Machine Learning Algorithms are Tools

 

There are some really amazing advances and some phenomenal machine learning algorithms and deep learning algorithms, but those are just tools that need to be applied. Companies take those core machine learning tools--they don’t have to build everything from scratch--then they apply the machine learning algorithms to a specific problem. So in our case, understanding the nuances in subtext and sarcasm must be done with a human-in-the-loop. There is no machine learning tool that does that for data scientists, but there are tools that allow us scientists to mine data more effectively.

Our core IP is the secret sauce. We outsource development a small amount of solely the basic reporting functions. But the core IP that the models are running to generate results are designed in-house. Our team of data scientists is busy investigating and tweaking those algorithms. The learning curve is just too steep to outsource development of our core intellectual property to anyone.

It’s difficult not to build some customization into the core infrastructure and get a little bit stuck in the details when our clients talk about analytics as a service. We built our platform to be plug and play way so that we can go through a dozen of APIs that are doing sentiment analysis, entity extraction, spelling grammar punctuation test. I can tell you about who is doing the best personality analysis although I won’t do that publicly. We’ve tried IBM Watson, Google, and Microsoft. We knew we had to mix and match and do this the right way so we built this from the ground up knowing that that was really important.

Dr. Michael Housman, Chief Data Scientist and Co-Founder of RapportBoost.AI, discusses using new and existing tools and API to be more effective in creating better solutions at the JMP Securities Conference panel on AI.

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Dr. Michael Housman

About Dr. Michael Housman

Michael has spent his entire career applying state-of-the-art statistical methodologies and econometric techniques to large data-sets in order to drive organizational decision-making and helping companies operate more effectively. Prior to founding RapportBoost.AI, he was the Chief Analytics Officer at Evolv (acquired by Cornerstone OnDemand for $42M in 2015) where he helped architect a machine learning platform capable of mining databases consisting of hundreds of millions of employee records. He was named a 2014 game changer by Workforce magazine for his work. Michael is currently an equity advisor for a half-dozen technology companies based out of the San Francisco bay area: hiQ Labs, Bakround, Interviewed, Performiture, Tenacity, Homebase, and States Title. He was on Tony’s advisory board at Boopsie from 2012 onward. Michael is a noted public speaker and has published his work in a variety of peer-reviewed journals and has had his research profiled by The New York Times, Wall Street Journal, The Economist, and The Atlantic. Dr. Housman received his A.M. and Ph.D. in Applied Economics and Managerial Science from The Wharton School of the University of Pennsylvania and his A.B. from Harvard University.

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