Nutonian’s Apple in the Big Apple

Posted by Jess Lin

11.08.2014 09:30 AM

On July 31st, Nutonian’s very own Michael Schmidt travelled to New York to present at the NYC Machine Learning meetup group. Speaking in front of a packed house at Pivotal headquarters, Michael shared his challenges and experiences in the analytics space. After walking through his first forays into machine learning, he introduced his advances in the field of evolutionary computation in the form of Eureqa®. This breakthrough in machine learning techniques autonomously detects the fundamental laws and rules that drive a system, delivering accelerated actionability and strategic value to the business users who have needed it the most.

Want to hear Michael speak at your next meetup? Talk to us!

Michael Schmidt NYC Machine Learning meetup video

Topics: Eureqa, Machine Intelligence, Meetup

#DataDrivenNYC: Entrepreneurs should strive for simplicity, clarity, and customer proximity

Posted by Jon Millis

24.07.2014 10:00 AM

Data Driven NYC is a community of tech enthusiasts passionate about big data, data technologies, and data-driven products and businesses. The community hosts monthly meet-ups featuring presentations from start-ups and entrepreneurs. At its most recent get-together, Chris Lynch, a serial-entrepreneur-turned-VC, sat down with the group to speak about current tech market conditions and how to get an idea funded. 

“If you build it, he will come.” The classic quote from Phil Alden Robinson’s Field of Dreams also doubles as an inspiring metaphor for entrepreneurs seeking VC funding: build something new, and the money will flow like wine.

The problem, according to Chris Lynch, a big data industry luminary, is that “too few people are building real products from their science projects, and those who are building products are focusing on the wrong market”. Now a partner at Atlas Venture in Cambridge, Lynch, to say the least, has a well-rounded perspective on what it takes to build market-disrupting technologies. Before Atlas, he was CEO at Vertica (acquired by HP) and Acopia (acquired by F5) and SVP of Sales and Marketing at ArrowPoint (IPO and acquired by Cisco).


Lynch told Data Driven NYC members that massive opportunity exists for big data start-ups that can deliver on three things the current market craves:

Opportunity #1: Simple analytics

“It all starts with being able to solve a problem,” Lynch said. “Don’t start another NoSQL database. If you’re thinking about a new platform, don’t waste your time. It’s been built. If you can take the power of big data from the one-percenters and drive it to the dummies like me, if you can put the power of insight and analytics into your smart phone and push the dummy button, that’s when big data can be transformational.

Opportunity #2: A clear value proposition

“At Vertica, we had to simplify our message so that the greatest number of people could absorb it. I pushed the engineering team to help me understand why a column-store really mattered. It boiled down to: it was faster. It was the first real-time database for people to make decisions that made or saved money for their companies. From there, we re-messaged Vertica around being a real-time database and what that meant for life sciences, for retail, etc.”

Opportunity #3: Customer proximity 

While the big data market has gotten crowded, Lynch said, the focus has been almost entirely on infrastructure instead of applications.

“Most of what gaming company Zynga does – identifying mavens and selling them virtual goods – is done using Vertica. But because we didn’t build an application that touched the user, we were dis-intermediated in a big way. The closer you can get to the customer, the further you can move up the stack, the more opportunity there is for monetization, the more opportunity there is for value.”

And while he believes some start-up valuations are overheated, Lynch brushes off skeptics who think that big data is just a flash in the pan.

“I’ve heard the term ‘hype’ used as related to big data. I don’t think there’s a hype cycle around big data. Big data is absolutely for real. It’s not hype. You think about it, anything with an on/off switch is generating data today – that’s a fact. Now, how we create value from that, utility from it, and cure cancer and do real stuff with it, that’s a different story, and that’s just promise unfulfilled. That’s not hype.”

Among Lynch’s favorite investments? A Somerville-based technology company called Nutonian…where data science is bundled up into one easy-to-use, customer-facing application.

Topics: Big data, Data Driven NYC, Meetup, nutonian

How Nutonian almost won $1B

Posted by Jess Lin

02.04.2014 01:00 PM

2014MarchMadnessWe journeyed out to Chicago for the first day of March Madness, armed with Eureqa and our final bracket for the NCAA tournament. While the chaos of this year’s March Madness may have cheated us out of Buffett’s $1B, we have enjoyed a pretty decent bracket (with what appears to be more successful predictions this weekend). It’s not cheating to use Eureqa™ to make confident bracket predictions (and explain them!) without spending hours watching ESPN or poring over analyst reports.

Why March Madness?

March Madness is one of the most popular annual sporting events in the US, and for those of us who are less than basketball savvy, it was an incredibly fun challenge. Quicken Loans offered $1B to anyone that could accurately predict the winners of all 63 games (OK, this may have had an influence on our decision as well). More commonly known as Buffett’s Billion Dollar Challenge, the contest sparked intense excitement as thousands searched for the hidden keys to unlocking this perfect bracket.

At Nutonian, our secret weapon was Nutonian’s cognitive computing engine, Eureqa™. Eureqa™ is capable of automatically discovering causal relationships within complex data structures – and NCAA stats are quite a complex beast. Any of the basketball pundits that made bracket predictions this year would far outstrip the combined basketball knowledge of all of us at Nutonian – no contest. But once we started pulling some basic data together, we could still quickly create a predictive model with high accuracy.

What data did we choose? We only began pulling data a few days before the tournament began, so we started with the basics from the Kaggle March Machine Learning Mania competition as well as the NCAA’s computerized stats. We were also advised to include distance data (game by game distance from home court) and Ken Pomeroy’s strength of schedule statistics. Even though there were many other important stats we could have included, we still ended up with a dataset that had almost 4,000 rows and 60+ columns. Not something that you or I could sift through to decipher by hand.

The Nutonian Difference

To be completely honest, some of the stats we gathered are still a complete mystery to us. But the beauty of using Eureqa is that it doesn’t matter. We just give Eureqa the data, and it tells us what’s important and why. After running for 864 core hours (12 hours on 9 machines for a total bill of $7.56 from AWS), we reached a model with ~75% accuracy. What did Eureqa give us?

win = logistic(2.33e5
-3.56e5 *
THEN greater(seedoseed, Ratio),
ELSE logistic(
THEN seed + tanh(Ratio) – oseed,
) / Pyth_1

What does this equation mean? If a team faced an opponent with a lower seed, the best determinant of the game winner was if the seed difference was greater than the team’s assist / turnover ratio. Otherwise, defense was the name of the game, with rebound margin and assist / turnover ratio acting as the best determinants of the game winner, though teams that faced stronger teams through the season were penalized less heavily.


Does Eureqa know how to play basketball? Does Eureqa know who UCLA is? Does Eureqa care how much time we spent pulling all this data together?? No. But look at the beauty of this simple model that Eureqa was able to discover. Without any prior knowledge of the game of basketball, Eureqa was able to expose the meaningful variables in a model that makes actual basketball sense and can be easily explained to others.

Final Thoughts

Sadly, no one at Nutonian is a billionaire yet. But given a system with less inherent chaos, such as sales forecasting or customer retention, Eureqa can help you become one. We’ve helped our customers pinpoint sales drivers, improve manufacturing processes, stay ahead of market trends, and more. Reaching this level of context and understanding provides actionable outcomes with Eureqa’s vertically focused application modules for retail, telecommunications, financial services, life sciences and utilities.

Watch the recording of our live meet-up for some of the insightful commentary we heard from attendees. Think about how you could apply Eureqa to your own data and let us know some of your ideas in the comments!


Topics: Chicago, Eureqa, March Madness, Meetup

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