“for life” covers that eventuality :P

What about AV2 + Opus though!?

It’s a bit excessive for my taste as well. Traditionally if you felt the need to cut this much just to make the sentence come out the way you want, you’d just do another take instead of making this many cuts in post. Over-cutting of spacing also makes the pacing a bit too “word-vomit” rather than “polished” imo.

I imagine this is more normalized in stereotypically “zoomer” presentation of video content, but it might also just be this guy (or their editor’s) style.

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I actually think this video is doing a pretty bad job of summarizing the practical-comparison part of the paper.

If you go here you can get a GitHub link which in turn has a OneDrive link with a dataset of images and textures which they used. (This doesn’t include some of the images shown in the paper - not sure why and don’t really want to dig into it because spending an hour writing one comment as-is is already a suspicious use of my time.)

Using the example with an explicit file size mentioned in the video which I’ll re-encode with Paint.NET trying to match the ~160KB file size:

• Original PNG (5,725,123 bytes) https://files.catbox.moe/l2wsxr.png
• Optimized PNG (5,579,693 bytes) https://files.catbox.moe/2dh00n.png
• Lossless WebP (4,504,946 bytes) https://files.catbox.moe/hiephv.webp
• Lossy WebP; default preset, quality 13 (162,820 bytes) https://files.catbox.moe/jnv4tp.webp
• JPEG XL; quality 12, effort 7 (164,859 bytes) https://files.catbox.moe/fylcqa.jxl (your browser probably can’t view this image)
• AVIF; lossless alpha compression [shouldn’t matter], quality 44, very slow preset, 4:2:0 chroma subsampling, preserve existing tile size, do not use premultiplied alpha (164,855 bytes) https://files.catbox.moe/u7q7dn.avif

Hadriscus has the right idea suggesting that JPEG is the wrong comparison, but this type of low-detail image at low bit rates is actually where AVIF rather than JPEG XL shines. The latter (for this specific image) looks a lot worse at the above settings, and WebP is generally just worse than AVIF or JPEG XL for compression efficiency since it’s much older. This type of image is also where I would guess this type of compression / reconstruction technique also does comparatively well.

But honestly, the technique as described by the paper doesn’t seem to be trying to directly compete against JPEG which is another reason I don’t like that the video put a spotlight on that comparison; quoting the paper:

We also include JPEG [Wallace 1991] as a conventional baseline for completeness. Since our objective is to represent high-resolution images at ultra-low bitrates, the allow-able memory budget exceeds the range explored by most baselines.

Most image compression formats (with AVIF being a possible exception) aren’t tailored for “ultra-low bitrates”. Nevertheless, here’s another comparison with the flamingo photo in the dataset where I’ll try to match the 0.061 bpp low-side bit rate target (if I’ve got my math right that’s 255,860.544 bits):

• Original PNG (2,811,804 bytes) https://files.catbox.moe/w72nsv.png
• AVIF; as above but quality 30 (31,238 bytes) https://files.catbox.moe/w2k2eo.avif
• JPEG XL could not go below ~36KB even at quality 0 when using my available encoder, so I considered it to fail this test
• JPEG (including when using MozJPEG, which is generally more efficient than “normal” JPEG) and WebP could only hit the target file size by looking garbage, so I considered them to fail this test out of hand

(Ideally I would now compare this image at some of the other, higher bpp targets but I am le tired.)

It looks like interesting research for low bit rate / low bpp compression techniques and is probably also more exciting for anyone in the “AI compression” scene, but I’m not convinced about “Intel Just Changed Computer Graphics Forever!” as the video title.

As an aside, every image in the supplied dataset looks weird to me (even the ones marked as photos), as though it were AI-generated or AI-enhanced or something - not sure if the authors are trying to pull a fast one or if misuse of generative AI has eroded my ability to discern reality 🤔

edit: to save you from JPEG XL hell, here’s the JPEG XL image which you probably can’t view, but losslessly re-encoded to a PNG: https://files.catbox.moe/8ar1px.png

Really wish they published the whole dataset. They don’t specify on the page or in the paper what the full set was like, and the GitHub repo only has one of the easy-to-read ones. If >=10% of the set is comprised of clock faces designed not to be readable then fair enough.

The human level accuracy is less than 90%!?

Anecdotally, a lot of users vote “selfishly” and don’t care that downvoting reduces visibility. all and local feeds also fall victim to people voting as if these are their own personal curated feeds.

And I hate it 🫠

“We’re going to collect as much data about you as we can to sell to advertisers”

That’s a rather pessimistic interpretation of a privacy policy that starts with this:

The spirit of the policy remains the same: we aren’t here to exploit you or your info. We just want to bring you great new videos and creators to enjoy, and the systems we build to do that will sometimes require stuff like cookies.

and which in section 10 (Notice for Nevada Residents) says:

We do not “sell” personal information to third parties for monetary consideration [as defined in Nevada law] […] Nevada law defines “sale” to mean the exchange of certain types of personal information for monetary consideration to another person. We do not currently sell personal information as defined in the Nevada law.

So yes, I suppose they may be selling personal information by some other definition (I don’t know the Nevada law in question). But it feels extremely aggressive to label it a “shithole” that “collect[s] as much data about you as we can to sell to advertisers” based on the text of the privacy policy as provided.

I guess perspective here depends on your anchoring point. I’m anchoring mostly on the existing platform (YouTube), and Nebula’s policy here looks better (subjectively much better) than what runs as normal in big tech. If your anchor is your local PeerTube instance with a privacy policy that wasn’t written by lawyers, I can see how you’d not be a fan.

