I’ve said it before, but it bears repeating: I’m a fan of Jim Fan.
This clip from RoboBusiness 2025 shows why. His mix of humor and technical depth is rare—he can explain a decade of AI progress in one breath, and make the room laugh while doing it.
Fan opened with a jab at AlexNet, the 2012 model that kicked off deep learning:
“AlexNet was terrible.”
He’s right—it confused cats and planes about 37 percent of the time, hitting just 62.5 percent accuracy. Yet that “terrible” model was the start of everything: large-scale GPU training, end-to-end learning, and the deep-learning revolution that gave rise to today’s foundation models.
“Thirteen years took us from confusing cats and dogs to passing the Turing Test,” Fan said. “Add another 13 years, and we’re at 2038. But we round up because PhDs procrastinate. So—2040. Robotics solved.”
He grinned. “I’ll send you a Google invite.”
#JimFan #NVIDIA #RoboBusiness2025 #HumanoidRobotics #PhysicalAI #AIandRobotics #ProjectGroot #EmbodiedAI #DeepLearning #AlexNet #TuringTest #2040 #AgilityRobotics
A note from Diana: When I was at NVIDIA GTC, I met some amazing people from some incredible companies- one of whom was Dave Driggers, CEO of Cirrascale. I will be joining Dave next week on October 22, 2025 at 10:00 a.m. PT for a discussion about why cloud infrastructure is an existential decision. Come join us!
Webinar Topic: Scale or Stall; Why AI Applications Live or Die by Cloud Infrastructure
October 22, 2025
⏰ 10:00 AM PST
🔗 Reserve Your Spot
