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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”

#11

Post by stcredzero »

cxseven wrote: post #8
matt_wulfeck wrote: post #5

And 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.

I guess someone at Google figured that imitating Apple is worth sacrificing what remained of their power user appeal.

"Sacrificing what remained of their power user appeal" is imitating Apple!

Re: How Google Is Remaking Itself for “Machine Learning First”

#12

Post by lugg »

StevePerkins wrote: post #4

Great 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.

> “The tagline is, Do you want to be a machine learning ninja?”

I don't really like the word, but I don't really give a flop either.

I'm not sure how its better or worse than guru, rockstar, or any other lame word recruiters like to use to make us feel like the special snowflakes we are.

Which word would you like to see in place of 'ninja'?

Re: How Google Is Remaking Itself for “Machine Learning First”

#13

Post by StevePerkins »

lugg wrote: post #12
StevePerkins wrote: post #4

Great 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.

> “The tagline is, Do you want to be a machine learning ninja?” I don't really like the word, but I don't really give a flop either. I'm not sure how its better or worse than guru, rockstar, or any other lame word recruiters like to use to make us feel like the special snowflakes we are. Which word would you like to see in place of 'ninja'?

I'd rather see all of those juvenile testosterone labels discarded in general.

Sheesh... "Do you want to make the world a better place?", with a photo of Gavin Belson holding an animal, would make me more inspired.

Re: How Google Is Remaking Itself for “Machine Learning First”

#14

Post by rhizome »

DrNuke wrote: post #7

Not sure where it is going at all: evolutionary leaps often come from outliers and sometimes from serendipity. What about this reinforced confirmation bias?

On first blush, my sense is that a translation could go something like "we're prioritizing the analytics API over the results API." Not analytics in the webserver sense, but the OLAP/DW one. So, e.g. ad targeting fidelity over results presentation algorithms. Backend biz vs frontend.

Re: How Google Is Remaking Itself for “Machine Learning First”

#15

Post by rhizome »

lugg wrote: post #12
StevePerkins wrote: post #4

Great 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.

> “The tagline is, Do you want to be a machine learning ninja?” I don't really like the word, but I don't really give a flop either. I'm not sure how its better or worse than guru, rockstar, or any other lame word recruiters like to use to make us feel like the special snowflakes we are. Which word would you like to see in place of 'ninja'?

The word "ninja" in recruiting was almost dead before today.

Re: How Google Is Remaking Itself for “Machine Learning First”

#16

Post by liyanage »

xenihn wrote: post #9

Anyone 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 pa…

You can work through the Coursera variant of Andew Ng's course without a deep math background: https://www.coursera.org/learn/machine-learning

More in-depth videos of the course are on YouTube: https://www.youtube.com/playlist?list=PLA89DCFA6ADACE599

Re: How Google Is Remaking Itself for “Machine Learning First”

#17

Post by sputknick »

xenihn wrote: post #9

Anyone 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 pa…

Six months ago, I would have said Kaggle, Juptyer, Python, figure things out. I've since discovered Microsoft's ML Studio. It allows you to start out with drag and drop (no code to learn) and, most importantly, you can visually see the output of your experiments. For example if you run a binary decision tree algorithm you can actually look at images of the 1000 trees it created and what the nodes from them is. Not important for practical functioning in the real world, but I like it a lot as a tool to learn.

Re: How Google Is Remaking Itself for “Machine Learning First”

#18

Post by Animats »

lugg wrote: post #12
StevePerkins wrote: post #4

Great 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.

> “The tagline is, Do you want to be a machine learning ninja?” I don't really like the word, but I don't really give a flop either. I'm not sure how its better or worse than guru, rockstar, or any other lame word recruiters like to use to make us feel like the special snowflakes we are. Which word would you like to see in place of 'ninja'?

Well, if she's a black belt 2nd dan in a martial art, she's entitled.

Re: How Google Is Remaking Itself for “Machine Learning First”

#19

Post by argonaut »

xenihn wrote: post #9

Anyone 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 pa…

You should start with an intro calculus class (e.g. Calculus I). Andrew Ng's Coursera course teaches you the necessary linear algebra. After his Coursera course it'll be worthwhile to take a linear algebra class.
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