Fundamentally, I don't know if people realise that what we're on the verge of here. It's effectively a motion-mapped keypoints of the person projected onto a simulated model. I'm assuming the cartoonish avatar was used as an example to partly avoid drawing direct lines to the full implications. - There's no reason this couldn't extend to voice modelling as well. (much clearer speaking at much lower bandwidth) - There…
If the sending machine (that films my face) does the same decoding I know will be on the other end, then diffs the raw video with the decoded video and finally sends both things, then the receiver should be able to always piece together a 100% reproduction of the actual video feed on my end. The transmitter can always predict exactly what the receiver will decode, so the correct amount of data to send is the amount o…
I suspect that this isn't feasible. Otherwise lossy video codecs wouldn't exist (or would be very niche). Because if you sent a perfect diff you would essentially have lossless compression again. So either your idea will revolutionize video compression or the "diff" would bring you back to the ballpark of lossless codecs.
It is a lossless codec yes, but I has a “base” image for the key frames (which are the most expensive) which can be transmitted as the key points. The question is how much that actually helps the end result vs how much it costs. As I said it would likely kill at lest nearly all the gains, but again - a small improvement in the state of the art for “normal” looking video would be more impressive than three orders of magnitude vs sending instructions to my head puppet.
At what resolution? And also, does the output actually resembles the original image? Examples with background other than uniform? Would be nice if they provided more than just screenshots It's not uncommon to see video calls at 100kbs-150kbps, which is ~10KB/s, and this is for 7fps or so, including audio. So "per frame" that would be 1KB or so (more for key frames, less for I frames). So they say it can be 0.1KB, so…
This is probably first-order-model[1] using keyframes. You send only one image each 2 seconds and the mesh of face 30 times per seconds. Then use first-order-model to extrapolate 2 seconds of video from the keyframe. Rinse, repeat. Very doable. AMAZING! The original first-order-model could not do 30 frames per second, but maybe this Nvidia model has some improvements. 1 - https://aliaksandrsiarohin.github.io/first-or…
Now we are just guessing. This is a press release, which does not contain enough technical info. So one can't say how groundbreaking this is.
It's like with those news "the new battery type has been discovered", with very little actual data, just guesswork.
I posit that no productivity would be lost. Just have a summarizing AI email you the outcomes.
Hello, isoprophlex, I'm your Assistant AI Today's meeting was an hour-and-a-half spent on bike-shedding the position--and color--of the "logout" button on our product page. 15 minutes were spent debating the resident usability expert who suggested white text on a dark blue background would be more readable for people with low vision. The department manager insisted on retaining pastel blue as it is his favorite color…
That was... believable, haha.
WFH hasn't lessened the amount of bullshit, but it's become more tolerable. I mute my mic and put on a playlist with elevator music.
Now all I need is an AI standin and this summarizer and we've basically achieved universal basic income.
In Vernor Vinge's boon Fire Upon the Deep he describes how interstellar calls work in the future. In the lowest bandwidth tier you are watching an animated static 2d photo with text-to-speech
. The book also touches topics like translation, different spectrum and senses different species want from the call.
What I don't like about AI processed images is that they are not real. I can't go past the fact that I am not looking at the picture as it looks like in reality but somehow smart approximation of the world that is not necessarily true.
You'd get used to it very quickly. Like you got used to TV and film, which differ substantially from an in-person view in many ways.