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Basketball or Medical: Apple & Google Make It Easier to Bring AI Into the Mix

June 13, 2018
By Paula Bernier - Executive Editor, TMC

It’s early days for artificial intelligence and machine learning. But there’s no doubt about it. Early AI and ML solutions are here today.

And the use of AI and ML in new applications, products, and services will become much more widespread in the not too distant future. In fact, AI is expected to be so widely used that some are comparing artificial intelligence to electricity. This comparison suggests that AI eventually will power everything.




Big tech companies like Apple and Google (News - Alert) have introduced tools that make it easy for application developers to bring AI into the mix. And they continue to add to and improve upon these solutions.

For example, Apple (News - Alert) unveiled Create ML at the Apple Worldwide Developer Conference earlier this month. Create ML could be used for a variety of applications. A couple examples that Apple talked about include enabling software to detect if online comments are angry or happy, and predicting wine quality based on its acidity, sugar content, and other characteristics.

Create ML joins the Apple Core ML tools for developers. Apple this month announced its second iteration of Core ML, which is 30 percent faster due to batch prediction; allows machine learning models to be up to 75 percent smaller; and supports custom data, vision and natural langage, and more.

Apple’s Head of Software Craig Federighi has also talked about how app developers can employ AI to build applications that can use mobile device cameras in new ways. For example, a recent report discusses the HomeCourt, which enables basketball coaches to point iPad cameras at action on the court. It then uses AI to make a record of how many times a player, shoots, scores, and misses. It takes note of the user location on the court for each throw. And it makes it quick and easy for users to watch the video later.

Meanwhile, Google has Tensorflow. That’s a computation framework for building machine learning models. Last month global freelancing website Upwork ranked Tensorflow as the No. 2 fastest-growing freelance skill for Q1 2018.

Google, which also has its Google Assist solution, its working with AI on a number of fronts. In May Google CEO Sundar Pichai blogged: “Two years ago, Google developed a neural net that could detect signs of diabetic retinopathy using medical images of the eye. This year, the AI team showed our deep learning model could use those same images to predict a patient’s risk of a heart attack or stroke with a surprisingly high degree of accuracy. We published a paper on this research in February and look forward to working closely with the medical community to understand its potential.

“We’ve also found that our AI models are able to predict medical events, such as hospital readmissions and length of stays, by analyzing the pieces of information embedded in de-identified health records,” he wrote. “These are powerful tools in a doctor’s hands and could have a profound impact on health outcomes for patients. We… are working with hospitals and medical institutions to see how to use these insights in practice.”




Edited by Maurice Nagle


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