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What Next | Daily News and Analysis

What Next: TBD | Tech, power, and the future - Is the A.I. Bubble Bursting?

What Next | Daily News and Analysis

Slate Podcasts

News, News Commentary, Daily News

4.32.4K Ratings

🗓️ 5 September 2025

⏱️ 35 minutes

🧾️ Download transcript

Summary

We’ve been told that artificial intelligence can write, code, generate images—it can do everything…except feasibly turn a profit. But investing in A.I. has nevertheless become a pillar of the U.S. economy. Where is this leading us?


Guest: Ed Zitron, author of the newsletter Where’s Your Ed At and host of the podcast Better Offline.


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Transcript

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0:00.0

There are some things you should always check, like the hygiene rating on your local takeaway,

0:06.2

the setting on your razor, and whether the party actually is fancy dress.

0:11.1

The other thing you should check is your Experian credit report, especially if you're looking to borrow money.

0:17.2

It lets you understand what lenders see, so you can increase your chances of getting the best deals.

0:22.8

It's dead easy to check it and completely free.

0:26.6

See it in seconds. Download the Experian app today.

0:30.9

The Monopoly game at McDonald's is back.

0:33.6

There's over two million pounds worth of cash prizes to be won.

0:36.6

And a chance to get your hands

0:37.8

on some epic prizes. Go on, it's your go.

0:43.0

18 plus UK ends 21st of October, selected menu items, at may be required, may depend on winning

0:48.0

moment. See victory rules.co.uk.uk.org. In case you were wondering, it is perfectly fine with Ed Zittron if you call him an AI hater.

1:01.5

I think so. I think considering I wrote a haters guide, and when you type haters guide into Google, it's one of the top two links, the thing I wrote.

1:12.2

Ed writes the newsletter, Where's Your Ed at?

1:14.9

And has a podcast called Better Offline.

1:18.1

He's a PR guy, but for the last few years, has been really making a name for himself

1:22.3

as someone who dislikes generative AI, especially large language models.

1:28.5

They are economically not feasible.

1:30.7

They require stealing from millions of people.

1:32.7

They require burning our environment.

1:34.8

They're incredibly expensive and inefficient.

1:37.7

And also, they have now become a load-bearing part of our economy

...

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