Chris shares his journey starting from playing in R.E.M, becoming interested in physics to leading WIRED Magazine for 11 years. His robot fascination lead to starting a company that manufactures drones, and creating a community democratizing self-driving cars.

Chris Anderson is the CEO of 3D Robotics, founder of the Linux Foundation Dronecode Project and founder of the DIY Drones and DIY Robocars communities. From 2001 through 2012 he was the Editor in Chief of Wired Magazine. He's also the author of the New York Times bestsellers `The Long Tail` and `Free` and `Makers: The New Industrial Revolution`. In 2007 he was named to "Time 100," most influential men and women in the world.

Links discussed in this episode:

DIY Robocars: diyrobocars.com

Getting Started with Robocars: https://diyrobocars.com/2020/10/31/getting-started-with-robocars/

DIY Robotics Meet Up: https://www.meetup.com/DIYRobocars

Other Works

3DRobotics: https://www.3dr.com/

The Long Tail by Chris Anderson: https://www.amazon.com/Long-Tail-Future-Business-Selling/dp/1401309666/ref=sr_1_1?dchild=1&keywords=The+Long+Tail&qid=1610580178&s=books&sr=1-1

Interesting links Chris shared

OpenMV: https://openmv.io/

Intel Tracking Camera: https://www.intelrealsense.com/tracking-camera-t265/

Zumi Self-Driving Car Kit: https://www.robolink.com/zumi/

Possible Minds: Twenty-Five Ways of Looking at AI: https://www.amazon.com/Possible-Minds-Twenty-Five-Ways-Looking/dp/0525557997

Topics discussed:

0:00 sneak peek and intro

1:03 Battle of the REM's

3:35 A brief stint with Physics

5:09 Becoming a journalist and the woes of being a modern physicis

9:25 WIRED in the aughts

12:13 perspectives on "The Long Tail"

20:47 getting into drones

25:08 "Take a smartphone, add wings"

28:07 How did you get to autonomous racing cars?

33:30 COVID and virtual environments

38:40 Chris's hope for Robocars

40:54 Robocar hardware, software, sensors

53:49 path to Singularity/ regulations on drones

58:50 "the golden age of simulation"

1:00:22 biggest challenge in deploying ML models

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