Tag Archives: Michael

Expert Interview: Michael Schmidt of Nutonian on the Future of Machine Intelligence

Michael Schmidt is one of the “World’s Most Powerful Data Scientists” (Forbes) and founder of Nutonian, an artificial intelligence (AI) company that automatically generates forecasts and strategic business recommendations. We recently checked in with Michael to get insight on data science and the future of machine intelligence. Here’s what he shared:

Can you talk about your professional background and interest in data science? What drew you to this field?

I pretty much stumbled into data science in grad school. I was studying computational biology at Cornell, and what I kept noticing was that all of these grad students and scientists were spending a majority of their time crunching numbers and building models to understand their data. The problem was that this was taking up a significant amount of their time, when the reality is, that part of the research is neither glamorous nor particularly rewarding … and on top of that, there’s a lot of potential for human bias to sneak in.

What I thought was: What if there were a way to help scientists bootstrap the process of extracting meaning from data? What if I could leverage some of my coding experience to build a computer program that could automate the process of creating predictive and explanatory models?

What came out of that was a free prototype version of Eureqa, an AI-powered modeling software that was downloaded about 80,000 times in the first year or two. I was fortunate enough to meet some investors who saw the potential of Eureqa in the business world, and that’s when I started to build out my current company, Nutonian. Eureqa is the only software on the planet that automatically prescribes solutions on how to improve your business.

blog banner HadoopPerspectives2017 1 Expert Interview: Michael Schmidt of Nutonian on the Future of Machine Intelligence

How has data science evolved since you started your career?

About 10 years ago, data science was uncool and even intimidating to most people. I think it’s starting to get a better reputation now, only because people have started to acknowledge that it could be the key to unlocking a whole lot of value from the data they’ve been collecting. But it’s still been pretty complex and time-consuming, with data scientists using things like R, SAS, Python and toiling for a few weeks or even months to solve a few problems. We’re starting to run into a scaling issue, where companies have way more questions than answers.

The biggest evolution to happen over the past couple of years has been the transition from data science being a scary, expensive and technical burden to something that can be leveraged by anyone to drive data-driven decision-making. The idea of using data science to automate data analysis, to prescribe solutions … and do it in minutes. And I can tell you, one company is light-years ahead of the others in making this happen.

What excites you about the future of data science? What trends or innovations interest you?

The term that’s most exciting to me is “machine intelligence.”

This isn’t about chat bots or sentient robots. Machine intelligence refers to the new subfield of artificial intelligence that automates the discovery and explanation of answers from data. So, whereas machine learning requires the user to exhaustively train and tune algorithms to perform a task, machine intelligence actually teaches the user.

Machine intelligence will automatically evolve the best algorithms that explain a problem, and will interpret them into plain English to answer questions like why problem X is happening and how we can solve it, such as:

  • “This jet engine is in jeopardy of failing, because of these five variables. Here’s what you should do about it.”
  • “This collection of stocks and bonds is likely to significantly outperform the S&P 500, and here are the 10 predictive variables that give us such confidence.”

Machine intelligence, in the hands of many users, will be an incredibly valuable tool for society, not only for making people money, but also for addressing pressing issues in areas like healthcare.

Related: Coming Soon to a Mainframe Near You: Machine Learning

Can you tell us about the mission behind Nutonian? How are you hoping to impact the way organizations create analytical models?

Nutonian’s goal is to enable companies to make the best data-driven decisions to maximize business or a desired outcome. Nutonian has two types of users.

The first is the tech-savvy person who likes to build models. We help him/her become exceptional at that, because we automate the heavy lifting of manual model creation, but we let the user guide the process and apply domain expertise to get the best possible models.

The second type of user is the business user. The analyst, the manager, the CxO. This person doesn’t need experience with data science or modeling. This person believes in the power of information and wants to make his or her business better, more efficient, more profitable. Eureqa’s forecasting app automatically creates predictions, and literally prescribes actionable recommendations, in a matter of minutes. This is where we change the game.

What are some of the common challenges facing organizations today in modeling? What are the reasons behind these challenges?

Modeling takes time and tech-savvy. Both of these things ding a company in the long run. You might have five brilliant people working to solve data-driven problems (what’s causing customer churn? Where should we open our next store? How do we make this metal stronger and lighter?), but it takes each of them a few weeks to complete their task.

The other issue is that models today are almost always too complex to reliably interpret and understand. If I want to know what’s causing customer churn, I might be trying to interpret a black box model from R that’s three pages long. Lack of model transparency means that even if I’ve got a highly accurate model, it’s hard to actually take actionable steps to improve my desired outcome, because the model is just too hard to comprehend.

What are the benefits of using machine intelligence to evaluate models and present easy-to-understand information from them?

Machine intelligence aims to not only optimize for accuracy, but also simplicity. Machine intelligence will identify the most accurate possible explanatory models in their simplest possible form. This ensures that companies can understand the causes underlying the problem and effectively act on them.

What are some outdated and/or ineffective methods for modeling you’re observing organizations using today? What are the risks to not adapting to new methods of understanding their data?

