Brandon Donnelly

Daily insights for city builders, delivered every morning at 6 AM ET. I’m Brandon Donnelly — a Toronto-based real estate developer and founder of Globizen. I’ve been writing here since 2013.

Subscribe

Category: Uncategorized

  • The WeWork of vacation rentals

    The word on the street is that Sonder — the marketplace for vacation rentals and competitor to Airbnb — is close to finalizing a $200 million investment round that would value the company at $1 billion.

    I first wrote about Sonder back in 2016 after I met someone from their business development team here in Toronto. I have yet to stay in a Sonder, but I’ve looked at their rentals a few times.

    One of the main differences between Sonder and Airbnb is that the former head leases their rental supply. And they do this by trying to go higher up on the food chain and partner with developers and real estate operators.

    In this regard, they are similar to WeWork. And it allows them to sit somewhere in between Airbnb and a conventional hotel. The supply is distributed, but the service offering is more consistent.

    Of course, this arguably makes their business model slower (they have to negotiate leases) and more costly (they’re committing to fixed costs). So it becomes a question of: How valuable is that consistent service offering?

    Lately when I travel, I’ve been trending more toward hotels, as opposed to Airbnb-like rentals. I like the experiences that many hotels are now focused on creating and I like knowing that if my flight arrives late (in a place like Brazil), I’ll be able to get into my room.

    I guess consistency does matter.

    Photo by Spencer Watson on Unsplash

  • The artificial intelligence bias

    Machine learning is one of the most important trends in tech right now. But like anything new, it naturally raises a number of important questions and concerns. Benedict Evan’s most recent blog post provides a good explanation of what he refers to as the artificial intelligence bias. Here are a couple of excerpts that I found interesting.

    What machine learning does:

    With machine learning, we don’t use hand-written rules to recognise X or Y. Instead, we take a thousand examples of X and a thousand examples of Y, and we get the computer to build a model based on statistical analysis of those examples. Then we can give that model a new data point and it says, with a given degree of accuracy, whether it fits example set X or example set Y. Machine learning uses data to generate a model, rather than a human being writing the model. This produces startlingly good results, particularly for recognition or pattern-finding problems, and this is the reason why the whole tech industry is being remade around machine learning.

    The rub:

    However, there’s a catch. In the real world, your thousand (or hundred thousand, or million) examples of X and Y also contain A, B, J, L, O, R, and P. Those may not be evenly distributed, and they may be prominent enough that the system pays more attention to L and R than it does to X.

    What AI isn’t:

    I often think that the term ‘artificial intelligence’ is deeply unhelpful in conversations like this. It creates the largely false impression that we have actually created, well, intelligence – that we are somehow on a path to HAL 9000 or Skynet – towards something that actually understands. We aren’t.

    The conclusion:

    Hence, it is completely false to say that ‘AI is maths, so it cannot be biased’. But it is equally false to say that ML is ‘inherently biased’. ML finds patterns in data – what patterns depends on the data, and the data is up to us, and what we do with it is up to us. Machine learning is much better at doing certain things than people, just as a dog is much better at finding drugs than people, but you wouldn’t convict someone on a dog’s evidence. And dogs are much more intelligent than any machine learning.

    Photo by Ales Nesetril on Unsplash

  • Young people are driving a lot less

    As a kid growing up in the suburbs, I got my driver’s license the day I turned 16. Being able to drive was a big deal. But we know that this desire to drive has been changing in profound ways. Here’s some recent stats on the percentage of licensed drivers in the US by age (taken from the WSJ):

    In 1983, about 46% of 16-year-olds had a driver’s license. By 2014, this number had dropped to 24.5%, which is the lowest it has been in recent years, and was probably impacted by the broader economy. As of 2017, this number was up to about 26%.

    If you’re a car company, I would imagine that these are pretty important numbers. They represent the top of the sales funnel. Most people probably like to have a driver’s license in hand before they go out and buy a car.

    Supposedly, some people in Detroit are betting that young people will still eventually buy a car. And when they do, it’ll be a nice big one like an SUV or a truck. But, the data suggests that it is not just young people who are eschewing driving.

    Here’s some data from the University of Michigan Transportation Research Institute (via NPR), looking at the proportion of licensed drivers in the US by all age categories:

    While the biggest drop has certainly happened among younger generations, licensing is still down for older cohorts. Based on these numbers, we don’t hit parity until somewhere around 50 to 54 years old.

