I think it's because the media coverage is all focused on how this means the big AI players have lost their competitive advantage, rather than the other side of the equation.

But that's also dumb, because "huge leap forward in training efficiency" is not exactly bad news for the major players in even the medium term. Short term, it means their models are less competitive, but I don't see any reason that they can't leverage e.g. these new mixed precision training techniques on their giant GPU farms and train something even bigger and smarter.

There seems to be this weird baked in assumption that AI is at a permanent (or at least semi-permanent) plateau, and that open source models catching up is the end of the game. But this is an arms race, and we're nowhere near the finish line.