The truth is technology is constantly evolving. I would say if you’re using R, MATLAB, SAS, Python, you’re ahead of some people, but you’re not an early adopter, and you’re certainly going to start feeling the headache of cost, speed and complexity, if you haven’t already. And truth be told, your competitors are probably already starting to dip their toes into machine intelligence.

I’m biased, but I think machine intelligence is going to be the single greatest technological advantage for corporations over the next few decades.

What are some of the most interesting and/or exciting applications for machine intelligence you’ve observed being used in business?

I’m most excited by the impact machine intelligence is having on forecasting. Because machine intelligence is about understanding and actionability as much as accuracy, it’s enabling companies to not only predict, but also to diagnose and to mend. You can predict your future and essentially change it for the better.

We’re working with a global automotive company that’s projecting sales – and receiving automated recommendations on how they can maximize that number. Everything from hiring more people at specific locations, to stocking certain car types more than others, to spending ad money through the most effective channels. We’re also working with a large retail pharmacy to forecast prescription drug demand per store and per drug, enabling them to optimally stock and staff their stores.

These are not small problems, and they’re not easily solvable. Machine intelligence is going to change that.

Learn how Syncsort can help your organization use data to evolve. Check out their Big Data solutions.

 Expert Interview: Michael Schmidt of Nutonian on the Future of Machine Intelligence

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WATCH: Comedian And Host Michael Colyar Talks New Show Plus The Origin On The “N” Word!

Here is an interview we conducted with comedian and host Michael Colyar as he talks about his upcoming projects, plus the origin of the N Word! Check out the interview! SUBSCRIBE to our channel!

Universal’s Reboot Of ‘Scarface’ Loses Director Antoine Fuqua!

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The Humor Mill

Have you seen Michael Moore's post about how Trump is going to win, and if so, your thoughts?

avatar 80daabc0929c 512 Have you seen Michael Moore's post about how Trump is going to win, and if so, your thoughts?

It’s a useful call to arms that everyone who is #BernieOrBust needs to hear and think about.

I’ve made it really clear that Bernie Sanders is who I wanted for my president, and I did what I could to make that happen … but he didn’t get the nomination, and now my realistic choice is between Hillary Clinton and Donald Trump.

I think Michael Moore is right about Hillary not exciting young people the way President Obama did and does. It’s now our job to help everyone who is upset and disappointed and thinking about staying home to realize that we’re going to need every single vote we can get to defeat and utterly demolish and humiliate Donald Trump and everything he stands for.

I don’t like that Clinton is a warmonger. I don’t like that she’s too close to Wall Street. I don’t like that she and her campaign were condescending and dismissive of Millennials during the primaries.

But none of that changes the reality we are facing: it’s Clinton or Trump. I understand that younger voters don’t remember the 2000 election when SCOTUS installed Bush, and I understand that younger voters who were in elementary school during his disastrous presidency were effectively insulated from it because they were kids. I was *exactly* that kid in 2000 when I voted for Nader, because Bush was an asshole and Gore was a terrible candidate.

But if I could get my vote back now, I’d build the time machine with my own hands. Think of the millions of people who have died because of Bush. Think of the destruction of our climate that is now a total crisis, because Bush and his administration did nothing to address it. Think of how much horrible debt college students have, because Bush put people who just wanted to take their money away from them into positions of power. Think about the militarization of our police, which began under Bush. 

President Obama did everything he could to roll back the damage Bush and Cheney did to our country and the world, and we aren’t even halfway to where we need to be. I don’t know how much President Clinton will work to continue rolling it back, but even if she keeps it in the same place, that’s better for our country and the world than what will happen under a President Trump.

If you, like me, wanted Bernie Sanders to be our president, if you, like me, believe in his revolution, if you, like me, believe that we have to make America work for the 99%, then your choice in this election is Hillary Clinton.

She’s not perfect. She’s not my first choice, or even in my top five choices. But she is the choice I have if I want to protect my country and my children from Donald Trump.

So that’s why, even though I still Feel the Bern, I’m With Her.

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Blogtastic!

AnalyticsWeek Leadership Playbook Podcast Featuring Michael O’Connell

rsz bigstock vector flat concept of audio p 81063152 AnalyticsWeek Leadership Playbook Podcast Featuring Michael O’Connell

Live Leadership Playbook Video Podcast
Featuring Michael O’Connell, Chief Analytics Officer at TIBCO Software

“Data preparation is an oxymoron,” says Michael O’Connell, chief analytics officer at TIBCO Software in his latest discussion on data analytics. In this live podcast, Michael O’Connell shares his philosophy on data preparation: it’s in-line, it’s immersive, it’s iterative… and it’s just the start.

Access the podcast and hear, in 30 minutes, how to extract the signal from the noise by getting the data you want into the shape and form it needs to represent information that solves your business problems.

VIDEO PODCAST Tablet 1 AnalyticsWeek Leadership Playbook Podcast Featuring Michael O’Connell

Watch Now! Join the conversation on Twitter using @analyticsweek #livepodcast and @MichOConnell

Looking to explore more?

