If you read carefully this is actually very similar to the Steam news. I doubt Valve or GOG care, but generally the games are “sold” by the publisher as non transferable licenses for you to play them. So the part that matters isn’t up to them.
Have you tried recent models? They’re not perfect no, but they can usually get you most of the way there if not all the way. If you know how to structure the problem and prompt, granted.
Them using Google indexes anonymously isn’t intending to solve the problem you think it is. It’s more about incentive structures. Google’s “free” search optimizes for ad revenue now. The API access doesn’t as much, and Kagi certainly doesn’t have an ad incentive. So privacy is a nice bonus, but the real benefit is a customer serving incentive structure.
Wonder how we should interpret the country “XD” being on the list. As far as I can tell its never been used for any real country.
I use Kagi, they provide access to all the main models in a chat interface and have a mode that feeds search engine results to them. It’s mostly replaced search engines for me. For programming work I find them very useful for using unfamiliar tools and libraries, I can ask it what I want to so and it’ll generally tell me how correctly. Importantly, the search engine mode has citations. $25 a month, but worth it.
This must be pandering to shareholders, no company in their right mind would want to compete when Meta is selling their first party headset at a giant loss.
The idea that “it’s ok cause we’d do the same” is ridiculous. There is no comparison: China is an authoritarian government and the parent company is practically an arm of the state. There are legitimate criticisms of American tech companies obviously, but they’re ultimately subject to the market and democratic governments. We shouldn’t be doing any business with authoritarians in the first place, much less inviting them to control a significant social media app in the guise of a legitimate business.
It runs great now. Most importantly, it supports extensions like ublock.
So this is probably another example of Google using too blunt of instruments for AI. LLMs are very suggestible and leading questions can severely bias responses. Most people using them without knowing a lot about the field will ask “bad” questions. So it likely has instructions to avoid “which is better” and instead provide pros and cons for the user to consider themselves.
Edit: I don’t mean to excuse, just explain. If anything, the implication is that Google rushed it out after attempting to slap bandaids on serious problems. OpenAI and Anthropic, for example, have talked about how alignment training and human adjustment takes a majority of the development time. Since Google is in a self described emergency mode, cutting that process short seems a likely explanation.
If I’m understanding this right, and this basically an API that lets you pick which app store administers an app, that could be quite helpful, not harmful. I currently have fdroid, play store, and Samsung store, and I assume they try to update apps by the fully qualified name, as multiple stores show and try to update a single app instance, sometimes with weird results.
Compression is actually a mathematical field that’s fairly well explored, and this isn’t compression. There are theoretical limits on how much you can compress data, so the data is always somewhere, either in the dictionary or the input. Trained models like these are gigantic, so even if it was perfect recall the ratio still wouldn’t be good. Lossy “compression” is another issue entirely, more of an engineering problem of determining how much data you can throw out while making acceptable compromises.
This is a classic problem for machine learning systems, sometimes called over fitting or memorization. By analogy, it’s the difference between knowing how to do multiplication vs just memorizing the times tables. With enough training data and large enough storage AI can feign higher “intelligence”, and that is demonstrably what’s going on here. It’s a spectrum as well. In theory, nearly identical recall is undesirable, and there are known ways of shifting away from that end of the spectrum. Literal AI 101 content.
Edit: I don’t mean to say that machine learning as a technique has problems, I mean that implementations of machine learning can run into these problems. And no, I wouldn’t describe these as being intelligent any more than a chess algorithm is intelligent. They just have a much more broad problem space and the natural language processing leads us to anthropomorphize it.
Normal people don’t, but when you get into absolutely massive enterprise archiving there’s no rival for the density and cost effectiveness. It sucks for general purpose storage, but for write once, hopefully never read use, they’re ideal.
Architecture emulation for current gen games is exceptionally unlikely right now. At a fundamental level, wine/proton doesn’t change the instructions the code describes, rather it translates the input and output. It’s a reimplementation of the same instructions in Windows. For architecture crossing you’d either have to create virtual hardware, which adds tremendous overhead, or recompile the binary. Recompilation is theoretically possible, but for x86_64 to ARM64, for games no less, it’s beyond the realm of mortals. It’s like how some jokes can’t be translated between languages; the structure and vocabulary is just too different.
People complaining about the promotion of FOSS on a FOSS powered site. Lemmy amd Mastodon are a golden opportunity to get people onboard with FOSS, no shit they’re going to evangelize it. Not to mention the early adopters were obviously FOSS devs.
Well this is a tremendous step in the wrong direction. The economic problem is the ad supported model in the first place, no matter how it’s run. This is the same thing Google does, they keep user data to themselves and sell the ad placement. So now Mozilla has the same economic incentives as Google. Unfathomably bad move.