He didn't say he bets everything against ASI, he said he bets everything against ASI being a flash of light in the sky which destroys our chance of getting access to the wealth it creates.
> Local ISP: “We’ll be happy to run fiber and new ethernet through your existing network conduits, trench to the curb, and help bodge in active poe ethernet repeaters for runs that are too long.”
I live in a major metro with a half a dozen apartments constructed within a block of me while I've lived here and this is very much not the case. I call them, they say they'll be happy too and then they ghost me. Of course I also can't get Starlink.
They're looking at national politics, and on that score, yes, the ST is liberal. When it comes to local politics the Seattle Times is conservative. Your objection is a bit like people who object that the Democrats are conservatives, from a European perspective, except this is about the city itself. The current mayor is liberal, the previous mayor was conservative. They're both Democrats and would be defined as liberals by your factcheck, but that's a different rubric than the one we're talking about.
At the core this is a hardware problem. 1M tokens is simply not enough context to understand a codebase the way a human would understand it. Being able to selectively forget is potentially a very valuable power, but right now it's a substitute for a human's ability to remember the rough shape of something, decide it's uninteresting, and remember that it is uninteresting.
They talk about memory only being useful when guided by a human, I think the proper solution is deeper than that, it probably involves feeding the entire codebase and every agent session into a finetuning of the model, though at that point you might want some guidance to avoid feeding certain sessions into the model. Or maybe not, maybe the bitter lesson applies.
The Apple Vision Pro. I really wish Valve would release a $3500 Steam Frame with all the bells and whistles. Of course, with the price of RAM it might be $7000 so maybe I'll just have to wait until hopefully the market cools down a bit and baseline hardware advances some more.
Fable happened to be released after I had been experimenting with Claude Code for roughly two weeks. I had been trying to use Sonnet, and when I switched to Opus it was night and day. My understanding of geometry was maybe not as good as it should've been, and I kept seeing Sonnet say things I knew were wrong but didn't know enough about 6DOF camera positioning to ask it to fix. I finally asked the right questions, it couldn't answer them at all, I switched to Opus, it was night and day. But! Opus still couldn't really keep 6DOF "in its head." When I left it to its own devices it tended to come back having forgotten that it needed to keep 6 degrees of freedom in its head and collapsed the problem down to 3DOF or just a single angle.
Fable just understood what I was talking about and never needed me to stop it and say "you forgot this thing we talked about." The difference in spatial reasoning capability between the three models is very very palpable. I am curious to get more time with it because ultimately I feel like I sandbagged it by giving it problems that would've been within Opus' abilities, but required a lot more handholding.
what is the known-good thing? The whole point is that LLMs were not optimized at all, they got better results than older ML algorithms just because they are able to use all of the GPU, where older algorithms are designed for 10yo GPUs and can't make use of modern GPUs. But now you do in fact have to optimize, to the point that transformers look a lot more complicated than "attention is all you need."
Really? Here are 3 examples, I'm not sure what you mean, Congress has extremely broad taxing authority. If what I suggest is unconstitutional (I'm curious to hear your justification for that) they could probably do it by putting terms of use on the PACER data, have a paid tier specifically for orgs that resell the data.
You asserted that we need the money PACER fees bring in - taxing businesses like LexisNexis seems like a way to get the same kind of money that wouldn't be regressive, if we really need to replace that revenue, and it comes from more or less the same place, without being paid by people who can't afford it.
We know where all the money in this system is: it's in LexisNexis and Westlaw. Each of them has revenue over $3B, individually. Presumably they have some lesser-known competitors. PACER fees are $150M. What percentage of PACER fees are paid by LexisNexis and Westlaw anyway in the course of their data ingestion? I'm not sure it really matters, we could simply restructure with a new tax on value-add services like LexisNexis that pulls in $200M, make PACER free, and everyone would be happier, probably including the value-add legal service providers.
What's a "basic machine learning system?" is this a question of the size of the model or the algorithm? Which algorithms are basic? If you've got an ensemble of models that includes multiple transformers not all of which are LLMs as well as CNNs, how do you think the marketing people should express that?
The R&D expenditure seems reasonable, and the revenue numbers seem realistic. I have no trouble believing they can be profitable by 2030 or much sooner. What I don't get is how you get from $30B in revenue to a nearly $1T valuation, but that seems almost level-headed compared to SpaceX, and it's not like any of the big tech companies' valuations make much sense in the context of their revenue.
The OS shouldn't be making many big changes that force me to reorient. When I'm moving between different UIs I often want to compare them; animations make it harder to compare state A to state B. I can detect very fine differences between two images by switching between them within a second, if there's a 1-second animation it not only means it's going to add a second, it adds a bunch of visual noise which might make it impossible to be able to distinguish what's an actual difference and what's just noise introduced by the animation.
> Approximately nobody is throwing away phones because the OEM stopped providing security patches.
This becomes a practical reason more quickly than you think. If a company only provides 4 years of security updates and they only provide 2 android MV releases, you quickly become out of date. I had a BlackBerry Key2 that I bought in 2018, I had to replace it in 2024 and I was really holding onto it despite a lot of practical problems - Slack dropped support for the version of Android a year earlier, it was only when I tried to install Google Wallet and could not that I finally decided despite the hardware and software functioning fine it really wasn't practical to use a device that was stuck on such an old version of Android. (I would've tried to figure out the kernel myself if the bootloader wasn't locked.)
I have mixed feelings about Kindle, but I mostly read books on my phone these days, and my Kindle library is always there. I also have a physical bookshelf, but if I'm not home I can't review it so in some ways it's often less tangible than my Kindle library which I always carry with me.
Binaries are source code outputs, they are copyrightable and patentable. Weights are not copyrightable so people can freely extract the weights and run them. If Google patents any of the novel algorithms here releasing it all freely isn't an impediment to making people license it.
The flicker/signin redirects are a regression introduced post-Github acquisition. Really just evidence of the product being abandoned, or possibly of general operational decline at Microsoft which is affecting all their products. Definitely since the acquisition, both products have declined but Github has declined more to the point where I might prefer Azure DevOps.
http://www.flinchbaughschlather.com/luke
mail:
luke 'preposition' schlather.info