Comments on Tesla Engineer Interview

According to an interview conducted by a Korean engineer who worked for Tesla, Tesla engineers closely examine and study parts from suppliers and know them well. Additionally, unlike other automobile manufacturers, parts that are designed and produced on their own are increasing. Additionally, if it is deemed not worth enough after discussing the value of parts that have been used in electric vehicles for many years, they are completely removed.

This spirit is evident not only in electric vehicles but also in robot research. The second-generation robot, which is lighter and faster than the first-generation Optimus, has not changed a little. It seems to have been completely redesigned. In order to lose weight, it is likely that the number of actuators and drive motors was reduced or redesigned to a lighter form. The robot's skeleton was also made of a less dense and stronger material. At the same time, in order to mass-produce and sell at a low price, it would not have cost a lot of raw materials.

In order to successfully complete the mission sent by the management or chief executive, engineers would have been able to quickly chase other companies in just two years after coming up with innovative ideas, designing and manufacturing accordingly. There are a number of companies in the United States and Europe that can provide a lot of research funds other than Tesla. But, why can't you quickly develop a robot of that level?

Aren't the Korean conglomerates Samsung, LG, and Hyundai Motor capable of providing enough money? Why can't they? The reason is simple. The know-how did not accumulate because the research on pursuing the fundamental thing has not been done for a long time. Schools didn't teach students to pursue the fundamental thing, and students didn't pay much attention.

Many students have made computer games with well-made physical engines, but very few have made poor physical engines by themselves. Who has more power? There should be someone like Andrej Karpathy, who was at OpenAI and moved to Tesla's AI team to study the computer vision that is key to autonomous driving.

He is a Slovak Canadian who received a bachelor's degree in physics and computer engineering from the University of Toronto and a Ph.D. in computer vision and natural language processing from Stanford University. As a native of Eastern Europe, he is good at math and physics and computer programming, so there is nothing to be afraid of.

When he leaves Tesla and goes back to OpenAI, some say that Tesla's self-driving is not developing further. This means that his vacancy is large.

The direction of the Ministry of Education, which is now emphasizing convergence education, is to ignore deep (深) and emphasize wide (博), but in my view, education that will eventually become thin (簿) rather than wide (博).

This training will only nurture people who will continue to try to assemble the parts sold by suppliers but will not think about making lighter and faster moving robots. You cannot raise engineers who ask the fundamental question, 'Is this part necessary? Can't it be taken out if it's not necessary?'

I'd like to say this to someone who thinks, "No way." "No way he's going to catch people."