16 korrents from this recording
Every claim below is a statement made in this recording, quoted word for word and linked to the second it was said, so you can hear it rather than take our word for it. The wording comes from the transcript published alongside the recording; the sentence above each quote is our reading of the claim, not their wording.
0:01:39 · watch on youtube.com↗
Their wordsMy 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
0:03:40 · watch on youtube.com↗
Their wordsIt 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.
0:06:08 · watch on youtube.com↗
Our reading
Incumbents have looked unbeatable at the start of every previous platform shift and have still lost.
Their wordsI'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.
0:09:27 · watch on youtube.com↗
Their wordsfilm 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.
0:12:07 · watch on youtube.com↗
Their wordsI 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.
0:15:02 · watch on youtube.com↗
Their wordsyou 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.
0:17:52 · watch on youtube.com↗
Their wordsI 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.
0:20:32 · watch on youtube.com↗
Their wordsPersonally, 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.
0:23:12 · watch on youtube.com↗
Their wordsBut 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.
0:27:19 · watch on youtube.com↗
Their wordswill 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
0:28:21 · watch on youtube.com↗
Their wordsLike 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.
0:30:55 · watch on youtube.com↗
Their wordsthere'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.
0:34:41 · watch on youtube.com↗
Their wordsIt'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.
0:46:39 · watch on youtube.com↗
Their wordsYou 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?
1:02:41 · watch on youtube.com↗
Their wordsBut 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.
1:10:27 · watch on youtube.com↗
Their wordsThe 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