テスラダイナー&スーパーチャージャー(ルイジアナ州ハリウッド) 24時間年中無休、今から営業

MirageLSD の紹介: 初のライブ ストリーム ディフュージョン (LSD) AI モデル カメラやビデオチャットからコンピューター画面やゲームまで、任意のビデオストリームを入力し、リアルタイムで任意の世界に変換します(<40msの遅延)。 仕組みは次のとおりです(使用できるデモ付き!

I'm constantly irritated that I don't have time to read the torrent of cool papers coming faster and faster from amazing people in relevant fields. Other scientists have the same issue and have no time to read most of my lengthy conceptual papers either. So whom are we writing these papers for? I guess, at least until they fall in to the same issue from their own work, AI's will be the only ones who actually have the bandwidth to read all this stuff. I'm not specifically talking about today's language models - let's assume we mean whatever inevitable AI shows up, that is able to read the literature and have impact on the research (whether by talking to humans or by running lab automation/robot scientist platforms). So then: how should we be writing, knowing that a lot of our audience will be AI (plus cyborgs, hybrots, augmented humans, etc.)? Maybe it's too early to know what to do, but we better start thinking about it because assuming our audience will always be today's humans seems untenable. Taking seriously the idea that someday the impactful audience will be very different, and that the things we write now are in some sense a training set for truly diverse future beings, how does our writing change? or does it? what say you @danfaggella @mpshanahan @Plinz @blaiseaguera ?