This week has been a busy one, but I managed to get through this recent Prof G Markets interview with Mark Cuban while on the road and in between meetings. I like Mark Cuban. He comes across as likable and balanced. He's also pretty good at making money.
The conversation covers a lot of topics: AI, why AI could change the way we design housing, healthcare, the media landscape, social media algorithms, why it should be easier to be a public company, and what Cuban would do if he were president of the US, among others. If you're interested in these topics, maybe have a listen.
The discussion around social media algorithms struck a bit of a chord. At one point, Cuban makes the statement that this is one of the underlying challenges facing the US: whoever controls the algorithms controls our thoughts. He goes on to say that the social media algorithms know his kids better than he does.
Algorithms also shape our cities. Everything these days is being reverse-engineered for the attention economy. Typically, this means promoting more extreme views, instead of measured ones, which can drive a further wedge between cyclists and motorists, existing communities and new developments, and so on.
We know all this. But it's scary to think about the influence it has on our behaviors.
This week has been a busy one, but I managed to get through this recent Prof G Markets interview with Mark Cuban while on the road and in between meetings. I like Mark Cuban. He comes across as likable and balanced. He's also pretty good at making money.
The conversation covers a lot of topics: AI, why AI could change the way we design housing, healthcare, the media landscape, social media algorithms, why it should be easier to be a public company, and what Cuban would do if he were president of the US, among others. If you're interested in these topics, maybe have a listen.
The discussion around social media algorithms struck a bit of a chord. At one point, Cuban makes the statement that this is one of the underlying challenges facing the US: whoever controls the algorithms controls our thoughts. He goes on to say that the social media algorithms know his kids better than he does.
Algorithms also shape our cities. Everything these days is being reverse-engineered for the attention economy. Typically, this means promoting more extreme views, instead of measured ones, which can drive a further wedge between cyclists and motorists, existing communities and new developments, and so on.
We know all this. But it's scary to think about the influence it has on our behaviors.
One traditional metric for measuring the performance of a company is revenue per employee. And in a knowledge-based economy, this makes a lot of sense. Human capital is often the biggest expense. But as we enter the age of AI, this is now being called into question.
Bond — which is a San Francisco-based VC firm with a cool website — just published this 340-page report on Artificial Intelligence. One of the authors of the report is Mary Meeker. She has been called the "Queen of the Internet" thanks to a 20-year run of presentations about the state of the internet, and her perceived ability to identity new trends early. So people are paying attention to this report. Her last one was in 2019 and I mentioned her 2018 report on this blog, here.
At this point, it's boring to say that AI is ushering in "unprecedented" global change. Everyone sends around snippets from ChatGPT. I incorporate some sort of AI-powered tool all the time in my daily workflow. And we've started using it on our development projects to help with tedious things like design coordination. Eventually we'll probably stop calling it out as "AI" and just refer to it as the things that computers and the internet can do.
One traditional metric for measuring the performance of a company is revenue per employee. And in a knowledge-based economy, this makes a lot of sense. Human capital is often the biggest expense. But as we enter the age of AI, this is now being called into question.
Bond — which is a San Francisco-based VC firm with a cool website — just published this 340-page report on Artificial Intelligence. One of the authors of the report is Mary Meeker. She has been called the "Queen of the Internet" thanks to a 20-year run of presentations about the state of the internet, and her perceived ability to identity new trends early. So people are paying attention to this report. Her last one was in 2019 and I mentioned her 2018 report on this blog, here.
At this point, it's boring to say that AI is ushering in "unprecedented" global change. Everyone sends around snippets from ChatGPT. I incorporate some sort of AI-powered tool all the time in my daily workflow. And we've started using it on our development projects to help with tedious things like design coordination. Eventually we'll probably stop calling it out as "AI" and just refer to it as the things that computers and the internet can do.
Sara Menker has, for example, proposed a new metric: revenue per MWh. (See above comparing Meta, Alphabet, and Microsoft.) This is meant to reflect the fact that, as AI infrastructure scales, it is likely that operating costs in the future will be dominated by electricity consumption, rather than employee count.
Naturally, this should make you wonder about a few things, namely: How will we manage the inequality that might (or will) arise from the decoupling of revenues from employees? And how are we going to sustainability supply this rapidly growing need for more and more electricity?
Albert Wenger argues that the comparable metric for nations will be GDP per GWh. This means that, to win, you're going to want cheap electricity. And as I understand it, the cheapest sources are wind, solar, and hydropower. This bodes well for Canada given that we dominate in the latter.
But I think it's valuable to point out that this has been a really long time coming. The report talks about an "AI winter" from 1967 to 1996. That's a long time to stay motivated and interested in something that doesn't seem to be gaining traction. And it's a reminder that crypto is still early. Even though I also use blockchains every day and I've already transitioned (or am transitioning) a lot of my online life, including this blog.
Of particular relevance to this community is probably the fact that AI is also going to have a meaningful impact on our built environment. One of the sections in the report is called "Physical World AI," and it talks about how quickly data centers are now being built (compared to housing) and how Waymo (using AI) has taken something like 27% of the ride share market in San Francisco in the span of just 20 months.
This transportation product is now scaling, and cities have always responded and remade themselves according to new mobility innovations. This time won't be any different.
Sara Menker has, for example, proposed a new metric: revenue per MWh. (See above comparing Meta, Alphabet, and Microsoft.) This is meant to reflect the fact that, as AI infrastructure scales, it is likely that operating costs in the future will be dominated by electricity consumption, rather than employee count.
Naturally, this should make you wonder about a few things, namely: How will we manage the inequality that might (or will) arise from the decoupling of revenues from employees? And how are we going to sustainability supply this rapidly growing need for more and more electricity?
Albert Wenger argues that the comparable metric for nations will be GDP per GWh. This means that, to win, you're going to want cheap electricity. And as I understand it, the cheapest sources are wind, solar, and hydropower. This bodes well for Canada given that we dominate in the latter.
But I think it's valuable to point out that this has been a really long time coming. The report talks about an "AI winter" from 1967 to 1996. That's a long time to stay motivated and interested in something that doesn't seem to be gaining traction. And it's a reminder that crypto is still early. Even though I also use blockchains every day and I've already transitioned (or am transitioning) a lot of my online life, including this blog.
Of particular relevance to this community is probably the fact that AI is also going to have a meaningful impact on our built environment. One of the sections in the report is called "Physical World AI," and it talks about how quickly data centers are now being built (compared to housing) and how Waymo (using AI) has taken something like 27% of the ride share market in San Francisco in the span of just 20 months.
This transportation product is now scaling, and cities have always responded and remade themselves according to new mobility innovations. This time won't be any different.
