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Google launches an end-to-end AI platform

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Re: Google launches an end-to-end AI platform

#71

Post by m0zg »

mlthoughts2018 wrote: post #69
m0zg wrote: post #59

Earlier quoted context omitted.

>> It’s so disingenuous for Google to brand >> these efforts as “democratizing AI.” Exactly. NVIDIA building fast consumer GPUs and CUDA/cuDNN is "democratizing AI". FB (and Google) releasing open source deep learning toolkits is "democratizing AI". People releasing reproducible research code and datasets are "democratizing AI". Cloud vendor lock-in and proprietary hardware, software, _and_ datasets is not in any way…

I agree with you that the supply of those workers is low (I am one of them! And hiring more is extremely hard!) ... but it doesn’t mean Google / FB / etc have meaningful work for them. A friend of mine was hired as a senior ML person at Facebook and ended up working solely on cartoon avatars and page responsiveness / latency optimization (not using ML). When he raised the issue to managers that he wasn’t working on a…

As an ex-Googler, that's not how you're supposed to operate at those companies. You find something you like to do, talk to the team, ensure the other team has open spots and would like to take you on, and move your shit from one desk to the other. Done. You're working on your specialization, if that's what you like to do.

Discussing stuff with your manager is utterly pointless because your interests aren't really aligned. You want to do something else. Your manager wants you to do whatever you're doing now because finding a replacement for you is a bit of a pain in the ass. She gets no brownie points if you leave.

It is true that Google has a ton of PhDs who just copy one protobuffer into another and browse memegen all day while earning half a million dollars a year. But they also have a ton of PhDs who do meaningful work, too. It's not really Google's problem that someone can't be bothered to look around and find something meaningful for themselves to do. Or to be more exact, it is a problem _for_ Google, because there are a lot of people who can be deployed in higher leverage occupations, but not one that Google itself can solve, because one of the main tenets of how they operate is _nobody tells you what to do_. You're supposed to figure it out on your own. A lot of people can't deal with that.

Re: Google launches an end-to-end AI platform

#72

Post by agentofoblivion »

jedberg wrote: post #46

This is where Google really has a big lead on AWS -- the AI space. AWS has AI tools, but Google's are better and easier to use. The big question is: If all your data sits in AWS, because your app that generates the data is there, do you reach across and try to use the Google AI tools, or are their tools compelling enough to get you to move your app and all your data to GCS?

What AI tools? SageMaker is awesome. What can Google do for me? All I've seen from them is marketing hype. I also haven't looked very hard.

Re: Google launches an end-to-end AI platform

#73

Post by agentofoblivion »

mlthoughts2018 wrote: post #69
m0zg wrote: post #59

Earlier quoted context omitted.

>> It’s so disingenuous for Google to brand >> these efforts as “democratizing AI.” Exactly. NVIDIA building fast consumer GPUs and CUDA/cuDNN is "democratizing AI". FB (and Google) releasing open source deep learning toolkits is "democratizing AI". People releasing reproducible research code and datasets are "democratizing AI". Cloud vendor lock-in and proprietary hardware, software, _and_ datasets is not in any way…

I agree with you that the supply of those workers is low (I am one of them! And hiring more is extremely hard!) ... but it doesn’t mean Google / FB / etc have meaningful work for them. A friend of mine was hired as a senior ML person at Facebook and ended up working solely on cartoon avatars and page responsiveness / latency optimization (not using ML). When he raised the issue to managers that he wasn’t working on a…

I just want to say that if this describes anyone that's reading this, then please join us at AWS. We're doing a ton of ML, and your talents won't be wasted.

Sitting around and stagnating your career for a nice salary is a profoundly short-sighted thing to do.

Re: Google launches an end-to-end AI platform

#74

Post by ed_balls »

siavash wrote: post #35

Make sure you've read the service terms[1] if you plan on building apps for speakers, cars, TVs or smart watches... 12.1 The following terms apply only to current and future Google Cloud Platform Machine Learning Services specifically listed in the "Google Cloud Platform Machine Learning Services Group" category on the Google Cloud Platform Services Summary page: Customer will not, and will not allow third parties to…

I can understand cars but TVs?