    And the only cohorts where licensing has increased significantly are when people reach over 55. Over 70 is up by a huge margin — more than the drop among 16 year olds — which is probably a symptom of people living longer.

    Some of this decrease among young people can probably be attributed to delayed family formation and people living in denser urban environments, where it is more convenient to get around without a car. But I don’t think that’s all of it.

    Which suggests to me that the race to autonomy is a pretty important one to win.

  • The work of centuries

    Witold Rybczynski’s recent post about the tragic fire at Notre-Dame de Paris provides an interesting summary of cathedral construction techniques over the years:

    The Paris fire is also a reminder of what a weird hybrid structure Gothic cathedrals really are. The ancient Romans roofed their basilicas and baths with concrete vaults (the Pantheon with a dome), and the Byzantines used thin domes and vaults of brick. Over time, builders lost these skills and Romanesque cathedrals were roofed with exposed timber rafters like big barns. This made the buildings highly susceptible to fire, often caused by lightning strikes. The solution, pioneered at Durham Cathedral in the 11th century, was to build a lightweight ribbed stone vault over the nave. The timber roof remained, so the vault had no structural function (except to support itself) but it separated the interior from the flammable roof above. This was largely effective as the April 15 fire shows.

    Below is an image from the WSJ depicting Notre-Dame’s timber rafters and showing the extent of the area consumed by the fire. Fortunately, relatively little of the cathedral was actually destroyed.

    Going forward, there will almost certainly be a debate about how the roof and spire should be rebuilt. What materials and construction methods are appropriate for this emblem of Christianity and French culture?

    But I agree with Witold in that “there is nothing inauthentic about rebuilding.”

    It is common to lament that buildings simply aren’t built like they used to be. But this is not a new phenomenon. Construction methods change, as do the skills of builders.

    There may have been critics in the 1220’s complaining about how the cathedral’s roof was built using wood, instead of concrete or brick vaulting. But that’s what was relevant at the time.

    We also know that there have been periods of time since its construction where Notre-Dame simply languished. In fact, some have argued that this week’s fire was the result of decades of neglect.

    But Victor Hugo once wrote that, “great buildings, like great mountains, are the work of centuries.” Despite what unfortunately happened this week, that remains true of Notre-Dame de Paris.

  • Architect Jeanne Gang named to the TIME 100 list

    Architect Jeanne Gang (of Studio Gang) has just been named to the TIME 100, which is Time magazine’s annual list of the world’s most influential people. Jeanne is the only architect to be included in the 2019 list.

    Jeanne was named to the “Titans” category, which typically honors those who are at the top of their respective field. She sits alongside Mark Zuckerberg, Tiger Woods, and LeBron James in this year’s TIME 100.

    Past honorees within the architecture profession include Elizabeth Diller, David Adjaye, and Bjarke Ingels. All, stars.

    The list is in its 16th year. But it’ll be the first year where there will also be a day-long conference. (Lynne and Marc Benioff, of Salesforce, acquired the magazine in 2018 for $190 million in cash and are making some changes.)

    Congratulations Jeanne.

    Full disclosure: Studio Gang is the design architect for our One Delisle project in midtown Toronto.

  • Liquidity network effect

    Uber filed its S-1 last week in anticipation of going public in May. The WSJ reported on it, here. These are always interesting documents because you get access to previously private information. Here we can see that Uber’s ride-hailing market share in the US is down to 67% (as of February 2019) from 78% two years earlier. Revenue from this business line — which is the company’s biggest — also seems to have levelled off (chart from the WSJ):

    The ride-hailing business today has become a commodity. A lot of people, myself included, simply check to see which service is the cheapest (usually it’s Uber vs. Lyft). So this space feels to me like a giant race to build the biggest network and get to something new, whether that be autonomous vehicles or delivery drones. Uber calls this creating a “liquidity network effect.” Here’s an excerpt from the S-1:

    We have a massive, efficient, and intelligent network consisting of tens of millions of Drivers, consumers, restaurants, shippers, carriers, and dockless e-bikes and e-scooters, as well as underlying data, technology, and shared infrastructure. Our network becomes smarter with every trip. In over 700 cities around the world, our network powers movement at the touch of a button for millions, and we hope eventually billions, of people. We have massive network scale and liquidity, with 1.5 billion Trips and an average wait time of five minutes for a rider to be picked up by a Driver in the quarter ended December 31, 2018. Every node we add to our network increases liquidity, and we intend to continue to add more Drivers, consumers, restaurants, shippers, carriers, and dockless e-bikes and e-scooters. We also hope to add autonomous vehicles, delivery drones, and vertical takeoff and landing vehicles to our network, along with other future innovations. Our strategy is to create the largest network in each market so that we can have the greatest liquidity network effect, which we believe leads to a margin advantage.

