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Jon Millis

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The “First Mover’s” Analytics Stack, 2015 vs. 2016

Posted by Jon Millis

7/1/16 10:00 AM

The irony of data science is the glacial and blazing speed at which the industry seems to move. It’s been more than 10 years since the origin of the phrase “big data”, and yet what we initially set out to accomplish – extracting valuable answers from data – is still a painstaking process. Some of this could be attributed to what Gartner refers to as the “Hype Cycle”, which hypothesizes that emerging technologies experience a predictable wave of hype, trials and tribulations before the they hit full-scale market maturity: technology trigger  peak of inflated expectations  trough of disillusionment  slope of enlightenment → plateau of productivity. 

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Topics: Eureqa, Big data, Machine Intelligence, Analytics stack

Using Machine Intelligence to Understand the Student Loan Problem

Posted by Jon Millis

5/6/16 12:30 PM

In March, the US Department of Education released its latest College Scorecard to “provide insights into the performance of schools eligible to receive federal financial aid, and offer a look at the outcomes of students at those schools.” Fortunately for us data-driven strategists (read: nerds) at Nutonian, the government also released the raw data it used to drive at its summary results and findings.

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Topics: Machine Intelligence, College Scorecard

Analyze This: 6 Ways Retailers Put Artificial Intelligence To Work

Posted by Jon Millis

5/4/16 12:08 PM

This week Retail TouchPoints, a leading retail analytics media company, ran an article by Scott Howser, our SVP of Products and Marketing. Scott is seemingly always on the cutting-edge of big data, data science, and AI, having spent time driving success at companies like Vertica (acquired by HP), Hadapt (acquired by Teradata), and now Nutonian. Retail TouchPoints sought Scott's expertise to find out how retailers are leveraging the latest hot technology: artificial intelligence. The article, "Analyze This: 6 Ways Retailers Put Artificial to Work," is reproduced below. 

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Topics: New store optimization, Sales forecasting, Artificial intelligence, Retail, Retail TouchPoints, Staffing

NSF Uses Artificial Intelligence to Tackle Illegal Tiger Poaching

Posted by Jon Millis

4/26/16 9:23 AM

AI to the rescue. Forget doomsday scenarios of robots transforming humans into paperclips. This time it’s more positive. The National Science Foundation (NSF) announced it’s turned to artificial intelligence as a critical weapon in the fight against poaching.

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Topics: Artificial intelligence

The Perils of Black Box Machine Learning: Baseball, Movies, and Predicting Deaths in Game of Thrones

Posted by Jon Millis

4/22/16 10:17 AM

Making predictions is fun. I was a huge baseball fan growing up. There was nothing quite like chatting with my dad and my friends, crunching basic statistics and watching games, reading scouting reports, and finally, expressing my opinion on what would happen (the Braves would win the World Series) and why things were happening (Manny Ramirez was on a hot streak because he was facing inexperienced left-handed pitchers). I was always right...unless I was wrong.*

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Topics: Machine Intelligence, Machine learning, Baseball, Game of Thrones

Industry Trends at the Bio-IT World Conference & Expo

Posted by Jon Millis

4/15/16 9:30 AM

In our market ascent, Nutonian has noticed that many of our most “cutting-edge” customers are biotech and healthcare companies. From drug demand forecasting to clinical trials analysis, Eureqa has been a critical cog in helping companies go from raw data to pattern detection, pinpoint forecasts, and root cause discoveries.

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Topics: Eureqa, Healthcare, Biotech

The Road to Recovery: Automated data science will drive important discoveries and efficiencies in healthcare

Posted by Jon Millis

11/11/15 10:00 AM

Healthcare drives people mad. There’s nothing neutral or uncontroversial about it. Politicians argue about it, countries overspend on it, citizens fret about it. Providers walk a fine line between providing quality care for the sake of positive patient outcomes, while routinely being incentivized to package quantity over quality. Insurers are customer-focused corporations trying to provide a universal good, while also acting as “rational players” seeking to line their pockets. Patients, meanwhile, are the ones with true skin in the game. After all, as the cabaret of politics, insurers, lobbyists and pharmaceutical companies spins and twirls, what some people keep seeming to forget is that healthcare is inherently about the patient. And at some point in our lives, to better our existences and our enjoyment of life, we’re all patients.

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Topics: Eureqa, Healthcare

How to Anchor Your Fantasy Football Team: Using Advanced Analytics to Pick the Best Available Quarterback

Posted by Jon Millis

9/10/15 10:40 AM

Fantasy football: where owning a sports franchise is within anyone’s reach, a year of pride is put on the line, and grown adults cry…more than once…almost every Sunday. Yet for many football fans, we wouldn’t have it any other way. Except for you, Reggie Bush. 550 total yards…FIVE HUNDRED AND FIFTY YARDS?!? I COULD JOG BACKWARDS FOR MOR—let’s move on.

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Topics: Eureqa, Fantasy Football

Eureqa Will Augment – But Not Replace – Engineers

Posted by Jon Millis

8/12/15 9:50 AM

A few weeks ago, Engineering.com wrote an article that nicely summarized Eureqa’s impact in the manufacturing space, slashing the cost and boosting the performance of metals. But while we lovingly call our product the “Robotic Data Scientist” for its ability to automatically inform engineers (or any analyst/data scientist) how to optimize processes, one thing Eureqa will never do is eliminate the need for good engineers.

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Topics: Eureqa, Manufacturing

Data Scientists Don’t Scale. Machine Intelligence Does.

Posted by Jon Millis

6/29/15 12:30 PM

Data scientists are unicorns. We know they exist, we know they’re magical, we know they hold the answers to many of our business intelligence hopes and dreams. Unfortunately, the current market encounters a tri-fold of problems in trying to find, tame and leverage these unicorns.

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Topics: Eureqa, Scaling data science

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