Re: Google launches an end-to-end AI platform

#75

Post by tareqak »

ed_balls wrote: post #74
siavash wrote: post #35

Make sure you've read the service terms[1] if you plan on building apps for speakers, cars, TVs or smart watches... 12.1 The following terms apply only to current and future Google Cloud Platform Machine Learning Services specifically listed in the "Google Cloud Platform Machine Learning Services Group" category on the Google Cloud Platform Services Summary page: Customer will not, and will not allow third parties to…

I can understand cars but TVs?

Google Chromecast and any possible offering that could compete with a future Google TV.

Re: Google launches an end-to-end AI platform

#76

Post by blihp »

pplonski86 wrote: post #21
petard wrote: post #14

This will make a bunch of startup's life really hard. I think it makes it harder to justify investing in your own ML pipeline or even building your own models for many use cases.

I'm running a startup which offers the same solution as Google AuotML Tables. Recently I decided to go open source. I will need to compare my solution with Google AutoML Tables (compare in terms of final model accuracy). But anyway I think many times the best model accuracy is not the most important in ML solutions. Any ideas what can I do with such a situation with my solution? Can I compete with Google?

Go vertical rather than horizontal with your solution. Google, and the other large players, need broad swaths of customers/users to get to a viable total addressable market at their scale. That is your advantage over them: you can survive and thrive in much smaller markets. Also, see ricklamers take in this thread (https://news.ycombinator.com/user?id=ricklamers)... it's not the be-all, end-all and never will be. If you've already decided to open source your tools, then is that really even your primary value add[1] or is it some expertise/service on top of your tools? Figure out what that is, be a cockroach and find a market that's too small for them to be bothered with and then super-serve that market.

[1] If the tool is your primary value add, I think you're making a mistake in open sourcing it.

Re: Google launches an end-to-end AI platform

#77

Post by eanzenberg »

streetcat1 wrote: post #63
eanzenberg wrote: post #50

Earlier quoted context omitted.

Most people including ones here don't understand the value prop. In ML, the model (and modeling) is an afterthought that takes 3 lines of code. The value-add isn't the model or modeling, it's the feature generation and methodology. When (and if) this gets automated then yes, it will make life hard on many data scientists. But I don't see it happening within 20 years and most likely not within my lifetime.

I am not sure why you do not see that happening. Driverless AI from h2o does a full feature engineering search. Also, I assume that you want to automate the features search in order to prune the non signal. I am not sure what you mean by methodology? The one thing that I, as a tool developer, do not understand is how humans would be able to handle hundreds of models, including retraining/monitoring and deployment wit…

Not every AI problem is computer vision or NLP.

Re: Google launches an end-to-end AI platform

#78

Post by sodosopa »

zeroxfe wrote: post #49
jimrandomh wrote: post #43

Earlier quoted context omitted.

I have a hard time imagining who this wouldn't be a dealbreaker for. These terms also mean you can't use it for open source, and you can't use it if you don't know what the ultimate application is going to be. And you probably can't resell technology you create, because no one who buys it is going to want that restriction, either.

It's not a dealbreaker for in-house ML applications particularly in the enterprise (banks, telcos, etc.), which is a huge market for cloud providers.

That's how my company would apply the platform to our work. My boss is there now, will be interesting to see what he find out vs what we're doing with our current IBM platform.

Re: Google launches an end-to-end AI platform

#80

Post by sodosopa »

holoduke wrote: post #44
pplonski86 wrote: post #21

Earlier quoted context omitted.

I'm running a startup which offers the same solution as Google AuotML Tables. Recently I decided to go open source. I will need to compare my solution with Google AutoML Tables (compare in terms of final model accuracy). But anyway I think many times the best model accuracy is not the most important in ML solutions. Any ideas what can I do with such a situation with my solution? Can I compete with Google?

Usually google is good in the initial release of a product, but they lack good customer care and support. They have non transparant pricings and they disrespect privacy. Those are something's you can differentiate on

> lack good customer care and support.

Depends on how much you're paying them and the SOW you've signed.

> non transparant pricings and they disrespect privacy.

For pricing, talk with them. Or use a cloud broker.

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