want to point out that software usually introduces bugs as it’s developed, which are hopefully fixed by people who can reason over the code.

Which brings us to AI models, and really they should just be called transformer models; they are statistical tensor product machines. They are not software in a traditional sense. They are trained to match their training input in a statistical sense. If the input data is corrupted, the model will actually get worse over time, not better. If the data is biased, it will get worse over time, not better. With the amount of slop generated on the web, it is extraordinarily hard to denoise and decide what’s good data and what’s bad data that shouldn’t be used for training. Which means the scaling we’ve seen with increased data will not necessarily hold. And there’s not a clear indication that scaling the model size, which is largely already impractical, is having some synergistic or emergent effect as hoped and hyped.

Also, we’re really not in the infancy of AI. Maybe the infancy of widespread hype for it, but the idea of using tensor products for statistical learning algorithms goes back at least as far as Smolensky, maybe before, and that was what, 1990?

We are in the infancy of I’d say quantum style compute, so we really don’t have much to draw on beyond theoretical models.

Generative LLM models have largely plateaued in my opinion.

In my experience it is obvious. Calling people on it also makes them feel embarrassed usually. I put something like “I can just ask an LLM myself if I wanted this output. Please provide your own commentary.” If I were a manager and I had an employee just copy pasting that kind of output, I’d probably wonder if that employee actually contributes anything.

I think this is the way. A certain number of times of “[coworker] wasn’t asked because they only respond with LLMs, so I just ask the LLMs directly. I am not sure what [coworker]’s expertise is anymore, I just don’t consult them” and I suspect coworker may in fact stop responding with LLMs.

I’m locked in to apples ecosystem for various reasons, but I’ll be buying this as a second phone hands down to try and wean me also convince family on switch over. Goes well with my self hosting.

There’s probably is a path to female only reproduction using artificial means. I suppose it would be possible with men too, if we could synthetically gestate a child, but it’s probably easier in women since they possess the evolved ability to gestate. Parthenogenesis has occurred in other organisms, possible perhaps for humans too, with help.

This already happens intrinsically in the models. The tokens are abstracted in the internal layers and only translated in the output layer back to next token prediction. Training visual models is slightly different because you’re not outputting tokens but pixel values (or possibly bounding boxes or edges, but not usually; conversely if not generative you may be predicting labels which could theoretically be in token space).

The field itself is actually fairly stagnant in architecture. It’s still just attention layers all the way down. It’s just adding more context length and more layers and wider layers while training on more data. I personally think this approach will never achieve AGI or anything like it. It will get better at perfectly reciting its training data, but I don’t expect truly emergent phenomena to occur with these architectures just because they’re very big. They’ll be decent chatbots, but we already have that, and they’ll just consumer ever more resources for vanishingly small improvements (and won’t functionally improve any true logical capability beyond regurgitating logical paths already trodden in their training data but in a very brittle way, because they do not actually understand the logic or why the logic is valid, they have no true state model of objects which are described in the token space they’re traversing probabilistically).