Inside Google Brain
wired.com
Inside Google Brain
1–10 of 77 posts
Re: Inside Google Brain
#2I knew this was a Wired article without even looking at the URL.
Re: Inside Google Brain
#3It seems they missed mentioning Ray Kurzweil, the AI master who's a Director of Engineering at Google.
Re: Inside Google Brain
#4It seems they missed mentioning Ray Kurzweil, the AI master who's a Director of Engineering at Google.
To clarify, Ray is a director, not the director. Google has many engineering directors.
Re: Inside Google Brain
#5"They’ve also found that the models tend to become more accurate the more data they consume. That may be the next big goal for Google: building AI models that are based on billions of data points, not just millions. "
I'm not versed in machine learning, but it looks to me that any model whose output quality is dependent on the quantity of data it ingests is deeply flawed. There's no doubt a bigger number of samples will make the predictions more accurate, but isn't the challenge to develop a system that is as accurate as possible regardless of the number of data points its fed, like the human brain?
Re: Inside Google Brain
#6I knew this was a Wired article without even looking at the URL.
I really don't know who buys Wired... despite it being a quality publication on the whole it seems far too dumbed down for real geeks and too niche for the layman. I imagine it ends up on the reception table of lots of startups and desgin agencies who want to some glossy 'we do technology' badge.
Re: Inside Google Brain
#7"They’ve also found that the models tend to become more accurate the more data they consume. That may be the next big goal for Google: building AI models that are based on billions of data points, not just millions. " I'm not versed in machine learning, but it looks to me that any model whose output quality is dependent on the quantity of data it ingests is deeply flawed. There's no doubt a bigger number of samples w…
Until you have reached a very large subset of all available information, more data allows you to make better predictions. Period. That is as true for machine learning as it is of the human brain.
You often want your models to also perform well when you have fewer data points. Those are two separate - if in effect related - design goals.
Re: Inside Google Brain
#8"They’ve also found that the models tend to become more accurate the more data they consume. That may be the next big goal for Google: building AI models that are based on billions of data points, not just millions. " I'm not versed in machine learning, but it looks to me that any model whose output quality is dependent on the quantity of data it ingests is deeply flawed. There's no doubt a bigger number of samples w…
If you think human brain is so sophisticated that it can perform its cognitive duties with little data, this is simply wrong. While it is definitely not a simple organic construct, it does get stimulated significantly all the time. See [1] what happens when you cut out this factors.
Regarding artificial systems, I think more data is the only way to reach super-performing classifiers. The data you supply doesn't have to be big but at least the data you extract from raw data should be big. For example, a method called Integral Channel Features [2] is designed to act in such a way.
[1] http://en.wikipedia.org/wiki/Sensory_deprivation
[2] http://pages.ucsd.edu/~ztu/publication/dollarBMVC09ChnFtrs_0...
Re: Inside Google Brain
#9"They’ve also found that the models tend to become more accurate the more data they consume. That may be the next big goal for Google: building AI models that are based on billions of data points, not just millions. " I'm not versed in machine learning, but it looks to me that any model whose output quality is dependent on the quantity of data it ingests is deeply flawed. There's no doubt a bigger number of samples w…
Re: Inside Google Brain
#10It seems they missed mentioning Ray Kurzweil, the AI master who's a Director of Engineering at Google.
To clarify, Ray is a director, not the director. Google has many engineering directors.
Corrected it. But I do think he deserves a mention when talking about AI and Google in particular.