Most of the people who fear of AI taking over, like Terminator and stuff like that usually have little or no knowledge of machine learning or neural networks.
Us coders usually feel safe cuz we pretty much understand how it works and what drives it. I feel bad for some people who might have nightmares about this😄.
To reduce the possible dangers of AI as a Terminator scenario is, to me, on itself reductive and ill-informed, and no, we don't understand exacly how it works, that's the point. AI purpose is to "make the algorithm" on its own, if we understood exactly how it works we wouldn't need the AI in the first place. We have an idea on how to feed and with what data to train, but the resulting algorithm is not understood, you could reverse-engineering based on the result but is not necesary. (more in my other comment)
Peter is the former President of the New Zealand Open Source Society. He is currently working on Business Workflow Automation, and is the core maintainer for Gravity Workflow a GPL workflow engine.
I've been following artificial intelligence since I was a boy in about 1985. I'm quite well informed about classic AI approaches and the current crop of Deep Learning systems. Prior to 2012 neural networks had fallen out of favour. In fact I don't know of any neural network technology used for real world applications prior to 2012. Deep Learning or deep neural networks along with big data and GPUs convirging have made it possible to build and deploy commercially successful AI.
But it isn't programming, rather it is cleaning and piping data into a predictive neural network which usually classifies. The surprising thing is that this is astonishingly effective in solving problems such as visual recognition that are impossible for programmed solutions.
Look at how fast the barriers fell down and how quickly many applications have been developed to leverage this kind of capability. Further, we got something fudamentally right with neural networks. It wasn't just a faster processor or larger RAM. There was a fundamental shift in capability by using existing technology in a new way that was orthogonal to traditional software development.
But we have not arrived at human level intelligence yet. But how far away is it? Well in 1982 I got my first PC, a ZX81 with 1K of RAM and a clock speed in the Khz range. That was about 40 years ago. Before the Internet was available to me, before hard drives were on home computers. I want to exphasise this difference because if you think that we will achieve less in the next 50 years than we have in the last 40 I have news for you.
The barrier to human level instelligence isn't hardware. There are a few key problems right now, but if solved I would expect human level intellilect to become pervasive almost overnight, just as voice recogntion has in smart phones. Even without such advances AI is already presenting harms. We have already surrendered to facebook and YouTube. Machines already control the information re receive and who we can communicate with. AI is now deeply entrenched in these systems. And it is only going to get smarter.
Hey I didn't mean to be offensive or anything 😅. I think I owe a correction. We don't "know exactly how it works", but we understand what drives it, at least. I meant like we have to provide it with material from which it has to train from before becoming 'intelligent'.
What I tried to say about non-coder people is that some of them over-estimate and that the word "taking over" doesn't really suite here. But people who build up a neural network, who code the algorithms, know to a pretty good extent as to what their AI can do and what it cannot.
Try checking out this documentary to clarify more about what I'm talking about youtu.be/WXuK6gekU1Y . It's an AI that beat the best human player of a game called "Go". See what the team members have to say when the press becomes concerned about the AI after the human player lost three consecutive games.
Once again, I deeply apologize if I offended anyone🙏🙏🙏. Hope I clarified the misunderstanding.
Happy Coding!
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Well, if you understand everything about deep learning, neural networks etc, please, explain it to me... or better write a paper, you'll be some kinda famous, as there are some parts of the "AI world" or concept that experts don't know why it works exactly and why it works as it does 😄.
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Most of the people who fear of AI taking over, like Terminator and stuff like that usually have little or no knowledge of machine learning or neural networks.
Us coders usually feel safe cuz we pretty much understand how it works and what drives it. I feel bad for some people who might have nightmares about this😄.
Nice article, btw...
To reduce the possible dangers of AI as a Terminator scenario is, to me, on itself reductive and ill-informed, and no, we don't understand exacly how it works, that's the point. AI purpose is to "make the algorithm" on its own, if we understood exactly how it works we wouldn't need the AI in the first place. We have an idea on how to feed and with what data to train, but the resulting algorithm is not understood, you could reverse-engineering based on the result but is not necesary. (more in my other comment)
I've been following artificial intelligence since I was a boy in about 1985. I'm quite well informed about classic AI approaches and the current crop of Deep Learning systems. Prior to 2012 neural networks had fallen out of favour. In fact I don't know of any neural network technology used for real world applications prior to 2012. Deep Learning or deep neural networks along with big data and GPUs convirging have made it possible to build and deploy commercially successful AI.
But it isn't programming, rather it is cleaning and piping data into a predictive neural network which usually classifies. The surprising thing is that this is astonishingly effective in solving problems such as visual recognition that are impossible for programmed solutions.
Look at how fast the barriers fell down and how quickly many applications have been developed to leverage this kind of capability. Further, we got something fudamentally right with neural networks. It wasn't just a faster processor or larger RAM. There was a fundamental shift in capability by using existing technology in a new way that was orthogonal to traditional software development.
But we have not arrived at human level intelligence yet. But how far away is it? Well in 1982 I got my first PC, a ZX81 with 1K of RAM and a clock speed in the Khz range. That was about 40 years ago. Before the Internet was available to me, before hard drives were on home computers. I want to exphasise this difference because if you think that we will achieve less in the next 50 years than we have in the last 40 I have news for you.
The barrier to human level instelligence isn't hardware. There are a few key problems right now, but if solved I would expect human level intellilect to become pervasive almost overnight, just as voice recogntion has in smart phones. Even without such advances AI is already presenting harms. We have already surrendered to facebook and YouTube. Machines already control the information re receive and who we can communicate with. AI is now deeply entrenched in these systems. And it is only going to get smarter.
Sweet dreams.
Great answer, thanks for sharing your knowledge on AI. True.
Hey I didn't mean to be offensive or anything 😅. I think I owe a correction. We don't "know exactly how it works", but we understand what drives it, at least. I meant like we have to provide it with material from which it has to train from before becoming 'intelligent'.
What I tried to say about non-coder people is that some of them over-estimate and that the word "taking over" doesn't really suite here. But people who build up a neural network, who code the algorithms, know to a pretty good extent as to what their AI can do and what it cannot.
Try checking out this documentary to clarify more about what I'm talking about youtu.be/WXuK6gekU1Y . It's an AI that beat the best human player of a game called "Go". See what the team members have to say when the press becomes concerned about the AI after the human player lost three consecutive games.
Once again, I deeply apologize if I offended anyone🙏🙏🙏. Hope I clarified the misunderstanding.
Happy Coding!
Well, if you understand everything about deep learning, neural networks etc, please, explain it to me... or better write a paper, you'll be some kinda famous, as there are some parts of the "AI world" or concept that experts don't know why it works exactly and why it works as it does 😄.