Kyle Vogt estimates that people spend five to ten hours a week on unpaid household chores.
“I think five to ten hours a week people spend doing essentially unpaid, unskilled labor in their own home.”
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Kyle Vogt
1 episodes · 19 quoted claims
Kyle Vogt says a general home robot became feasible only recently because of large language models and end-to-end neural networks.
“it was very clearly not possible up until very recently with LLMs and then end-to-end neural networks to control robots.”
Kyle Vogt says transformative household machines such as dishwashers and laundry machines date from roughly the 1950s and 1960s.
“These are all machines that had a huge impact on our lives, and these are all from the era of, I don't know, the 50s and 60s”
Kyle Vogt says laundry and dishes are poor first tasks for a home robot because people are particular about them and mistakes are costly.
“laundry and dishes are things for which people are very particular about. And the cost of making a mistake is very high.”
Kyle Vogt says folding clothes was long a hard research problem because classic robots were built for repeatable, precise handling of rigid objects.
“That used to be the holy grail of manipulation. because classically, robots are designed for repeatability and precision and picking up the same thing in the same place every time.”
Kyle Vogt says traditional robots used expensive laser scanners to rebuild their surroundings and then relied on complicated algorithms that were hard to tune.
“it would have expensive laser scanners and try to perfectly reconstruct everything that we see and then use very complicated and hard-to-tune algorithms”
Kyle Vogt says self-driving needed about five or six nines of reliability to be commercially successful.
“the bar for commercial success for self-driving was like five, six nines of reliability.”
Kyle Vogt says each additional nine of reliability is ten times better and takes roughly ten times more engineering work.
“understand that each extra nine of reliability you add, so 10 times better, takes probably 10 times more engineering work.”
Kyle Vogt says Bot Company engineers can go from their desk to running code on a robot within about 10 feet.
“I don't think you have to walk more than 10 feet in our office to go from your desk to running code on a robot.”
Kyle Vogt says self-driving was mainly funded by large corporations with deep pockets rather than by venture-backed startups.
“They were large corporations with R &D budgets or basically the pockets that were deep enough to make strategic long-term bets that could significantly move the needle for the company”
Kyle Vogt says the US has no federal preemption or federal safety standards for autonomous vehicles, leaving a patchwork of local rules.
“because there is no federal preemption. There's no real federal safety standards for autonomous vehicles.”
Kyle Vogt says Tesla pioneered the end-to-end neural network approach to self-driving and that he thinks it is the right long-term bet.
“What I see is really Tesla as a company who kind of pioneered the end-to-end neural network approach to self-driving, which I think is the right technical bet long-term.”
Kyle Vogt says Tesla constrained its engineers by denying them lidar and radar and requiring cheap, good-looking sensors.
“They said, hey, engineers, you can't have the best sensors like lidars and radars, and the sensors have to look good when we put them on the car.”
Kyle Vogt says Waymo began in the DARPA Grand Challenge era using classical computer vision and motion planning.
“With Waymo, they started off in the DARPA Grand Challenge era of self-driving, which is old school, classical computer vision, classical motion planning.”
Kyle Vogt argues Waymo's approach is flawed because keeping a real-time 3D map of everywhere is intractable.
“it is just intractable to maintain a 3D map of every square inch of the planet and update it in real time”
Kyle Vogt says companies growing from 80 to 400 people can see productivity per person drop by about 90 percent.
“when we go from 80 people to 400 people, our productivity per person is going to drop by 90%.”
Kyle Vogt says he justified selling Cruise because the buyer was then North America's largest automaker.
“I convinced myself when selling Cruise that at the time it was North America's largest automaker.”
Kyle Vogt compares a large corporation to an aircraft carrier that cannot be steered, explaining why he regrets selling Cruise.
“It's like an aircraft carrier. You can't steer it. You can't get it to change its focus.”
Kyle Vogt predicts the next $100 billion company created around 2025 to 2026 will have fewer than 100 employees.
“I think the next $100 billion company that's created in 2025, 2026 will be under 100 people.”