We knew this was coming, but Starsky Robotics is officially shutting down. CEO & Co-Founder Stefan Seltz-Axmacher addressed the shutdown in a lengthy blog, saying that “timing, more than anything else, is what I think is to blame for our unfortunate fate.”
The autonomous trucking startup was founded in 2015 and raised about $21 million. It raised a $16.5 million Series A in March 2018 that was led by Shasta Ventures. Previous investors Y Combinator, Trucks.vc, 50 Years and 9Point Ventures also contributed in the round.
Starsky tried taking a different approach to autonomous trucks than its competitors. Starsky’s trucks could be remotely operated by humans when exiting highways and driving the local streets to distribution centers – and vice versa.
“Our approach, I still believe, was the right one but the space was too overwhelmed with the unmet promise of AI to focus on a practical solution,” wrote Seltz-Axmacher. “As those breakthroughs failed to appear, the downpour of investor interest became a drizzle. It also didn’t help that last year’s tech IPOs took a lot of energy out of the tech industry, and that trucking has been in a recession for 18 or so months.”
‘Supervised machine learning doesn’t live up to the hype’
Seltz-Axmacher wrote about the various challenges facing autonomous vehicle companies. He said the biggest challenge is that “supervised machine learning doesn’t live up to the hype. It isn’t actual artificial intelligence akin to C-3PO, it’s a sophisticated pattern-matching tool.”
“Back in 2015, everyone thought their kids wouldn’t need to learn how to drive. Supervised machine learning (under the auspices of being “AI”) was advancing so quickly — in just a few years it had gone from mostly recognizing cats to more-or-less driving. It seemed that AI was following a Moore’s Law Curve.
“Five years later and AV professionals are no longer promising Artificial General Intelligence after the next code commit. Instead, the consensus has become that we’re at least 10 years away from self-driving cars.
“It’s widely understood that the hardest part of building AI is how it deals with situations that happen uncommonly, i.e. edge cases. In fact, the better your model, the harder it is to find robust data sets of novel edge cases.
“Additionally, the better your model, the more accurate the data you need to improve it. Rather than seeing exponential improvements in the quality of AI performance (a la Moore’s Law), we’re instead seeing exponential increases in the cost to improve AI systems — supervised ML seems to follow an S-Curve.”
Starsky Robotics’ Series B broke down
Seltz-Axmacher said a $20 million Series B fell apart in November 2019. Starsky Robotics then furloughed most of its employees and began working to sell the company. He said most of the employees found other jobs. He’s still working on selling Starsky Robotics’ assets, which include a number of patents for operating unmanned vehicles.
“Unfortunately, when investors cool on a space, they generally cool on the entire space. We also saw that investors really didn’t like the business model of being the operator, and that our heavy investment into safety didn’t translate for investors.”
He ended the blog with a pessimistic view about the industry’s ability to reach Level 5 fully autonomous vehicles.
“From my vantage point, I think the most likely line of human equivalence is L3 which means that no one should be betting a business on safe AI decision makers. The current companies who are will continue to drain momentum over the next two years, followed by a few years with nearly no investment in the space, and (hopefully) another unmanned highway test for 5 years.
“I’d love to be wrong. The aging workforce which will almost certainly start to limit economic growth in the next 5–10 years; the 4,000 people who die every year in truck accidents seem a needless sacrifice. If we showed anything at Starsky, it’s that this is buildable if you religiously focus on getting the person out of the vehicle in limited-use cases. But it will need to be someone else to realize that vision.”
Buck Crowley says
“Experience” is a code word for mistakes. The problem was that starting from no related experience, 4yrs & 7m is not enough time to make all the mistakes that others with 20,30,40,50 years of experience have going for them.
#Stefan_Seltz-Axmache You got this right:
“people use first principals and street smarts (experience) to solve “unsolvable” problems”.
The relevant first principals were established more than 30 years ago.
Experienced engineers put a man 238,900 miles away and brought him home. 50 years ago.
Certainly, #Jeff_Sterling is right, the workflow should always be changed before automating.
Experienced engineers can get this done.
#Stefan_Seltz-Axmache As you said Humanity needs this – now!
Crew Chief says
My 2019 Freightliner Cascadia has interactive cruise control and I have REGULAR issues with some part of the cruise control/automatic braking assist, ABS or some other electronic component. I’m not worried about autonomous vehicles taking over any time soon…
John Lopez says
Giving up too quickly!
Melvin Cannon says
Why wouldn’t the company put all the sensors and information gathering technology on a thousand tractor trailers driven by experience people for four years and use all that information for deep learning for its AI