Fundamental science costs a lot of money and it's not immediately monetizable. Besides, how much of this was spent on TPU cycles? Furthermore, this "information" discourages everyone else from investing in AGI research.
“Alphabet’s DeepMind Losses Soared To $570 Million In 2018” @Forbeshttps://www.forbes.com/sites/samshead/2019/08/07/deepmind-losses-soared-to-570-million-in-2018/ …
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are you proposing that the world cover up deepmind’s economics in order to stave off an AI winter?
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I wonder how much Bell Labs "lost" in a typical year back before they broke up Ma Bell?
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Transistors of course made tons of money, even if (because of consent decrees) not for Bell. Deep RL thus far has not.
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This is the destiny of any research activity. Loose money in the short term but compensate it in the long term.
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AI started more than 70 years ago. We aren't in an AI winter, we're in the long tail. That said, the long tail of AI seems the wrong time for any company to focus on AI as a goal in itself. If the goal is to optimize multiple lineair regression, that market is quickly saturated.
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A good friend works there. Seems like exciting work! But also, ML research environments are really intense. Many companies have lots of R&D projects but they are scattered throughout the .org rather than concentrated under one umbrella.
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Silly stuff
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