Sri is a teenage phenom who combines an engaging social media profile with impressive projects on a wide variety of software engineering projects.
I particularly appreciate Sri’s summary of the neural networks in his perception stack. Not only did Sri train a network to detect and classify traffic lights, which is a component of the Capstone, but he also trained MobileNet-SSD to detect cars and pedestrians, which goes above and beyond the requirements.
Several years have now passed since I was part of the team that built this project for Udacity. We had so much fun, and I’m delighted to see that students like Sri are still enjoying it!
I know Chris principally from his organization of DIY Robocars, which is a kind of Homebrew Computer Club for the Bay Area autonomous vehicle community. Although I’ve never built a DIY robocar myself, I regularly pack my son up and drive him to the East Bay to watch the competitors zip their autonomous cars around the indoor track.
I am excited to see what Chris Anderson and the 3DR team does for Kitty Hawk.
I love this Domino’s commercial, featuring Nuro’s self-driving delivery vehicles.
The commercial played tonight during the Suns-Nuggets NBA playoff game. According to the YouTube date, this commercial has been up since April, but tonight was the first time I saw it. Autonomous vehicles go prime time!
As a side note, I inherited the Phoenix Suns from my father thirty years ago, which was an absolute disaster for the last ten years of my life. But this season has been so much fun!
Last week I wrote about Faction, a Y-Combinator start-up creating autonomous motorcycle-class vehicles. I’m now listening to an episode of The Eccentric CEO podcast in which host Aman Agarwal interviews Faction founder Ain McKendrick.
McKendrick talks a lot about how thoroughly motorcycle-class vehicles like rickshaws and scooters have penetrated Asia, but how rare they are in North America. Food for thought.
University of Toronto computer science professor Raquel Urtasun is launching a self-driving car startup called Waabi, as my Forbes editor Alan Ohnsman reports. Urtasun created the KITTI dataset, which remains a standard benchmark for robotic perception. She also joined Uber ATG as their chief scientist.
My friends at Uber ATG always had great things to say about her, so I’m excited she’s going out on her own. It’s also a natural result of Uber’s sale of ATG to Aurora, which is a minority investor in Waabi.
Waabi is launching with an $83.5 million funding round. For context, that’s more money than Voyage raised in total, across four years and deployment with real passengers (and safety operators). Waabi should be able to do a lot with $83.5 million dollars, presumably all the more so in Toronto, a lower cost region than Silicon Valley. According to TechCrunch, Waabi already employs 40 people.
Waabi seems likely to pursue a machine-learning first approach to autonomous vehicle development, based both on Urtasun’s statements and her academic background. Even the name, “Waabi”, hints at the goal.
Waabi means “she has vision” in Ojibwe and “simple” in Japanese.
Kirsten Korosec, TechCrunch
Ohnsman reports in Forbes that Waabi plans to focus “heavily on cutting-edge AI tools and less of what Urtasun calls a traditional ‘robotics’ mindset.” Urtasun is a deep learning expert, so I would expect to see a deep-learning-first approach at Waabi, or maybe even a deep-learning-only approach.
“You end up with an approach that requires much less to actually develop. It’s much less capital-intensive and doesn’t require this driving and driving and driving on the road. You get much more automated, fast-paced solutions, and with the ability to come up with much more complex systems.”
Raquel Urtasun in Forbes.com
That focus is reminiscent of Drive.ai, which applied a similar ML-first philosophy to self-driving cars, and also had an academic foundation. Drive.ai eventually ran out of funds and was acquihired by Apple.
Deep learning continues to advance, however, and with Urtasun at the helm, a deep-learning-first approach to self-driving may finally be poised to succeed.
“Cruise is the first entrant into the CPUC’s Driverless Pilot program, in which passengers can ride in a test vehicle that operates without a driver in the vehicle.”
California Public Utilities Commission
CPUC regulates taxis and other transportation carriers in the state. As always, Kirsten Korosec at TechCrunchnicely summarizes the news.
“In order to launch a commercial service for passengers here in the state of California, you need both the California DMV and the California PUC to issue deployment permits. Today we are honored to have been the first to receive a driverless autonomous service permit to test transporting passengers from the California PUC.”
Prashanthi Raman, Cruise Director of Government Affairs, in TechCrunch
Trucks is the preeminent mobility-focused venture capital firm in San Francisco, and arguably the world. They’ve been a big fish in a small pond, and the pond has been getting bigger, so now they are getting bigger.
Reilly Brennan, one of the founders of the firm, is well-known in the industry for his weekly Future of Transportation newsletter.
Trucks’ portfolio includes AEye, Bear Flag Robotics, Gatik, Joby, May Mobility, nuTonomy, Starsky Robotics, and many other mobility startups. Several of those companies have exited, one way or another, which is a credit to the firm.
They’re also launching a Growth Fund, to invest in larger companies, ideally companies from their seed funds that have grown into larger funding needs. The fund is open to the public right now, so take a look and consider participating!
The Growth Fund has an unusual structure, in which participants can provide $5,000 or more per quarter, and each quarter gets its own fund. I think this means you could invest as little as $5,000 in the growth fund (although you must be an accredited investor).
Yesterday I took my first ride in a Cruise autonomous vehicle! It was so much fun.
You can see in the photo that my car was named Tamale. Cruise names its vehicles playfully 🤗
Tamale took me from Cruise headquarters to the Pacific Heights neighborhood and back. That took a little under an hour, in San Francisco traffic.
Along the way we went up and down lots of hills, through several construction zones, and across multi-way intersections.
I sat in the back, while two Cruise technical operators sat in the front.
The vehicle’s ability to navigate really complex situations amazed me. I’ve seen vehicles handle these situations many times as an engineer, replaying rides at my computer. But riding in the vehicle really emphasizes the vehicle’s performance, and the complexity of the task.
I also observed lots of small potential improvements, many of which I know the engineering teams at Cruise are already tackling.
Riding in a self-driving car is a great way to appreciate just how impressive artificial intelligence and robotics is, and what the future holds in store.