Human experience dies with the person who acquired it, whereas machines can continue to learn indefinitely from a larger and larger pool of labeled data. Think about all the "take overs" when AI fails that Tesla sees each day that are made available to their training set.
As for the point about the training environment, a lot of what AI cars do is learn from simulations.
Re:Lidar Is a Crutch
by hprotagonist on Thursday January 31, 2019 @08:28AM
(#19044525)
>Human experience dies with the person who acquired it...
unless they wrote it down.
Books are one of the best thing we have to transmit experiences but it's far from a 1:1 process. Two people can read the same book but take away diametrically opposed things due to their own experiences / expectations.
You can read all the books and notes about WW1 battles, you'll never come close to feel what they felt in the trenches.
Re:Lidar Is a Crutch
by hprotagonist on Thursday January 31, 2019 @10:29AM
(#19045402)
Sure. Those objections are just as valid for "how i felt last week", though. The past is a foreign country, even to those of us who were around for it.
Re:Lidar Is a Crutch
by PhasmaFelis on Thursday January 31, 2019 @10:56AM
(#19045628)
Human knowledge can be written down, but knowledge is a poor shadow of first-hand experience.
Let's not forget about human experience. It gives context to any visual perception, and can't be replicated by cars. We simply have access to a larger, more complex environment, and the environment fosters our intelligence. It's easy to overemphasise the brain to the detriment of environment, but in reality the environment is the main cause for the development of intelligence in the brain. The corollary is also true - a lower complexity environment will lead to lesser intelligence, no matter how powerful the brain is. Intelligence springs where agent needs meet with external limitations, those limitations guide its development.
By analogy, the environment is like the training set and the brain is like a deep neural net. A deep neural net with a poor training set is not going to be accurate. That's why DeepMind, OpenAI and others have focused so much on artificial environments (games) to train agents - they know that environments are the key to training advanced AI. A mere dataset is like a static environment where nothing new happens. Research is transitioning from datasets to simulated environments for the next step in AI. I'd even go as far as to track the evolution of AI by the evolution of environments and environment models.