Watch Michael O’Connell in his latest webinar, ‘Biggest Baddest BI Platform on the Planet’ explain how Spotfire’s architecture is helping IT and business users unify on one platform and why it’s the preferred solution for enterprise analytic deployments. Register here and try TIBCO Spotfire for free today.

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Interview with Michael W. Moss, CEO of Value-4IT, about the IBM System z Mainframe

What do you believe are the most important trends in mainframe computing today?

Currently, data is the biggest driving force for System z Mainframe innovation. Ever increasing amounts of data are being created day after day, primarily from Analytics, Cloud, Mobile Devices and Social Media sources. The System z platform delivers the highest capacity and is the resilient single footprint server available today. These attributes are ideal for optimizing virtualized workloads, especially via Linux on z Systems functionality, while safeguarding and processing this mission-critical business data.

What do you see as the biggest challenges for mainframe computing today?

By some, the System z Mainframe is still perceived as a legacy technology only suitable for Fortune 500 organizations. The System z Mainframe must continue to evolve with constant innovation that optimizes cost (even for small organizations) while continuing to deliver an agile, flexible, scalable, secure and resilient platform for the 21st century business.

What can systems administrators do to keep mainframe costs reasonable?

System administrators must always be mindful of software cost optimization to maintain the best TCO for their organization. A hybrid of technical and commercial skills is required to minimize CPU capacity usage and leverage from the best software licensing regime. Moreover, with each and every release of System z software or hardware, the realm of possibility exists for organizations to exploit the latest function or feature in order to optimize costs. Never have the archaic sayings of “be careful how the small things grow” and “look after the pennies and the pounds look after themselves” been more relevant.

How much of a player is data analytics in today’s System z environment?

Data analytics is a significant challenge and opportunity for each and every business, whether they deploy a System z Mainframe or not. The time to market for new business or consumer facing products or solutions is rapidly diminishing with a clear and present requirement for real-time data analytics. Recognizing that 70%+ of Fortune 500 organizations deploy the System z platform for their mission-critical business applications, this priceless data source must be secure and leveraged from to drive the business forward. The System z consistently delivers the Common Criteria Evaluation Assurance Level 5+ (EAL5+) security standard as a cornerstone of its architecture.

Aside from data analytics, what other factors are driving the popularity of System z?

The reliability, availability and scalability of the System z Mainframe server ideally positions this platform for consolidation of distributed systems workloads. From a system administration and cost optimization viewpoint, the latest System z servers are becoming increasingly popular for x86 workload migration activities. Moreover, the System z platform never stands still, providing a software ecosystem that supports the latest application programming techniques. This ensures that businesses can integrate Cloud methodologies into their business processes, thereby implementing application change rapidly and safely.

What do you see in the future of System z?

The future for System z is to leverage from its core foundations, offering high performance CPU chips, the biggest single server footprint and best-of-breed security solutions. The System z platform will continue to observe the Analytics, Cloud, Mobile Devices and Social Media data sources, driving today’s business requirements, and delivering a cost efficient platform that is accessible to many global organizations – not just the perceived limited subset of committed Fortune 500 organizations.

With the newest release of the ZPSaver Suite, Syncsort demonstrates the commitment to continually look for ways to help customers fully leverage the tremendous strengths of the IBMz and z13, especially zIIP processors and advanced levels of cache design. Syncsort is offering potential customers free comprehensive workload analysis services, which will deliver a crisp and clear estimate of the potential cost savings and performance benefits of the ZPSaver Suite for a given customer’s mainframe environment.

 Interview with Michael W. Moss, CEO of Value 4IT, about the IBM System z Mainframe

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Big Data Business Models and Code Halo Strategies with SmartStory’s CEO Michael Boerner

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While many companies talk about someday implementing strategies that will provide competitive advantages and change the world, SmartStory Technologies is delivering.  They combine the use of big data, POS (point of sale) systems, Code Halos strategies, mobile apps and hyper-personalization to deliver customized short-form videos to mobile devices that are specific to the user’s needs, at the right time and on the right device.  This technology will change retail.  Especially when complex products and services are involved.

Digital transformation is about recognizing the impact of innovation in your industry, market and business.  It is about understanding how new technologies will transform your business plans and budget priorities.  It is about being bold enough to act and change direction mid-year, or budget cycle.

In this interview with SmartStory’s CEO Michael Boerner, we dig deep into how digital transformations are already changing the way retailers interact and support their customers in completely new and innovative ways that will change the competitive landscape forever.

If you sell complex products and services – I strongly suggest you study this video segment and discuss what you are seeing with your strategy team.  Your industry and market will be impacted. Stay tuned for parts 2 and 3 in this series.

Video Link: http://youtu.be/rLlNmW-VmXw?list=UUGizQCw2Zbs3eTLwp7icoqw

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Kevin Benedict
Writer, Speaker, Senior Analyst
Digital Transformation, EBA, Center for the Future of Work Cognizant
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Recommended Strategy Book Code Halos
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***Full Disclosure: These are my personal opinions. No company is silly enough to claim them. I am a mobility and digital transformation analyst, consultant and writer. I work with and have worked with many of the companies mentioned in my articles.

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