    If you’d like to download a full copy of their filing, click here.

  • The post-combustion era

    Over the winter I visited BMW World, and its neighboring museum, in Munich, Germany.

    I loved seeing how the company got its start and how far it has come since it helped to invent the automobile at the beginning of the 20th century. I think their first product was actually an airplane engine.

    But you and I both know that the paradigm is changing. The internal combustion engine (ICE) is going away and pretty soon we won’t be driving, so much as being driven around by our cars.

    Bloomberg recently published an interesting article about this shift and about BMW. Here is an excerpt:

    The fact that both combustion engines and electric motors find themselves inside the same 18,000-person complex in Dingolfing, BMW’s largest in Europe, makes it a microcosm of a shift overtaking automakers the world over. A visitor can see that 625-horsepower engine—more than twice as powerful as the original from 1985, a luxury product relentlessly branded as “the ultimate driving machine”—then walk around the corner and see its puny electric replacement. You start thinking the better slogan might be “the ultimate combustion engine.” As in: last of its kind.

    Electric motors are a hell of a lot simpler to manufacture (and service) than gasoline engines. BMW estimates that they take about 30% less time to make. So the impacts of this transformation span everything from supply chain to human capital.

    Today, about 10% of the work that goes on in Dingolfing is related to electric vehicles.

  • What’s in a roof?

    Over the weekend I stumbled upon this illustrated Medium post by Alfred Twu comparing sloped and flat roofs. The argument is that these two roof types are coded. In this part of the world, at least, sloped roofs signal low-rise “house” and flat roofs signal big city “high-rise.”

    I’m not yet convinced of this association with height, or of all the claims made in the article. Did New York City really make the flat roof commonplace in our cities? But the idea that a roofline can trigger certain associations — or even become divisive — is a fascinating one.

    Take, for example, Am Fischtal in Berlin. On one side of the street you have, still to this day, homes with flat roofs. And on the other side you have homes with sloped roofs. This clean divide is the result of a supposed “roof war” that took place during the Weimar Republic.

    At this moment in time in the suburbs of Berlin, the kind of roof you chose to live under was a proclamation of your political orientation. I’m not sure roofs have as much gravitas as they did in the 1920’s on Am Fischtal, but they still do say something.

    Image: Alfred Twu

  • Holding a shadow

    Debating the merits — or shortcomings, depending on which camp you’re in — of all-glass buildings isn’t new. But there seems to be a bit of a resurgence happening right now because of the recent opening of Hudson Yards in New York.

    There’s an important environmental consideration here: Glass is, as a rule, a poor insulator. But often the other concern with all-glass buildings is their sameness. Witold Rybczynski recently wrote about this on his blog in a post called The Transparency Trap:

    Le Corbusier described (modernist) architecture as “the masterly, correct and magnificent play of volumes brought together in light.” Corbusier used glass but he never designed all-glass buildings. Neither did Mies; he added superfluous I-beams to his facades (which also had substantial spandrels). The problem with transparent glass is that it doesn’t hold a shadow, and without a shadow there can be no “play of volumes.” Since minimalist modernist architecture doesn’t offer decoration or ornament, that doesn’t leave much to look at.

    Witold isn’t usually appreciative of that which is new and I often find myself disagreeing with this critiques. But I like his metaphor of “holding a shadow.” Light and shadow are, of course, fundamental to architecture.

    Photo by LinedPhoto on Unsplash

  • Manhattan is getting a congestion pricing zone

    About a year ago I wrote about how NYC is considering a congestion charge on vehicles entering Manhattan below 60th street. Well it looks like that plan could be adopted as early as April 1 (however the fees won’t start until 2021).

    Here’s a map of the proposed congestion pricing zone from the NY Times:

    I have written extensively on road pricing over the years and so I won’t repeat myself here today. Suffice to say that I think creating a sustainable funding source for transit and other mobility options is a positive step forward.