How Google Is Remaking Itself for “Machine Learning First”
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How Google Is Remaking Itself for “Machine Learning First”
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Re: How Google Is Remaking Itself for “Machine Learning First”
#2This is a really great idea, especially when done right. The difficulty with machine learning and AI is understanding the pitfalls inherent in selecting data and training systems. You can fool yourself pretty easily into thinking you've got something that works when you really don't. That said it sounds like they're doing things well, I have no doubt this will have a positive impact in demystifying the "magic" of ML/AI and making all those Google products I use better!
Re: How Google Is Remaking Itself for “Machine Learning First”
#3This is a really great idea, especially when done right. The difficulty with machine learning and AI is understanding the pitfalls inherent in selecting data and training systems. You can fool yourself pretty easily into thinking you've got something that works when you really don't. That said it sounds like they're doing things well, I have no doubt this will have a positive impact in demystifying the "magic" of ML/…
"And then (this is hard for coders) trusting the systems to do the work."
Like you say, it can be easy to think that something works when it really doesn't. I hope that the above quote isn't meant to be interpreted as "believe the results are correct." Evaluation is paramount when working on these systems to avoid making such mistakes. I assume Google is including evaluation in their machine learning training, but it would have been nice to see that pointed out in the article for folks who may have an interest in machine learning but don't know what's important to focus on.
Re: How Google Is Remaking Itself for “Machine Learning First”
#4Great article, but I can't help but CRINGE at the "ninja" references. I think that's already played out within the industry... and although pop-tech writers tend to lag a few years behind, it will sound extremely dated in the mainstream within a few years.
Re: How Google Is Remaking Itself for “Machine Learning First”
#5And my anecdotal experience is that it's working extremely well. Take the Google Photos app that does automatic image recognition and tagging. The other day I was looking for a picture we took of our cat the first night we brought him home. I remembered we left him with a blanket in the bathroom but couldn't remember much else.
"kitten bathroom 2013"
And there was a picture of the cat sitting in the tub on a blanket. Simply amazing.
Re: How Google Is Remaking Itself for “Machine Learning First”
#6Great article, but I can't help but CRINGE at the "ninja" references. I think that's already played out within the industry... and although pop-tech writers tend to lag a few years behind, it will sound extremely dated in the mainstream within a few years.
That first paragraph almost made me stop reading.
Re: How Google Is Remaking Itself for “Machine Learning First”
#7Not sure where it is going at all: evolutionary leaps often come from outliers and sometimes from serendipity. What about this reinforced confirmation bias?
Re: How Google Is Remaking Itself for “Machine Learning First”
#8And my anecdotal experience is that it's working extremely well. Take the Google Photos app that does automatic image recognition and tagging. The other day I was looking for a picture we took of our cat the first night we brought him home. I remembered we left him with a blanket in the bathroom but couldn't remember much else. "kitten bathroom 2013" And there was a picture of the cat sitting in the tub on a blanket.…
Strangely, half the time I try to use Google Now on my phone, it doesn't seem to understand basic queries that worked two years ago. And in the meanwhile, features and APIs that used to allow more reliable and explicit control (e.g. like in Picasa) are being shut down. I guess someone at Google figured that imitating Apple is worth sacrificing what remained of their power user appeal.
Re: How Google Is Remaking Itself for “Machine Learning First”
#9Anyone happen to have a suggested self-teaching path for Machine Learning? I.e. books and courses. I know that Andrew Ng's course is a great resource, but I know that I'm not ready to start it yet. I'm actually way behind on the mathematical pre-requisites, so recommendations for that would be greatly appreciated as well. I've never taken a statistics course, and never received any formal education for mathematics past trig. I know that I'm looking at a good 6 months to a year just to get caught up on the math alone.
Re: How Google Is Remaking Itself for “Machine Learning First”
#10That's a good change from "social first" from a few years back. Google was never a social company to start with. Remember Orkut?
AI is google's leverage. It should explore on that path.