Apple Hires AI Expert Ian Goodfellow (cnbc.com) 38
One of Google's top minds in artificial intelligence has joined Apple in a director role. Ian Goodfellow said on his LinkedIn profile that he switched employers in March. He said he's a director of machine learning in the Special Projects Group. CNBC reports: Goodfellow is the father of an AI approach known as generative adversarial networks, or GANs. The approach draws on two networks, one known as a generative network and the other known as a discriminative network, and can be used to come up with unusual and creative outputs in the form of audio, video and text. GAN systems have been used to generate "deepfake" fake media content.
Goodfellow got his Ph.D. at the University of Montreal in 2014, and since then he has worked at OpenAI and Google. At OpenAI he was paid more than $800,000, according to a tax filing. His research is widely cited in academic literature. At Google Goodfellow did work around GANs and security, including an area known as adversarial attacks. People working on AI at Apple have previously done research that drew on the GAN technology.
Goodfellow got his Ph.D. at the University of Montreal in 2014, and since then he has worked at OpenAI and Google. At OpenAI he was paid more than $800,000, according to a tax filing. His research is widely cited in academic literature. At Google Goodfellow did work around GANs and security, including an area known as adversarial attacks. People working on AI at Apple have previously done research that drew on the GAN technology.
*Generative* Adversarial Networks (Score:5, Informative)
I know it's from TFA's headline, but GFA is "Generative Adversarial Networks", not what they said.
GANs are the biggest leap in AI in decades (Score:2)
I think the reason AI is suddenlt leaping forward after being stallaed for decades is
1. almost entirely because computers are faster now. Especially because GPUs are faster. And specifically because of all machine learning algorithms out there the one that maps to matrix multiplies most easily is the Neural Net. It was just waiting for a graphics card with enough speed and memory to reach a practical scale.
2. Almost all mchachine learning is a refinement of past ideas. But GANs, seem to me to be the bi
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Hinton and company created a method that gets around that major issue, and it is that method that led to the explosion of successful application of NN's to various problems in the last 10 years.
For example, prior to the deep learning algorithm, the best image recognition was from a
The 30 year old 'expert' with +40 years experience (Score:2)
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Not so much any more. This is solid indication of bailout of non-violent persons who have no interest in working for Death Incorporate, the US War Industrial Complex, are bailing on Google, the technologists of Death Incorporated, whilst trying to skull behind ethicsvertising and outed by Donald Trump himself. Google don't be evil, FOR FREE.
A lot more Googlites will be seeking to bail out the evil Google and recruiting from there will be a lot easier. Hardly surprising Apple is now able to pick the best fro
Did you just say he was like Isaac Newton? (Score:3)
he build his 'unique' expertise on the work of others...
Hey you know who else did that?
If I have seen further than others, it is by standing upon the shoulders of giants.
-Issac Newton.
Hey you know who ELSE has done that?
Anyone who has ever used StackOverflow to find an answer.
Don't knock building expertise on what others before you have done.
How is that not realistic (Score:2)
Somehow 5 years later he is an "industry leader in machine learning"?
That seems very doable to me, given how recent a lot of the modern approaches to machine learning are... that is in fact about the right time that if you went into applying machine learning around five years ago, you could easily be a leading expert at this point.
My thought is, the proof is in the hire. Lots of people here spouting a lot of trash but two high level companies agree he's an expert. That sounds a lot more informative than
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Somehow 5 years later he is an "industry leader in machine learning"?
Perhaps it had something to do with publishing original research that revolutionized machine learning.
Remember hearing about Alphazero defeating the world's Go champion? That was based on a GAN, which Ian invented.
He also wrote the definitive book on deep learning [amazon.com] which anyone in the field should read. Twice.
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In regular co-evolution you'd generally have a cost/fitness function to judge fitness by. Evolutionary algorithms are essentially optimizers that do well with non-convex problems.
GANs were invented to answer the question "what do you do when you don't know what the cost function is?" in the particular circumstance when you want to build a generative model. You want the output of your generative model to be as much as possible like a true example, but it's difficult to properly measure similarity. There are
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That's a good point. I think selection by viability implies some kind of fitness function embedded in the environment, but it doesn't have to be fixed, simple, or explicit.
I suspect you could look at GANs in a few different ways in a co-evolutionary framework. Goodfellow presents them as adversarial (it's even in the name) and gives the example of an art forger (the generator) and an art authenticator (the critic). That's kind of a predator-prey setup. Personally, I think a better way to look at it is more
Idoru (Score:4, Insightful)
Is it just me, or does "AI expert Ian Goodfellow" sound like a character from a William Gibson novel?