In the footnotes they mention GPT-3.5. Their argument for not testing 4 was because it was paid, and so most users would be using 3.5 - which is already factually incorrect now because the new GPT-4o (which they don’t even mention) is now free. Finally, they didn’t mention GPT-4 Turbo either, which is even better at coding compared to 4.
I’ve heard of Intel Arc users for instance not able to play certain games because it checks for AMD/nVidia, so you’d have to fake the GPU vendor to get it to work.
Eg see stuff like this: https://www.phoronix.com/news/Intel-Graphics-Hogwarts-Legacy
Or https://www.phoronix.com/news/The-Finals-Intel-Arc-Graphics
Before y’all get excited, the press release doesn’t actually mention the term “open source” anywhere.
Winamp will open up its code for the player used on Windows, enabling the entire community to participate in its development. This is an invitation to global collaboration, where developers worldwide can contribute their expertise, ideas, and passion to help this iconic software evolve.
This, to me, reads like it’s going to be a “source available” model, perhaps released under some sort of a Contributor License Agreement (CLA). So, best to hold off any celebrations until we see the actual license.
You cannot go back after trying it
I did! Used to have a Samsung 49" ultrawide. After using it for a couple of years, I sold it and got a 16:10 32" QHD, which I found worked better for me (+ one or two laptop screens for chat / random stuff when I’m doing serious work).
The biggest issue I had with the ultrawide is that most of the games that I played weren’t optimised for it, especially in some games where things like the mini-map might be at the far end of the screen, or worse, if it was an older game then you’d have to put up with black bars, or play the game in windowed mode.
You can already run Linux apps using Termux and Termux-X11, and I’d say the performance would be better than this demo, because this is running in a virtual machine and uses it’s own kernel, whereas with Termux you’re running your apps directly on top of the Android Linux kernel. Also, you don’t have the overhead of running ChromeOS on top of Android.
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Because MIUI deviates from stock Android so much that it often causes unexpected behaviour and bugs. So it’s easier for developers to just say they don’t support it, instead of putting up with negative reviews and complaints.
This is a general tech community, mostly centered around news and end-user technology discussions, so it’s very unlikely you’ll get an answer here. Might want to try asking on Reddit or some dedicated Datto/Connectwise forum.
Nice, great to see the continued development of an old-school, lightweight browser. We need more active alternatives to the bloated duopoly.
Check out bamboo pillows and pillow cases, they have natural hypoallergenic properties and it might suit you better. Or you could just get a bamboo pillow protector + pillow case, in case you don’t want to change your whole pillow out.
Since you’re on Linux, it’s just a matter of installing the right packages from your distros package manager. Lots of articles on the Web, just google your app + “ROCm”. Main thing you gotta keep in mind is the version dependencies, since ROCm 6.0/6.1 was released recently, some programs may not yet have been updated for it. So if your distro packages the most recent version, your app might not yet support it.
This is why many ML apps also come as a Docker image with specific versions of libraries bundled with them - so that could be an easier option for you, instead of manually hunting around for various package dependencies.
Also, chances are that your app may not even know/care about ROCm, if it just uses a library like PyTorch / TensorFlow etc. So just check it’s requirements first.
As for AMD vs nVidia in general, there are a few places mainly where they lagged behind: RTX, compute and super sampling.
For RTX, there has been improvements in performance with the RDNA3 cards, but it does lag behind by a generation. For instance, the latest 7900 XTX’s RTX performance is equivalent to the 3080.
Compute is catching up as I mentioned earlier, and in some cases the performance may even match nVidia. This is very application/library specific though, so you’ll need to look it up.
Super Sampling is a bit of a weird one. AMD has FSR and it does a good job in general. In some cases, it may even perform better since it uses much simpler calculations, as opposed to nVidia’s deep learning technique. And AMD’s FSR method can be used with any card in fact, as long as the game supports it. And therein lies the catch, only something like 1/3rd of the games out there support it, and even fewer games support the latest FSR 3. But there are mods out there which can enable FSR (check Nexus Mods) that you might be able to use. In any case, FSR/DLSS isn’t a critical thing, unless you’re gaming on a 4K+ monitor.
You can check out Tom’s Hardware GPU Hierarchy for the exact numbers - scroll down halfway to read about the RTX and FSR situation.
So yes, AMD does lag behind in nVidia but whether this impacts you really depends on your needs and use cases. If you’re a Linux user though, getting an AMD is a no-brainer - it just works so much better, as in, no need to deal with proprietary driver headaches, no update woes, excellent Wayland support etc.
