https://epic.uchicago.edu/insights/china-has-quickly-and-sha...

Still, that is a good point, a lot of the emissions from manufacturing have been shifted to other countries.

To write a piece of music, you're working at so many different levels, the analytical, emotional, and structural as well as drawing on years of training and experience. When a person with little (or even just a moderate amount of) music training generates a piece of music in a couple hours, are they actually a composer? I personally would say no. I mean it does take a good ear (which is important) to use a music generator well, but still, would say they are more of an editor or an evaluator or a practical critic of music instead of a composer.

Yeah, at what point in a discipline does the increasing skill of AI overtake the need for our contributions from the working being done? In music, it's happened already. Looks like it's happening in coding too.

But kind of disagree about the film, think it was under appreciated. It isn’t a masterpiece, but the acting, the overall story, and the visuals were really good. And yeah, those dark Tron-visuals combined with the pulsing, digital daft-punk music really worked (at least for me), and when I want to get pulled into a different world, will rewatch that film.

And just a side question, it's incredible that her advisor would not use their computer (especially since they were in an analytical field, would think computers were essential for statisticians). What were their reasons? One obvious thought was were they just much older and didn't learn how to use them?

But even though their AI models aren’t the absolute leaders in every field, all their models are near the top, across the board. Yeah, their recognition of this current dominant trend before any other major company has given them a big advantage in the number of fields they’ve applied AI to. For example, by putting their full weight behind DeepMind early on, they had a bunch of models before anyone else dealing with topics from protein folding to playing games. Think for them, this might be the right strategy. Explore as much in AI as you can, and figure out the ways it is truly revolutionary. Don’t focus so much on creating products that will make money today or even in near future. Take the long view… hmm, actually, a good example of this is Waymo, it seemed stalled out a few years ago, but is the clearly the best self-driving cars currently out there and finally growing market share.

Also, it was their researchers who kicked off the LLM race with their seminal paper on transformers in 2017 (yeah, they should have released an LLM first, but think they have made up for it since then).

Yeah, am trying not to be overly enthusiastic, but still, despite a couple of big mistakes in AI, they seem to have made mostly correct calls for the past ~10 years. It’s an impressive track record at least to me.

https://www.businessinsider.com/sundar-pichai-wants-to-build...

And yeah, they did/do a lot through acquistions, but seems like most major companies screw up acquistions. Google has it's fair share of failed acquistions, but especially in the earlier half of the company's lifespan, they really did some great one: Youtube, Google docs, Nest...

maybe am biased, but have always thought Google in general does do it better than most tech companies. think it's their focus on the love of interesting ideas vs the love of money (although, that changes more and more as the company ages)