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Comment by thebluehawk | Hacker News Reader

I'm really confused. When describing the "Operational Domain" The author explains that a Tesla he drove 18 years ago handled a sample drive on FDR with two disengagements, while the Cadillac wouldn't stay engaged when he tried the same drive. Then says the Cadillac wins by a hair. How does a brand new system that doesn't work reliably win over a system that's been working better for over 18 months?

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I think the point of the whole article is that GM was able to make sure people only use the system when it was capable of working, where as Tesla's system can be used when it shouldn't be. He gets very distracted through out and accidentally mentions how good Tesla's self driving is.

As an aside, I rather Tesla's strategy to GM's. In 10 years when the tech is there, will this Cadillac simply handle freeways better? Seems like the car is locked in to a specific subset of self driving for the life of the car.

the whole field of modern "ai" is about 6 years old (since AlexNet won ImageNet), so 18 months is quite a long time.

More importantly, a review of flash performance is something that can be reasonable to perform, as another more long term reliability oriented one also can be.

This is a huge misconception. Modern AI is at least 30 years old, first convnets were conceived in 1980'ies, LSTM in early 90's. A lot of work went into deep learning before AlexNet eventually won the ImageNet. To some degree last years were not the "emergence" of deep learning but rather a culmination of many years of research and development.

I agree with you about the theoretical origins, but you'll agree that we didn't have anything remotely as deep or as effective before AlexNet, and that there was not remotely as much attention to the topic

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