Awww, upset the snowflake with some basic questions. I was under the impression that AI was just around the corner. Turns out we need to train programs for every conceivable combination of possibilities. You guys better get started!
So you need to create a machine learning program for each thing it needs to be trained on? There are many billions of objects. How long is this going to take? And once you are able to produce a computer that can recognize a fish in long grass, we have AI, right?
So once the machine breaks down an image as a number of objects, it can them magically know which objects are sheep and which objects are grass? How does it know if an object is a sheep versus a fence post? Why didn't it work in this case? Did the researchers not do it right?
That is interesting. So the AI was biased because it preferred black and white fence posts in the ground to sheep? Did you have problems recognizing sheep in the pictures? If not, why didn't you? After all, you have biases.
So do you need to train an AI to recognize every object separately? There are many billions of different objects. How long is this going to take? They seem to have a hard time training it to recognize sheep. When is someone going to work on that?
Well that is truly weird. I was under the impression that AI was right around the corner. So do you need to train it again to have it recognize sheep? And then again to have it recognize airplanes? How long is this going to all take?
So why haven't we been able to create a neural net that approximates what a simple animal brain can do? Are neural networks new, and we are just starting to learn how to use them?
So the problem is not enough training data? How many pictures of sheep do you need in order to recognize a sheep reliably? Did the researchers not have enough pictures of sheep?
They do work in the same way? Then why can't it recognize sheep? A two year old can. So you are saying if we just make the neural net larger, it will be able to recognize sheep in a picture? Why hasn't anyone done that? Neural networks have been around since the 1940s. Did no one think of just making them larger. Fascinating!
So if you show your 4 year old a sheep on a blank background, or in a car, they won't tell you it is a "sheep"? Does your 4 year old get confused when watching "Shaun the Sheep" movies because sometimes it shows the main character in a city?
Oh I hope so. Neural networks were first described over 60 years ago. I am sure that eventually they will have one that can recognize sheep as well as a chicken can! So, another 60 years or so?
Wait wait wait. "Applied to recognizing written characters"? That sounds like a computer program to me. Do I need to use a different net to make it recognize sheep instead? Two year old children can recognize characters AND sheep AND plants AND cars. Why do you need a special NN for each one of those tasks?
Really? In which picture did you have problems seeing/not seeing sheep? Are you saying that the computers were not given enough time to run their AI because they were overworked with the number of samples?
So you are saying that the system was only given a vague description of "sheep farming" and wasn't given enough time to decide if they were posts in the ground or sheep? You weren't able to discern if the pictures were sheep or not?
Why are the algorithms so primitive? Are neural networks new? The concept of neural networks was invented in the 1940s. Why can't they recognize sheep yet?
Surely "neural networks" are similar to how real brains work, right? I mean they call them "neural", which means "like a neuron" and a network of them is like a human brain, which is a network of physical neurons. So, neural networks are like human brains. After all, a two year old can recognize sheep. Surely a computer can. It is 2018 and neural networks have been around for 40 years now. AI is right around the corner, right? Just needs to tweaking to make the learning "deeper".
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Really? We were studying them in university 30 years ago. What community was that?
Awww, upset the snowflake with some basic questions. I was under the impression that AI was just around the corner. Turns out we need to train programs for every conceivable combination of possibilities. You guys better get started!
So you need to create a machine learning program for each thing it needs to be trained on? There are many billions of objects. How long is this going to take? And once you are able to produce a computer that can recognize a fish in long grass, we have AI, right?
So once the machine breaks down an image as a number of objects, it can them magically know which objects are sheep and which objects are grass? How does it know if an object is a sheep versus a fence post? Why didn't it work in this case? Did the researchers not do it right?
That is interesting. So the AI was biased because it preferred black and white fence posts in the ground to sheep? Did you have problems recognizing sheep in the pictures? If not, why didn't you? After all, you have biases.
What human would call a sheep a dog just because it was inside a house? I don't know any human that would do that.
So do you need to train an AI to recognize every object separately? There are many billions of different objects. How long is this going to take? They seem to have a hard time training it to recognize sheep. When is someone going to work on that?
Well that is truly weird. I was under the impression that AI was right around the corner. So do you need to train it again to have it recognize sheep? And then again to have it recognize airplanes? How long is this going to all take?
We have been training neural networks for over 40 years now. Why can't they recognize sheep yet? What progress has there been?
So, you are saying the computer needs glasses? AI is a fascinating field!
Wait, so you are saying that the AI neural net in this case was never taught was a sheep looked like? This was an "untrained" neural net? Fascinating!
So why haven't we been able to create a neural net that approximates what a simple animal brain can do? Are neural networks new, and we are just starting to learn how to use them?
So the problem is not enough training data? How many pictures of sheep do you need in order to recognize a sheep reliably? Did the researchers not have enough pictures of sheep?
They do work in the same way? Then why can't it recognize sheep? A two year old can. So you are saying if we just make the neural net larger, it will be able to recognize sheep in a picture? Why hasn't anyone done that? Neural networks have been around since the 1940s. Did no one think of just making them larger. Fascinating!
That can't be. These are "deep learning neural networks". Surely they work like the brain works. Otherwise, why would they call them that?
So if you show your 4 year old a sheep on a blank background, or in a car, they won't tell you it is a "sheep"? Does your 4 year old get confused when watching "Shaun the Sheep" movies because sometimes it shows the main character in a city?
Oh I hope so. Neural networks were first described over 60 years ago. I am sure that eventually they will have one that can recognize sheep as well as a chicken can! So, another 60 years or so?
Wait wait wait. "Applied to recognizing written characters"? That sounds like a computer program to me. Do I need to use a different net to make it recognize sheep instead? Two year old children can recognize characters AND sheep AND plants AND cars. Why do you need a special NN for each one of those tasks?
So you are saying that the computer wasn't given enough time to run its AI program?
Really? In which picture did you have problems seeing/not seeing sheep? Are you saying that the computers were not given enough time to run their AI because they were overworked with the number of samples?
So you are saying that the system was only given a vague description of "sheep farming" and wasn't given enough time to decide if they were posts in the ground or sheep? You weren't able to discern if the pictures were sheep or not?
Why are the algorithms so primitive? Are neural networks new? The concept of neural networks was invented in the 1940s. Why can't they recognize sheep yet?
"They're merely self-optimizing systems tuned to a specific task."
Wait, so you're telling me that machine learning is just a program running an optimization for a particular task? So, just computers running programs?
Surely "neural networks" are similar to how real brains work, right? I mean they call them "neural", which means "like a neuron" and a network of them is like a human brain, which is a network of physical neurons. So, neural networks are like human brains. After all, a two year old can recognize sheep. Surely a computer can. It is 2018 and neural networks have been around for 40 years now. AI is right around the corner, right? Just needs to tweaking to make the learning "deeper".
I agree. So why do so many conservative Christians get caught participating in such deviant behavior? The list is endless.