I based my statements on the actual commits being made to the repo, from what I can see it’s certainly not “floundering”:
In any case, ZLUDA is really just a stop-gap arrangement so I don’t see it being an issue either way - with more and more projects supporting AMD cards, it won’t be needed at all in the near future.
It’s not “optimistic”, it’s actually happening. Don’t forget that GPU compute is a pretty vast field, and not every field/application has a hard-coded dependency on CUDA/nVidia.
For instance, both TensorFlow and PyTorch work fine with ROCm 6.0+ now, and this enables a lot of ML tasks such as running LLMs like Llama2. Stable Diffusion also works fine - I’ve tested 2.1 a while back and performance has been great on my Arch + 7800 XT setup. There’s plenty more such examples where AMD is already a viable option. And don’t forget ZLUDA too, which is being continuing to be improved.
I mean, look at this benchmark from Feb, that’s not bad at all:
And ZLUDA has had many improvements since then, so this will only get better.
Of course, whether all this makes an actual dent in nVidia compute market share is a completely different story (thanks to enterprise $$$ + existing hw that’s already out there), but the point is, at least for many people/projects - ROCm is already a viable alternative to CUDA for many scenarios. And this will only improve with time. Just within the last 6 months for instance there have been VAST improvements in both ROCm (like the 6.0 release) and compatibility with major projects (like PyTorch). 6.1 was released only a few weeks ago with improved SD performance, a new video decode component (rocDecode), much faster matrix calculations with the new EigenSolver etc. It’s a very exiting space to be in to be honest.
So you’d have to be blind to not notice these rapid changes that’s really happening. And yes, right now it’s still very, very early days for AMD and they’ve got a lot of catching up to do, and there’s a lot of scope for improvement too. But it’s happening for sure, AMD + the community isn’t sitting idle.
The best option is to just support the developer/project by the method they prefer the most (ko-fi/patreon/crypto/beer/t-shirts etc).
If the project doesn’t accept any donations but accepts code contributions instead (or you want to develop something that doesn’t exist), you can directly hire a freelancer to work on what you want, from sites like freelancer.com.
Pretty much the same as you, but I do yoga instead of qigong. Plus I focus a lot on diet and nutrition and try to make sure I’m getting everything I need, whilst trying to minimise or avoid things that are bad for you, like processed foods, sugary stuff etc. Bought a Garmin smartwatch and smart scales last year to keep a track of my exercise goals, hydration, HRV, and sleep quality, and that’s been real helpful in keeping track of my health.
Also planning to take up some basic martial arts as well; I was looking at kyokushin, but might pick wing chun due to it’s practicality / self-defence aspects.
Bonus question: Where else can I post questions besides Ask Lemmy?
You can also post questions on Ask Lemmy’s evil twin - [email protected]
I personally use a ThinkPad Z13 (all AMD; it’s nice but pricey), but I’d recommend getting a Framework (which wasn’t an option for me back then). I think modular and repairable laptops are cool, plus they seem to be well supported by the Linux community.
Samsung midrangers like the A15 / M15 / A25 etc have both the jack as well as an sdcard slot. There’s also the Motorola G34 and the G84. And finally, there’s also a flagship - the ASUS ROG Phone 8 Pro. And a whole bunch of Chinese phones which I won’t bother mentioning.
Considering that predicting the next word from context is the one thing LLMs are really good at, I just don’t understand how none of these developments have found their way into predictive keyboards.
The problem is that LLMs require a considerable amount of computing power to run, unlike the simple markov chain predictions that keyboards use. You could use a cloud-based service like ChatGPT or something, but most people wouldn’t want their keyboards to send all their keystrokes to a remote server… and even if they didn’t know or care, the response time wouldn’t be good enough for real-time predictions.
Now smartphone SoC makers like Qualcomm have started adding NPUs (neural processing units) with their latest chips (such as the SD8 Gen 3, featured in the most recent flagship phones), but it’s going to take a while before devices with NPUs become commonplace, and it’ll take a while for developers to start making/updating apps that can make use of it.
But yeah the good news is that it is coming, it’s only a matter of “when” - I suspect it won’t be long before the likes of SwiftKey start to take advantage of this.
You might be interested in these things called mouse jigglers, they range from a tiny USB dongle that simulates a mouse, to motorised movement pads that you can place under a real mouse, which would be undetectable by software.
PS: You’re welcome. ;)
Serenity for sure. I love the 90s aesthetic and would like to see it make a comeback. At the very least I’d like to see their Ladybird browser become mainstream - we really need more alternatives to the Chromium family.