AI Eats the World: Benedict Evans on What Really Matters Now
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What is the main topic discussed in this episode?
You've got people who are saying this is all
What is the big question about AI being a platform shift or a paradigm shift?
None of it works, it's completely useless, which is just really a stupid thing to say.
How do error rates and trust affect the adoption of AI models?
There are hundreds and hundreds of companies who've already got this in production doing stuff that's really useful, but at the same time it's not good at everything. And there's a bunch of stuff that it really can't do yet. You can't just kind of pretend that's not there by saying, well, it's getting better all the time. What do you mean better?
Why are brand, distribution, and reach the real moats for AI products?
Welcome to the Mad Podcast. Today I'm thrilled to welcome back Benedict Evans, by far one of my favorite thinkers and analysts in the world of tech.
What does hiring a CEO of Applications signal for OpenAI’s strategy?
After two decades tracking every platform shift, from the PC to mobile to cloud, Benedict now advises Global 2000 boardrooms on what generative AI really changes and what it doesn't.
How are big tech companies (Apple, Google, Meta, AWS) approaching AI?
In this wide-ranging chat, we dig into model commoditization and distribution wars.
Is ChatGPT becoming a search engine and how does it compare to traditional search?
Much buzz in tech around perplexity, they don't break the top hundred in the app store.
What are the emerging consumer AI apps and where might the next breakout be?
Why is ChatGPT at the top of the App Store chart and has been for a year? It's kind of a distribution and brand and reach story. Enterprise reality checks and the agent hype cycle. I'm puzzled by AI agents. I struggle to see why this isn't just like the models are a bit better now. These agent demos where they don't do all these multi-stage things, it's not a real demo. It's not working. And why doom Terrorism fizzled. They invited all the Doomers to Davos in 2024. And they listened to them and saw these people are idiots and didn't invite them back. They were all really clever people who told each other how clever they were and constructed these logically flawless.
kind of arguments. This is a fantastic discussion, in turn thought provoking, funny, and deeply insightful. A quick note before jumping in, if you listen to the Mad podcast on either Spotify or Apple Podcasts, we'd be very grateful for a five-star rating. This really helps the podcast. Please enjoy my conversation with Benedict Evans. Benedict, welcome back. Thanks for having me. So last time uh we uh did this, which was about a year ago in April twenty twenty-four, uh we left people on a bit of a cliffhanger. And the question at the time was whether AI is a platform shift, uh meaning something a little bit like cloud or mobile, or something more important like a paradigm shift. Fast forward to today, do we have any more clarity on that question?
Um
Um, well it's funny, I don't think we do, to be honest. I mean, the models have keep getting better. We've shifted from pre training to post training. We keep they keep getting better, but not in a way that would make you say, Oh, well, obviously now we're going to the moon. It's just they carried on improving. The thing that's become very clear if it wasn't clear a year ago is that the models themselves are sort of commodities in that, you know, there's half a dozen people who have a state of the art model. I mean there's a bit of sort of difference in emphases, but you the models themselves seem to be commodities. So there's an interesting kind of split in that like you could say that Anthropic and Claude and ChatGPT are just as good as each other are indeed Gemini, but then go and look at the app store charts or look at Google Trends and see which one's getting used.
So there's an interesting sort of sort of there's some interesting kind of differences emerging. Um, but yeah, we uh a year ago we didn't know if the scaling would continue. We still didn't know if the scaling will continue. And a lot of the questions you kind of could have asked in like the beginning of 2023 don't really have answers yet. Um so I kind of struggle sometimes to say anything new to say. Because you can talk about intellectual property, you can talk about the user interface problem, you can talk about how do you manage the error rate, you can, you know, you can make your list of a dozen questions. And there's not very much that you would say that's different about those now to what you would have said in the kind of the spring of of twenty twenty three, at a kind of a high kind of conceptual sort of product strategy level.
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Chapters
8 chapters
1
What is the main topic discussed in this episode?
0:00–0:02
2
What is the big question about AI being a platform shift or a paradigm shift?
0:02–0:06
3
How do error rates and trust affect the adoption of AI models?
0:06–0:23
4
Why are brand, distribution, and reach the real moats for AI products?
0:23–0:32
5
What does hiring a CEO of Applications signal for OpenAI’s strategy?
0:32–0:43
6
How are big tech companies (Apple, Google, Meta, AWS) approaching AI?
0:43–0:49
7
Is ChatGPT becoming a search engine and how does it compare to traditional search?
0:49–0:52
8
What are the emerging consumer AI apps and where might the next breakout be?
0:52–1:15:09
Speakers
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