AI Stories December 27, 2017

Google claims that the latest version of its AI-powered speech synthesis system, Tacotron 2, is almost indistinguishable from human speech – and has put some comparative examples online to demonstrate.

Tacotron 2 works directly from written text, and Google says it can use context to correctly pronounce identically-spelled words like ‘read’ (to read) and ‘read’ (has read), responds to punctuation and can learn to stress words …

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AI Stories November 27, 2017

We’re expecting a major revamp of the Snapchat app to land early next month, but it seems the company isn’t holding back everything until then. It’s been quietly rolling out a feature that recognises (some of) the content in your photos, and suggests relevant borders and filters …

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Everyone can use an Echo Dot: Just $50!

AI Stories August 8, 2017

A bot can use your Instagram feed to tell whether you’re clinically depressed

It seems there’s not much AI can’t do these days. Whether it’s drive a car, improve music discovery, retouch photos or narrate the world to blind people. And now machine learning can even look through your Instagram feed to decide whether you are clinically depressed …

AI Stories July 11, 2017

Reflecting a continued focus on machine learning, Google has announced a new venture fund specifically aimed at artificial intelligence. Gradient Ventures will focus on providing technical mentorship for early-stage startups focused in the burgeoning field.

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AI Stories March 31, 2017

Google invests in Canada’s AI boom w/ Google Brain Toronto and Vector Institute funding

Noting Canada’s artificial intelligence boom, Google announced yesterday that its internal deep learning division is opening another office in the country. The company is also investing $5 million into the new Vector Institute AI research facility.

AI Stories March 3, 2017

It’s hard to think of a job more important that determining whether or not a patient has cancer. Yet the magnitude of the task facing pathologists is so vast that agreement between different clinicians studying the same slides can be as low as 48%.

There can be many slides per patient, each of which is 10+ gigapixels when digitized at 40X magnification. Imagine having to go through a thousand 10 megapixel (MP) photos, and having to be responsible for every pixel. Needless to say, this is a lot of data to cover, and often time is limited.

Which is why Google is working on automating the task with a Deep Learning AI project – with incredibly exciting results …

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