It seemed really amazing that you could write a few lines of code and have it learn to do interesting things.
Andrew NgRead
AI has been making tremendous progress in machine translation, self-driving cars, etc. Basically, all the progress I see is in specialised intelligence. It might be hundreds or thousands of years or, if there is an unexpected breakthrough, decades.
Interpretation
AI advancements are largely seen in specialized areas, with general intelligence remaining distant.
In this quote, Andrew Ng highlights the significant progress made in artificial intelligence, particularly in specialized fields like machine translation and self-driving cars. However, he emphasizes that true general intelligence, akin to human-like cognition, may still be far off, potentially taking centuries unless an unforeseen breakthrough occurs.
In practice
During a tech conference to explain the current state of AI development.
It seemed really amazing that you could write a few lines of code and have it learn to do interesting things.
Most of the value of deep learning today is in narrow domains where you can get a lot of data. Here's one example of something it cannot do: have a meaningful conversation.
Imagine if we can just talk to our computers and have it understand, 'Please schedule a meeting with Bob for next week.' Or if each child could have a personalized tutor. Or if self-driving cars could save all of us hours of driving.
A single neuron in the brain is an incredibly complex machine that even today we don't understand. A single 'neuron' in a neural network is an incredibly simple mathematical function that captures a minuscule fraction of the complexity of a biological neuron.
None of us today know how to get computers to learn with the speed and flexibility of a child.
I've been to so many manufacturing plants. I've yet to walk into one where I did not think AI solutions wouldn't help.
What the computer in virtual reality enables us to do is to recalibrate ourselves so that we can start seeing those pieces of information that are invisible to us but have become important for us to understand.
We are now living in a completely digitalized world and a completely globalized world, so we have to find some new mechanisms and values to deal with this post-digitalized and post-globalized world.
The only reason we don't notice how absolutely interwoven our thinking processes have become with older technologies - pencils, paper, electric light, penicillin, fire - is that they're old, so we've ceased to notice their effects.
We are all now connected by the Internet, like neurons in a giant brain.
What I think is coming instead are much more organic ways of organizing information than our current categorization schemes allow, based on two units - the link, which can point to anything, and the tag, which is a way of attaching labels to links. The strategy of tagging - free-form labeling, without regard to categorical constraints - seems like a recipe for disaster, but as the Web has shown us, you can extract a surprising amount of value from big messy data sets.
Every time a new technology comes along, we feel we're about to break through to a place where we will not be able to recover. The advent of broadcast radio confused people. It delighted people, of course, but it also changed the world.
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