[cmaury]

While Google may be the leader in Machine Learning tools, they are way behind when it comes to Machine Learning services.

They've only just now released a Natural Language Understanding service in beta, and it is more limited compared to other NLU services from Microsoft/others.

While tooling is important, the market for low level tools is much smaller than for the services built using those tools. The vast majority of businesses who could benefit from Machine learning don't have the expertise to run RNNs using Tensor Flow, but do have engineers who can integrate API's that leverage trained classifiers.

[shakil]

> they are way behind when it comes to Machine Learning services.

Umm, there's five separate managed services within the Google ML family: Vision (GA), Translate (GA), Natural Language (Beta), Speech (Beta), and Cloud ML (Alpha)

https://cloud.google.com/vision/ https://cloud.google.com/translate/ https://cloud.google.com/natural-language/ https://cloud.google.com/speech/ https://cloud.google.com/ml/

[nevir]

The market for services is several orders of magnitude less than the market for products that make use of ML. It's probably ok if they don't focus to heavily on the services side

Google makes heavy use of these tools internally to build a wide range of products (and enhance existing ones)

[cmaury]

How do you see those two as being different?

In my mind, products that make use of ML are using ML services as the back end. An example would be the recent wave of bot companies: many are not rolling their own NLU system but rather leveraging services like wit.ai or Microsoft's LUIS.

[AIMunchkin]

Google has done a far better job of abstracting the underlying math of machine learning into vertical-oriented services like the CloudVision API and the Cloud Natural Language API.

In contrast, the AWS Machine Learning service provides a 100% vendor-locked interface to logistic regression and that's it. You can't even import or export models. They just hired Alex Smola to do something about that. We'll see what comes of that.