Good day! Let’s crack open a fat AI coconut, shall we?

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Here’s everything you need to know about AI today in 5 minutes.
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TODAY IN MINDSTREAM:

Analysts are predicting the AI hype might be over as soon as 2024, in terms of stock market gains.

In its annual roundup of top predictions for the future of the technology industry in 2024 and beyond, CCS Insight made several predictions about what lies ahead for AI.

The main forecast for 2024 is that generative AI “gets a cold shower in 2024” as the reality of the cost, risk and complexity involved “replaces the hype” surrounding the technology.

“The hype around generative AI in 2023 has just been so immense, that we think it’s overhyped, and there’s lots of obstacles that need to get through to bring it to market.” said Chief Analyst Ben Wood.

Their main argument is that the cost of deploying AI is immense, which will dampen any gains that companies hope to see from it.

An interesting and well-thought-out prediction, but will it come true?

Read more of the analysis here.

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Neural Architecture Search

Neural Architecture Search (NAS) automates the design of neural network structures to find the best-performing configuration for a specific task. This process streamlines model development, particularly for complex tasks like image recognition and natural language processing.

AI is helping scientists in almost every field make huge advances. It can already code computer programs, draw pictures and even take notes for doctors.

But when it comes to the sciences, AI has been a giant leap forward in a tiny period of time.

On Thursday, the U.S. National Academies held a two-day meeting on the potential for AI to change science.

AI scientists can really be more systematic, more comprehensive and not make errors," says Yolanda Gil, director of AI initiatives at the University of Southern California.

Rather than using AI to do all science, she imagines a future in which AI plans and executes experiments, with their human counterparts. In a world facing increasingly complex technical challenges, "there's not enough humans to do all this work," she says.

And she’s not the only one. Science researchers up and down the land are using AI to supercharge their research.

Susana Vazquez-Torres from the University of Washington says there are so many problems that need to be solved, and that many exciting discoveries lie ahead thanks to AI. "We can just make drugs right now so easily with these new tools," she says. Job security isn't a worry at all. "For me, it's the opposite — it's exciting."

If you want to dive deep on this, I highly recommend reading the article in full here on NPR.

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