Beyond the Machine Learning Hype: Solving Vexing Problems in New Ways

Gartner’s latest quarterly IT spending forecast delivers big news about the cloud’s role in global IT expenditures. The firm expects worldwide IT spending to reach $3.8 trillion this year, rising 3.2% over 2018, as the company points out here. A major driver of this growth is the enterprise software segment, which is projected to increase 8.5% this year and another 8.2% in 2020 – reaching $466 billion that year. Organizations are expected to shift more of their budgets to software-as-a-service (SaaS) in 2019.

Unless you’ve been stuck under a rock, you’ve probably come to the conclusion that artificial intelligence–really machine learning, is going to take over the world. Elon Musk and Mark Zuckerberg have recently sparred each other over the risks and benefits of artificial intelligence.

Musk, founder of Tesla and SpaceX, has a well-known belief that the future looks more like Ridley Scott’s famous cult science fiction film Blade Runner than the amazing Disney Word gee-whiz future in the marketing brochure. His company SpaceX’s mission is to make life on Mars possible for when Earth is no longer inhabitable. “I keep sounding the alarm bell,” he recently told attendees at a National Governors Association meeting. “But until people see robots going down the street killing people, they don’t know how to react.”

Elon Musk & Mark Zuckerberg

Mark Zuckerberg hit back in a Facebook Live event, calling Musk a “naysayer”. Going even further, he said, “in some ways, I actually think it is pretty irresponsible.” Facebook, Google, Salesforce, IBM and any major tech player of note are all betting big on the sunny-side scenario. But as with all things, some see the porridge as too hot, others too cold. The truth is always somewhere in the middle and the middle is a place where the raisins and brown sugar are best.

One such place in favor of the value of machine learning is the annual Data Science Bowl co-sponsored by Booz Allen and Kaggle (now owned by Google). The Data Science Bowl brings together data scientists, technologists, domain experts, and organizations to take on some of the world’s toughest challenges with data and technology.

The 2015 contest asked data scientists from around the world to examine over 100,000 underwater images to assess ocean health on a massive scale. The winning submission beat the state of the art by more than 10%. In 2016, contest participants applied analytics to cardiology. The winning team weren’t doctors or data scientists, they were hedge fund traders. This year’s contest winners created an algorithm that dramatically reduces the false positive rate in the diagnosis of lung cancer, and again the winners were not physicians, rather they were data scientists.

August 8th, 2017
DATA ANALYTICS & MACHINE LEARNING
DATA ANALYTICS & MACHINE LEARNING
DATA ANALYTICS & MACHINE LEARNING
DATA ANALYTICS & MACHINE LEARNING

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2019-05-02T11:15:27-05:00