However beyond being in legalese I’m not sure what part of it you find so bad as to describe it as a shithole. Even compared to e.g., lemmy.world’s privacy policy Nebula’s looks “good enough” to me. They collect slightly more device information than I wish they did and are more open to having/using advertising partners than I had expected (from what I know of the service as someone who has never actually used it) but that’s like… pretty tame compared what most of the big platforms have.

Nebula is a shithole, just have a glance at their privacy policy.

https://nebula.tv/privacy

It looks pretty run of the mill to me?

Can access fine (with reduced functionality) on my end with JS disabled - maybe you have something else tripping it up or something?

There is a deep irony covering this by writing about it… on Substack

I think you’ve tilted slightly too far towards cynicism here, though “it might not be as ‘fair’ as you think” is probably also still largely true for people that don’t look into it too hard. Part of my perspective is coming from this random video I watched not long ago which is basically an extended review of the Fairphone 5 that also looks at the “fair” aspect of things.

Misc points:

• In targeting Scope 2 emissions they went with renewables to get down to 0 Scope 2 emissions. (p13)
• In targeting Scope 3 emissions they rejigged their transportation a little (ocean freight instead of flying, it sounds like?) to reduce emissions there. (p14)
• In targeting Scope 3 emissions they used an unspecified level of renewable energy in late manufacturing with modest claimed emissions reductions. (p14)
• Retired some carbon credits, which, yes, are usually not as great as we would like, but still. (p14)
• They may have some impact by choice of supplier even when they don’t necessarily directly spend extra cash on e.g., higher worker payments.
• They may have some impact by engaging with suppliers. They provide small-scale examples of conducting worker satisfaction surveys via independent third party which seemed to provide some concrete improvements (p30) and “supporting” another supplier in “implementing best practices for a worker-management safety committee” (p30).
• They’re reducing exposure to hazardous chemicals in final assembly, and according to them they are “the first company to start eliminating CEPN’s second round priority chemicals” (p31). I don’t know much about this.
• With partners, they “organize school competitions in which children are educated about […] e-waste” (p40).
• They’re “building local recycling capacity” in Ghana by “collaborating” with recycling companies (p40).
• Extremely high repairability (with modest costs for replacement parts that make it financially sensible to repair instead of replace) keeps more phones in use, reducing all the bad parts of having to manufacture brand new phones.
• The ICs make up a huge portion of the environmental costs of the phone (both with the FP4 (pp 40-41) and with the FP5 (p10)), and Fairphone isn’t big enough to get behemoth chip manufacturers to change their processes (though apparently they’re lobbying Qualcomm for socketable designs, as unlikely as that is to happen any time soon). If you accept the premise that for around half of the phone they have almost no impact on in terms of the manufacturing side, it makes their efforts on the rest a bit better, I guess?

So yes, they are a long way from selling “100% fair” phones, but it seems like they’re inching the needle a bit more than your summary suggests, and that’s not nothing. It feels like you’ve skipped over lots of small-yet-positive things which are not simply “low economy of scale manufacturing” efforts.

So they literally agree not using an LLM would increase your framerate.

Well, yes, but the point is that at the time that you’re using the tool you don’t need your frame rate maxed out anyway (the alternative would probably be alt-tabbing, where again you wouldn’t need your frame rate maxed out), so that downside seems kind of moot.

Also what would the machine know that the Internet couldn‘t answer as or more quickly while using fewer resources anyway?

If you include the user’s time as a resource, it sounds like it could potentially do a pretty good job of explaining, surfacing, and modifying game and system settings, particularly to less technical users.

For how well it works in practice, we’ll have to test it ourselves / wait for independent reviews.

It sounds like it only needs to consume resources (at least significant resources, I guess) when answering a query, which will already be happening when you’re in a relatively “idle” situation in the game since you’ll have to stop to provide the query anyway. It’s also a Llama-based SLM (S = “small”), not an LLM for whatever that’s worth:

Under the hood, G-Assist now uses a Llama-based Instruct model with 8 billion parameters, packing language understanding into a tiny fraction of the size of today’s large scale AI models. This allows G-Assist to run locally on GeForce RTX hardware. And with the rapid pace of SLM research, these compact models are becoming more capable and efficient every few months.

When G-Assist is prompted for help by pressing Alt+G — say, to optimize graphics settings or check GPU temperatures— your GeForce RTX GPU briefly allocates a portion of its horsepower to AI inference. If you’re simultaneously gaming or running another GPU-heavy application, a short dip in render rate or inference completion speed may occur during those few seconds. Once G-Assist finishes its task, the GPU returns to delivering full performance to the game or app. (emphasis added)

Would be curious to read the LLM output.

It looks like it’s available in the linked study’s paper (near the end)

The process described and shown by the screenshots does seem a bit much for a cancellation. Suing feels disproportionate when I first hear it, but are there many other recourses to force it to become more user friendly?

Fair point, but I guess I would hope that the person being paid to write the copy would check it, since getting that right seems like it’s part of their job description ¯\_(ツ)_/¯

Or 53.6 degrees Fahrenheit if you believe whoever wrote the page for Nissan lmao. I guess they just typed it into a converter with no context, and the converter spat out an answer amounting to “if your thermometer says it’s 12 degrees C, that would be 53.6 degrees F”… but without that context.