That is called transfer learning. You might only need to see one photo of a sign to identify it in real life (although arguably learner drivers take a while to notice signs) but that is only because you have been training on identifying generic objects since you left the womb.
You brain already knows how to select the most important features of a sign. The shape, the size and the color. You have also learned how to understand the text on the sign.
A new born baby does not have that ability.
This is applied in ANN as well. Transfer learning is using a pre-trained neural network, which has already learned identifying objects, and then using it to train on identifying a new, usually smaller, set of objects using, usually, a lot less training data. That is what Andrew is talking about in the article.
And the context. For example, self-driving cars need to account for "Pizza Stop" restaurant signage, placards stuck to telephone poles that say things like "Stop Cancer", stop signs retracted into the sides of school buses, signs with additional instructions like "Stop when lights flashing", road workers with handheld stop signs, and the unconventional stop signs you see in parking lots.
You can probably get pretty far by checking the proximity to the road, height, dimensions, orientation, what it's mounted on, and if the sign incorporates any other text. But you can't just scan some pixels for "red octagon with STOP on it".
> because you have been training on identifying generic objects since you left the womb.
We can go back even further - your genes carry information about the structure and function of your brain and this has been refined by natural selection over the course of human evolution. Humans don't start from scratch with randomly initialised weights.
I'm not sure "training" is the right way to think about it. Children don't train to identify objects, they quickly develop the ability to recognize objects and are able to correlate them with prior information that was retained and learned. Case in point: if you take a child born blind, give them the ability to see, they are immediately able to recognize and correlate objects around them.
I have to disagree. They spend an inordinate amount of time trying to understand what they see, taste and hear.
> able to correlate them with prior information that was retained and learned
This is what we call inference.
> Case in point: if you take a child born blind, give them the ability to see, they are immediately able to recognize and correlate objects around them.
Not everyone who is legally blind can see absolutely nothing, but people who have recovered from complete vision loss [1] have problems. Mike May [2] lost vision as 3 year old child and regained it in his 40s. Despite seeing for the first three years of his life, years after regaining vision he was unable to see in 3D or recognize people from faces alone.
Blind people do not lack spatial awareness, so being able to recognize objects with context if they regained sight with would not surprise me. There are blind people that can "see" with echo location using parts of the brain associated with visual processing [3] But for example in Mike's case, he was unable to recognize close family by their faces years after regaining vision, he needed additional context.
Many things we take for granted as being innate to the human experience, are in fact learned (trained) behavior.
> I have to disagree. They spend an inordinate amount of time trying to understand what they see, taste and hear.
To understand yes, however I meant "identify" in the sense of recognizing an object. I show a picture of an apple to a child a bit over a year old, hide it, put it in a basket of other things and present it back to them, they will be able to identify it. Or if you show an object to a child, then hide the object, they can realize that the object is no longer there, regardless of their understanding of what happened to the object.
> Many things we take for granted as being innate to the human experience, are in fact learned (trained) behavior.
I don't think it's that simple, I would say it's both. I don't question learning plays a big role in recognition, just pointing out that a large amount intrinsic knowledge also exists from early child development. Many of those cases where someone regains eyesight happens much later in life, at a time when their brains have largely matured to the point that neuroplasticity is pretty much over for them. Having someone's brain develop with almost no visual input at a young age is bound to mean that their visual cortex and its connections to everything else doesn't develop as it should.
From a quick search, it appears that to some degree children born categorically blind can recover all the way up to teenage life. [1] But indeed it's likely less effective than a younger child undergoing a similar procedure (which I don't think is really that rare: it's hard to diagnose vision problems at young age, and a lot of children who get necessary corrective surgery at young age turn out fine).
You brain already knows how to select the most important features of a sign. The shape, the size and the color. You have also learned how to understand the text on the sign.
A new born baby does not have that ability.
This is applied in ANN as well. Transfer learning is using a pre-trained neural network, which has already learned identifying objects, and then using it to train on identifying a new, usually smaller, set of objects using, usually, a lot less training data. That is what Andrew is talking about in the article.