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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

Letter from a Grateful Hobbyist Who's Predicting the Financial Markets with Eureqa

Posted by Jon Millis

6/22/15 2:00 PM

Nutonian users aren’t just large corporations. They’re also hobbyist data modelers leveraging Eureqa to predict the popularity of songs, analyze home science experiments, and even determine what makes some Porsches faster than others. The letter below was sent to us by a former real estate investor and manager named Bill Russell, who’s been using Eureqa to anticipate relatively short-term movements in stock prices. Hopefully Bill’s note will not only shed light on Eureqa’s potential, but will encourage our non-commercial fans to start thinking how they might apply Eureqa to some cool personal projects outside the office.

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Topics: Eureqa, Big data, Financial Services

Trading Necessitates Speed Along Every Step of the Data Pipeline

Posted by Jon Millis

6/10/15 1:43 PM

We just returned from Terrapinn’s The Trading Show, a data-driven financial services conference that brings together thought leadership in quant, automated trading, exchange technology, big data and derivatives. With more than 1,000 attendees and 60 exhibitors gathering at the Navy Pier in Chicago, this year’s event was an excellent way not only for us to educate the market about using AI to scale data science initiatives, but for us to learn about the most pressing needs faced by financial services companies.

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Topics: Eureqa, Big data, Machine Intelligence, The Trading Show, Financial Services

Demystifying Data Science, Part 3: Scaling data science

Posted by Lakshmikant Shrinivas

5/15/15 9:45 AM

In my last post in this series, I spoke about what goes into a data science workflow. The current state of the art in data science is not ideal; the value of data is limited by our understanding of it, and the current process to go from data to understanding is pretty tedious. The right tools make all the difference. Imagine cutting a tree with an axe instead of a chainsaw. If you were cutting trees for a living, wouldn’t you prefer the chainsaw? Even if you only had to cut trees occasionally, wouldn’t you prefer a chainsaw, because, well, chainsaw! The key here is automation. Ideally you want as much of a process automated as you can, for the sake of productivity.

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Topics: Big data, Demystifying data science, Scaling data science

Demystifying Data Science, Part 2: Anatomy of a data science workflow

Posted by Lakshmikant Shrinivas

4/22/15 10:00 AM

“Data Science” is a pretty hot topic these days. But what is it exactly? Before I learned about data science, my reaction to it could be best described with the following cartoon:

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Topics: Big data, Demystifying data science, Data science workflow

Nutonian Takes its Shot at NHL Playoff Predictions

Posted by Jon Millis

4/16/15 5:14 PM

The National Hockey League: where grown men skate after a small cylinder, whack it with sticks and beat each other to a pulp. God Bless America (and Canada). Hockey is popular for good reason. It's fast, action-packed and highly-skilled. It also produces a decent amount of freely available data for fans – and now software – to crunch and predict the winners of this year's holy grail, the 2015 Stanley Cup. Here's how our virtual data scientist, Eureqa, believes this year's playoffs will shake out:

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Topics: Eureqa, Big data, Machine Intelligence, NHL Playoffs

Do Investors Rely on Too Much Information or Not Enough?

Posted by Jon Millis

4/7/15 10:00 AM

Information is beautiful. It helps us learn about the world around us. It helps us better understand people and subject matters. And in the professional world, it helps us make informed decisions that are likely to help us achieve specific goals.

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Topics: Eureqa, Big data, Machine Intelligence

Demystifying Data Science, Part 1: My Transition from Infrastructure to Machine Intelligence™

Posted by Lakshmikant Shrinivas

4/6/15 10:00 AM

A lot of people thought I was crazy for leaving one of the hottest, most innovative big data companies of the last 10 years, to join another start-up.

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Topics: Big data, Machine Intelligence, Demystifying data science

Convert Data to Intelligence, Faster

Posted by Jon Millis

3/20/15 10:00 AM

Oil_refinery


“Data might be the new oil, but a lot of us just need gasoline,” proclaimed Derrick Harris, one of our favorite technology journalists, in a recent blog post.

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Topics: Eureqa, Big data

Stop Talking About Big Data

Posted by Jess Lin

8/26/14 10:00 AM

No buzzwords. Can you really explain what "Big Data" is? If you wade through the hype for long enough, you should see that big data isn't about the data at all - but you'll have a long way to wade first. It's about finally bridging the divide between potential and action. It's about moving us from a generalizable world where machines and even people are lumped into amalgamous buckets that are all supposed to behave the exact same way into a personalized world where everything is recognized for its distinctive traits and unique qualities. But thanks to a highly technical origin combined with rapid enterprise adoption, big data is still a very amorphous concept that people struggle to define yet can't ignore.

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Topics: Big data

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