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.

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.

Cover photo by Annie Spratt on Unsplash

Waymo and Uber just announced a partnership that will bring Waymo's autonomous vehicles to the Uber app in Austin and Atlanta. Notably, this is an exclusive partnership, meaning the only way you'll be able to summon a Waymo vehicle in these cities will be through Uber.

The people who follow this space closely, people like Reilly Brennan of Trucks (VC) and Harry Campbell (The Rideshare Guy), think this is a really big deal for a number of reasons.

One, it signals a bifurcation in the industry where there will be companies, like Waymo, that supply autonomous vehicles, and companies, like Uber, that operate them and manage the overall ride hailing marketplace. As part of this deal, Uber is going to handle all of the maintenance and cleaning of the vehicles. This split is similar to the airline industry.

Two, it suggests, and this is Harry's argument, that Waymo needs Uber more than Uber needs Waymo. One of the reasons for this is that a 100% AV fleet is simply too expensive to operate if you're solving for peak demand loads. Because during off-peak times, you then need to pay for downtime.

Uber, on the other hand, doesn't pay for downtime with its human drivers. Most of its drivers are part-time and only plug in when they want to or when the surge pricing becomes too attractive to pass up. So they're the perfect compliment to an AV fleet. Harry argues that this is part of Uber's competitive moat.

And three, it signals that AVs are really starting to arrive, if not already here. The hype cycle certainly hit its trough of disillusionment and everyone switched to thinking that AVs weren't going to happen for many years, if not decades. But now it's happening. City by city.

Construction is an essential sector of the economy, responsible for building and maintaining the physical infrastructure that underpins our society. However, it's no secret that construction productivity lags behind other sectors of the economy, such as manufacturing and information technology. So why is this the case?

One of the main reasons for the productivity gap is the unique nature of the construction industry. Unlike other sectors, construction projects are often one-off, bespoke endeavors, making it challenging to achieve the economies of scale that are typical of manufacturing or technology. Each project requires a different set of skills, tools, and materials, which can be costly and time-consuming to source and manage. This leads to a lack of standardization and efficiency, which can hinder productivity.

Another factor that contributes to low productivity in construction is the reliance on manual labor. Despite the increasing use of technology and automation, much of the work in construction still relies on physical labor, which is subject to human limitations and the potential for errors. This can result in delays, rework, and additional costs, all of which impact productivity.

Moreover, the construction industry faces challenges in terms of supply chain management and workforce development. The industry relies heavily on a complex network of suppliers, subcontractors, and laborers, all of whom must be coordinated and managed effectively. This can be difficult, particularly in light of the current labor shortage and skills gap in the industry.

To address these challenges, the construction industry needs to embrace innovation and new technologies to improve efficiency, standardize processes, and reduce waste. There is also a need to invest in workforce development and training to upskill the existing workforce and attract new talent to the industry.

In conclusion, the construction industry faces unique challenges that make it challenging to achieve the productivity gains that are typical of other sectors. However, with the right investments in technology, training, and process improvement, the industry can overcome these challenges and continue to build the infrastructure that our society relies on.

Maybe you didn't notice. But if the above doesn't sound like me and my writing, it's because today's blog post is brought to you by ChatGPT (AI). The prompt I used was, "write a short blog post about why construction productivity lags other sectors of the economy."

On some level, it's unsettling that AI can now, almost instantaneously, spit out a blog post like this. It would now be pretty easy to set up a daily blog, like this one here, and use ChatGPT to populate it each day.

But of course, while that might be interesting initially, it would quickly become a banal baseline. Anyone and everyone could copy what you're doing. AI is going to change a lot. But our jobs remain the same: find new ways to create value and be remarkable.