Chatting with Chet: AI Innovation with RPA

I thanks and welcome back to you I pass chat which yet today I'm here with Diego Lamont oh did I get that right you perfect I've actually never heard it say so if you've ever wanted to see two guys that were diametrically opposed he grew up was born and raised here in New York City and if you can't tell I'm from out in the woods in Texas but this is is just a testament to the overarching ability of our PA of bringing different cultures and classes together today we're going to talk about our PA and AI uh is something sneer and dear to my heart as well at HP I had the opportunity of setting all of my AI functions on top of my RP a backbone so as you take us through a little bit and tell us what's coming down the pike yeah I love first of all I love talking to people who work like you're not customer anymore but people are customers who are innovating in the AI space it's one of my favorite things to do here at uipath as as a product marketing guy yeah you know I think what's really interesting to me and and fascinates me and one of the reasons why I joined the company is how are PA and AI are merging to some extent but it's a bit of a misnomer to look at them completely different right I think for someone who's done sure in the past you know you're a I is not just you know this one set of technologies that does the specific thing and then RPS and another set of technologists does another thing there's a lot of bleeding over between the two and to some extent our PA is AI both from the fact that there is computer vision that's a core component of what our PA does and and real quick for those of you that don't understand computer vision its UI past ability to understand that computer screen very much in the same way that human does that's right that's right being able to see and understand what's happening on the screen and then react to it is what computer vision that's one of the you know core technologies that we've had broken through but then in another sense what are PA does the ability for an automation a robot a machine to follow a set of instructions based on what happens in the course of a workflow is a it's just not as well-known as what is popular in a I right now which is machine learning which is different but machine learning is coming it's our PA as well so I love being part of the ARP ARP a space because of its roots in some of these AI technologies but then what it's bringing in from AI and that's what I think so fun for us enough and a lot of the data scientists and analytics analytics talks that I go and do what I stand up there and tell them I said say okay data scientists write out your algorithm for me now what is this first bird oh that's total di so bought go get it yeah and only bring back clean records so what are PA in my mind and in my experience what it's done is it's given the data scientists time to be data scientists because they're not spending their time collecting and cleaning data what do you think 100% not only that I I would say it's giving them the ability to be data scientists because they're not collecting and cleaning data but they're also not deploying models into workflows all right cuz that's not what a data scientist should be doing right data scientist should be coming up with the algorithms right they should be building the models acquiring the data from a technology like our PA training those models making them better and then you should they should be leaving the deployment to another set of people that specialize in that because it's not the best use of their time they should be in the lab building building better mom play To Your Strengths we learned that a while back and yeah we need data scientists to be data scientist that's right that's right – right so you know if you talk to PDR head of AI here I think he estimates this truly 3,500 data scientists in the world right wow that's that's big small or no that's what I thought was there yeah it was just a study that's it here about 500,000 but when I I brought that study to him and I have we talked about it he said that's that's a lot of the people deploying models that's not that's not data scientists so there's there's not a lot of them they're in demand they're expensive and we have them doing I won't call it lower value work but work that you could be market to another group of people that there's a lot more of those people out well I certainly appreciate you coming on today Thank You Diego for coming by awesome chat thank you remember automation first as we get this mindset around AI as we think about how do we do things better smarter remember automation first and thanks for coming by

One Comment

  1. Idjles Erle said:

    This was completely devoid of any substance. They mention "Computer Vision", which it's still "in its infancy" – marketing-speak for "It doesn't really work", . Nothing was said about AI Innovation with RPA, just 3500 "data scientists" (who?) building "models" (which do what?), and nonsense that an RPA workflow, fully constructed by a human, is also "AI". But hey, he's the VP of Product Marketing, whose job it is to spin something out of nothing.

    July 12, 2019

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