Again, I am really wanting to see this EU case you reference, because this is an issue I have been reading up on. Do you have a reference for me?
Again, I am really wanting to see this EU case you reference, because this is an issue I have been reading up on. Do you have a reference for me?
The points linked above allege Valve will delist a game from their platform if the price is lower off-platform (even for non-key sales), correct?
This is called a “Platform Most Favored Nation” clause, and it has anti-competitive effects. It is controlling the price off-platform using the leverage of market share to coerce behaviors out of publishers.
Please also link me this European court case, I have been unable to locate it myself.
It’s an ongoing case, so I don’t know what you expect of me here. My reply was to correct your misunderstanding about the focus of the case, which is not limited to the use of steam keys as you originally claimed.
I am not aware of the european case you reference, would you mind pointing me to where I can learn more?
If that is demonstrably true, I’d like to see the demonstration. In fact, the case alleges the policy extends to non-key sales (see pts 204, 205, 207, 208).
I like Wolfire. Their head (David Rosen) had a really good procedural animation talk at GDC about a decade ago, their games are pretty good, and they started up Humble before it spun off on its own.
Before tarnishing their reputation, I’d suggest reading up on the actual complaints put forth in the lawsuit. I’ve done so extensively, I think they have very solid grounds to go after Valve (Valve’s behaviour is comparable to Amazon’s in terms of anticompetitive practices).
I’m curious what issue you see with that? It seems like the project is only accepting unrestricted donations, but is there something suspicious about shopify that makes it’s involvement concerning (I don’t know much about them)?
It’s only double counted in a situation where you’re actually counting both sides. This is a Canadian study published by a Canadian outlet about the impacts of Canadian policy.
They’re not trying to balance the books, so to speak, they’re evaluating transactions on a single account.
404media is doing excellent work on tracking the non-consentual porn market and technology. Unfortunately, you don’t really see the larger, more mainstream outlets giving it the same attention beyond its effect on Taylor Swift.
Right concept, except you’re off in scale. A MULT instruction would exist in both RISC and CISC processors.
The big difference is that CISC tries to provide instructions to perform much more sophisticated subroutines. This video is a fun look at some of the most absurd ones, to give you an idea.
Huh, thanks for the heads up. Section 4 makes it look like they can close-source whenever they want.
I’m just glad FUTO is still letting Immich use the AGPL instead of this, though.
There is an episode of Tech Won’t Save Us (2024-01-25) discussing how weird the podcasting play was for Spotify. There is essentially no way to monetize podcasts at scale, primarily because podcasts do not have the same degree of platform look-in as other media types.
Spotify spent the $100 million (or whatever the number was) to get Rogan exclusive, but for essentially every other podcast you can find a free RSS feed with skippable ads. Also their podcast player just outright sucks :/
Errrrm… No. Don’t get your philosophy from LessWrong.
Here’s the part of the LessWrong page that cites Simulacra and Simulation:
Like “agent”, “simulation” is a generic term referring to a deep and inevitable idea: that what we think of as the real can be run virtually on machines, “produced from miniaturized units, from matrices, memory banks and command models - and with these it can be reproduced an indefinite number of times.”
This last quote does indeed come from Simulacra (you can find it in the third paragraph here), but it appears to have been quoted solely because when paired with the definition of simulation put forward by the article:
A simulation is the imitation of the operation of a real-world process or system over time.
it appears that Baudrillard supports the idea that a computer can just simulate any goddamn thing we want it to.
If you are familiar with the actual arguments Baudrillard makes, or simply read the context around that quote, it is obvious that this is misappropriating the text.
The reason the article compares to commercial flights is your everyday reader knows planes’ emissions are large. It’s a reference point so people can weight the ecological tradeoff.
“I can emit this much by either (1) operating the global airline network, or (2) running cloud/LLMs.” It’s a good way to visualize the cost of cloud systems without just citing tons-of-CO2/yr.
Downplaying that by insisting we look at the transportation industry as a whole doesn’t strike you as… a little silly? We know transport is expensive; It is moving tons of mass over hundreds of miles. The fact computer systems even get close is an indication of the sheer scale of energy being poured into them.
concepts embedded in them
internal model
You used both phrases in this thread, but those are two very different things. It’s a stretch to say this research supports the latter.
Yes, LLMs are still next-token generators. That is a descriptive statement about how they operate. They just have embedded knowledge that allows them to generate sometimes meaningful text.
It’s not really stupid at all. See the matrix code example from this article: https://spectrum.ieee.org/ai-code-generation-ownership
You can’t really know when the genAI is synthesizing from thousands of inputs or just outright reciting copyrighted code. Not kosher if it’s the latter.
I get that there are better choices now, but let’s not pretend like a straw you blow into is the technological stopping point for limb-free computer control (sorry if that’s not actually the best option, it’s just the one I’m familiar with). There are plenty of things to trash talk Neuralink about without pretending this technology (or it’s future form) is meritless.
The issue on the copyright front is the same kind of professional standards and professional ethics that should stop you from just outright copying open-source code into your application. It may be very small portions of code, and you may never get caught, but you simply don’t do that. If you wouldn’t steal a function from a copyleft open-source project, you wouldn’t use that function when copilot suggests it. Idk if copilot has added license tracing yet (been a while since I used it), but absent that feature you are entirely blind to the extent which it’s output is infringing on licenses. That’s huge legal liability to your employer, and an ethical coinflip.
Regarding understanding of code, you’re right. You have to own what you submit into the codebase.
The drawback/risks of using LLMs or copilot are more to do with the fact it generates the likely code, which means it’s statistically biased to generate whatever common and unnoticeable bugged logic exists in the average github repo it trained on. It will at some point give you code you read and say “yep, looks right to me” and then actually has a subtle buffer overflow issue, or actually fails in an edge case, because in a way that is just unnoticeable enough.
And you can make the argument that it’s your responsibility to find that (it is). But I’ve seen some examples thrown around on twitter of just slightly bugged loops; I’ve seen examples of it replicated known vulnerabilities; and we have that package name fiasco in the that first article above.
If I ask myself would I definitely have caught that? the answer is only a maybe. If it replicates a vulnerability that existed in open-source code for years before it was noticed, do you really trust yourself to identify that the moment copilot suggests it to you?
I guess it all depends on stakes too. If you’re generating buggy JavaScript who cares.
We should already be at that point. We have already seen LLMs’ potential to inadvertently backdoor your code and to inadvertently help you violate copyright law (I guess we do need to wait to see what the courts rule, but I’ll be rooting for the open-source authors).
If you use LLMs in your professional work, you’re crazy. I would never be comfortably opening myself up to the legal and security liabilities of AI tools.
That’s significantly worse privacy-wise, since Google gets a copy of everything.
A recovery email in this case was used to uncover the identity of the account-holder. Unless you’re using proton mail anonymously (if you’re replacing your personal gmail, then probably not) then you don’t need to consider the recover email as a weakness.
As the article points out, TSA is using this tech to improve efficiency. Every request for manual verification breaks their flow, requires an agent to come address you, and eats more time. At the very least, you ought not to scan in the hopes that TSA metrics look poor enough they decide this tech isn’t practical to use.