Daron Acemoglu is doubling down and expanding a bit on what is on the GS paper on Generative AI: "Only about a quarter of tasks that could use artificial intelligence will likely be cost-effective in the next decade, according to Daron Acemoglu, Institute Professor at MIT. Speaking on the Goldman Sachs Exchanges podcast, Acemoglu says that even with big breakthroughs in AI, the impact will not be seen for several years." "The current architecture of the large language models has proven to be more impressive than many people would have predicted, but I think it still takes a big leap of faith to say that just on this architecture of predicting the next word, we're going to get something that's as smart as, you know, Hal in 2001: A Space Odyssey," he said. There "could be very severe limits on where we can go with the current (LLM) architecture," Acemoglu said. He is also skeptical that AI can achieve its goals more quickly by simply using more GPU capacity. He added that higher and higher-quality data, rather than capacity, will be needed, and where that data comes from needs to be clarified. It's worth a listen. https://lnkd.in/eMjnGVcy #AI #generativeAI
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How do we separate the hype of AI from potential investment opportunities? MFS strategists explored the AI phenomenon and what it means for investors. Grab a seat at this research table conversation and watch the replay now. bit.ly/4bB0OnA.
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How do we separate the hype of AI from potential investment opportunities? MFS strategists explored the AI phenomenon and what it means for investors. Grab a seat at this research table conversation and watch the replay now. bit.ly/4bB0OnA.
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How do we separate the hype of AI from potential investment opportunities? MFS strategists explored the AI phenomenon and what it means for investors. Grab a seat at this research table conversation and watch the replay now. bit.ly/4bB0OnA.
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