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Looking into the code.

DPA via Reuters

Looking inside the black box

One of the biggest challenges facing artificial intelligence companies is that they don’t know everything about their algorithms. This so-called black box problem is exacerbated by the fact that deep learning models do precisely that — they learn. And when they learn they change. They take in enormous troves of data, detect patterns, and spit something out: How a sentence should read, what an image should look like, how a voice should sound.
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A smartphone is displaying GPT-4o with the OpenAI logo visible in the background in this photo illustration, taken in Brussels, Belgium, on May 13, 2024.

Google and OpenAI’s competition heats up

Both Google and OpenAI held big AI-focused events last week to remind the world why they should each be leaders in artificial intelligence.

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FILE PHOTO: A flare burns excess natural gas in the Permian Basin in Loving County, Texas, U.S. November 23, 2019. Picture taken November 23, 2019.

REUTERS/Angus Mordant/File Photo

Hard Numbers: Unnatural gas needs, Google’s data centers, Homeland Security’s new board, Japan’s new LLM

8.5 billion: Rising energy usage from AI data centers could lead to additional demand for natural gas of up to 8.5 billion cubic feet per day, according to an investment bank estimate. Generative AI requires high energy and water demands to power and cool expansive data centers, which climate advocates have warned could exacerbate climate change.

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Shira Perlmutter, Register of Copyrights and Director, U.S. Copyright Office, speaking at a hearing of the House Judiciary Committee's Subcommittee on Courts, Intellectual Property, and the Internet at the U.S. Capitol.

Michael Brochstein/Sipa USA via Reuters Connect

Bad-behaving bots: Copyright Office to the rescue?

It might not be the flashiest agency in Washington, DC, but the Copyright Office, part of the Library of Congress, could be key to shaping the future of generative AI and the public policy that governs it.

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Regulating AI: The urgent need for global safeguards
Regulating AI: The urgent need for global safeguards | GZERO Media

Regulating AI: The urgent need for global safeguards

There’s been a lot of excitement about the power and potential of new generative artificial intelligence tools like ChatGPT or Midjourney. But there’s also a lot to be worried about, like misinformation, data privacy, and algorithm bias, just to name a few.

On GZERO World with Ian Bremmer, cognitive scientist and AI researcher Gary Marcus lays out the case for effective, comprehensive, global regulation when it comes to artificial intelligence.

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