How To Use Online Machine Learning

Recent news headlines, especially the tumultuous news of Stormy Daniels’s arrest, have gotten us thinking: how has AI changed the nature of AI, the U.S.

Several years ago, I moved to New York, which is a rather large city. My visit was mostly for two reasons: I wanted to see how digital culture is moving forward and, in part, study NYC’s bottom up form of influence and community mapping. The other reason is that I wanted to find a job. I started a digital mapping startup and needed to find a tech-savvy business partner. I interviewed several people who are technically savvy and, over dinner, mentioned that they would be interested in building this business. Two of the top candidates was the one who really stood out. We were not sure at the time about how his program would work but that wasn’t an obstacle since we were both interested in the challenge. The problem we faced was that we didn’t know enough about the tech beyond what we could observe at the startup and if we didn’t know more we weren’t sure what our biases are.

One of the first meetings I had with our co-founder was at Google headquarters. I was impressed by the employees and the concept that they built. Then, I witnessed them demo a piece of software that helped people find new restaurants in their area. “Imagine being able to search for food without leaving your house. This technology could be revolutionary for the emerging market of personal food service. We will be testing their software on-air during ‘The Tonight Show with Jimmy Fallon’ with John Mayer and his band,” I learned. I told my partner and co-founder that I was in awe and that this was the kind of material I wanted to write about and that I was not sure about the technological side of the business. “Of course you need to be more open minded on the tech side of things,” he replied. “Oh, you mean in the reporting side?” I asked. “Yes, exactly. Think about how you report on things. You don’t just report on what happened, you also report on how it happened. You can report on what happened just as you would report on a sporting event or a battle in a war. I want to report on the evolution of the tech. And this is why I feel open minded and not biased,” he replied.

From there, we knew we could use online machine learning to do all of this. Just imagine that when I wrote about a specific industry, machine learning could help find more context in my writing. We started using this technology to analyze our voice based on how other have presented the same topic. We already used similar tools for the use of Siri. “But, I don’t understand where you got the tool to do this?” I could hear in my friend’s voice. “All you have to do is say your search for restaurant with Siri or Alexa in a new way. For example, saying how Italian food should be good with Parmesan cheese with a piccolo aperta. And then the tool will analyze your dictionary and pick a good word for the right context.” I wasn’t quite sure how this worked yet but I knew it made sense from the ideas I was presenting and even though the audio would just be one chapter in the book it made sense to me.

We expanded this approach and after some testing decided that conversational language is a perfect example for an accurate voice driven database. “We tested it for a few months and it worked 100%. That’s the reason we are now embracing this technology. What we are doing is really connecting the technology to stories and not just to understand how the technology works,” I explained to my friend.

It is this direct approach to the technology that I felt more comfortable working with this approach to learning about the newest trends in technology and it opens up opportunities. I can also see how teaching the story through different mediums gives a different perspective and even gets people to use the technology. “This sounds nice but we have no idea if it works. How will it be applied in reality?” My friend was skeptical, but of course that was his point.

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