Large language models can be leveraged for identifying potential investments by steering them towards uncovering companies worth researching, aiding in foreign language learning by providing explanations and filling in knowledge gaps, generating ideas which require further exploration, and serving as a resource for various tasks like understanding how a company generates revenue, troubleshooting software issues, exploring creative recipes from available ingredients, and providing quick assistance in audio editing.
In 2023, the AI industry spent an estimated $50 billion on Nvidia chips, with the purpose of training AI models. The payoff for all that spend, according to Sequoia Capital, is $3 billion in revenue. Is that a return worth bragging about?
RIcky Mulvey talks with Fool analyst Asit Sharma about how investors might think about companies’ AI spend. They also discuss:
- The rate of improvement for AI models
- How non-Mag 7 companies are using AI
- And one company that’s spending smartly on the new technology.
Take a look at the Gartner Hype Cycle.
Host: Ricky Mulvey
Guest: Asit Sharma
Producer: Mary Long
Engineer: Tim Sparks
Companies discussed: GOOG, MSFT, NVDA, ARM, AMD, ORCL
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