From one piece Why Everyone Is Wrong About AI (Including You) | Benedict Evans 16 beliefs, in the piece's order there
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Their words
The interesting Tesla point is people always looked at it and said, "It's the iPhone of cars." No, it's not. What's happening is that cars are becoming Android with no iPhone. And then Tesla is just selling and is is in that metaphor Tesla is just another android phone maker
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Their words
But you're still going to buy a smartphone. You're still going to buy the nice one with a good battery and the fast chip to run the models and the good screen and the best camera, which will still be an iPhone because Apple still has the best chip team and a whole bunch of other hardware advantages. But everything you do on it will be from someone else.
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You see this for the music now. You can generate new music. It could generate new stuff that you wouldn't know. For an LLM variance is bad. originality is is is a lower score. So what's the feedback loop for original but good?
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will the error rate ever be controllable or manageable will you ever get to a model that knows when it's wrong which to me seems like given a stat statistical system seems like a contradiction in terms
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It's like something around 10% give or take three or four percent of people depending on the survey are using this say they're using this every day. Another sort of 15 to 20% of people say they're using it every week.
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korrents.com
Large language models have no network effect, and remembering a user is a switching cost rather than one.Their words
there's no apparent equivalent in LLM right now there's no reason why the LMS get better because more people use them now that may come you have that open AI and people have doing memory where it remembers what else you've asked, but that seems more like a switching cost than a network effect.
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AnthropicGooglechat interfaces
Their words
Like it seems to me right now you could do like a double blind test of the same prompt given to Grock Claude Gemini um Mistral Deep Seek. Do a double blind test. I bet most people wouldn't be able to tell which is which.
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Their words
But once you actually have a sophisticated industrial economy, central planning can't handle the complexity. And so you try and create incentives and structures around that while not having pricing and that just doesn't work.
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korrents.com
The belief that this technology will produce bioweapons and kill everyone rests on childish logical fallacies.Their words
Personally, like most people in tech, I think the idea that this is all going to kind of produce bioweapons and take over the world and kill us all is just idiotic. Like I think I think it's just a bunch of kind of childish logical fallacies within that.
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Their words
I think regulation of AI is sort of the wrong level of abstraction. Talking about regulating AI as AI is the wrong level of abstraction. And it's like saying we're going to regulate databases or regulate spreadsheets or regulate cars. Well, we do, but not like that.
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korrents.com
Studies showing a language model behaving badly prove nothing, because the model was asked to produce that behaviour.Their words
you write murder is good on a piece of paper and you put it in a photocopier and you press go and you say my god the machine says murder's good. Well, no, you told the machine to say that. And that's what these anthropic studies are. They're basically you tell the machine to say a thing and then it says it like well you haven't proved anything.
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film was this high margin product where they had a bunch of unique intellectual property and digital cameras are a low margin um commodity where they were competing with the entire consumer electronics industry with no differentiation.
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I think it's actually the opposite which is that everyone's kind of using the same data which is you need such an enormous amount of generalized text that the amount that Google has or that meta has is not actually enough to move to be a kind of fundamental difference in what you can train with.
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korrents.com
Incumbents have looked unbeatable at the start of every previous platform shift and have still lost.Their words
I'm pretty sure people thought Microsoft had an advantage on the internet and Google and um Meta had an advantage on mobile and everyone thought IBM was going to win PCs. Like once IBM made a PC, that was it. It's all over now. And we kind of forget that like there were PCs before and then IBM made one and that kind of became the standard but then IBM lost it.
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korrents.com
Being certain a technology matters tells you almost nothing about where its value will end up being captured.Their words
It wasn't clear that the browser wasn't where the value capture was cuz Microsoft crowbarred its way into dominance in browsers but that turned out not to matter and then all the value is in search advertising and social which were 5 years later and 10 years later and so like you can be very very clear that this is the thing and then still be completely unclear how it's going to work.
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Their words
My sort of base case is to say this is kind of another platform shift and all the new stuff will be built around this for the next 10 or 15 years and then there'll be something else and so the impact on employment will be kind of like the impact on employment from the other platform shifts