Computer Vision with Graham Leslie from JBKLabs

1

INTRO

On episode 7 of the InsurTech Geek Podcast, talking about Computer Vision and Hot Dogs with Graham Leslie, the Chief Geek at JBKLabs!

2

INTERVIEW

JAMES: And back for another fun episode on a great day and back in the studio with us again, Mr. Graham Leslie, chief geek at JBKLabs. We have had a couple of weeks with just awesome interviews and we are back with another awesome guy our chief geek at JBKLabs Graham. Graham, how are you doing today?

GRAHAM: I am doing wonderfully. A little hungry so we should not have done the hot dog episode before lunch.

JAMES: I know right? I should have done this over lunch. And maybe a beer.

GRAHAM: I like where your head is at.

JAMES: That would have been better yeah. I like podcasting with whiskey, it is Joe Rogan I blame him. He had his whiskey episode with Elon Musk, and I had a couple of whiskey episodes and it always loosens the lips a little bit and free flows the conversation. But we are not doing that today. Stone - cold sober. We have got some water in our hands and no food in front of us, and yeah, we are going to talk about computer vision and hot dogs today on the InsurTech Geek Podcast. So just a reminder for everybody out there, Graham Leslie is our chief geek at JBKnowledge Labs. He is our director of JBKnowledge Labs. Does all of our research and development here at JBKnowledge. We are a 211-person technology firm, dedicated do the insurance and construction industries. And so, Graham has been around here for a while now, since 2014, so five years and he started as an intern then went to team lead now, now he is director of research here. And kicks butts and takes names every day. Also shares my love and passion cars and trucks and likes to tear them apart and rebuild them and he is super into that, so it is good to have you on today. Today Graham, we are going to talk about Computer vision. This is a topic you have had quite a bit of opportunity to research on.

GRAHAM: Yeah, you have got it.

3

GRAHAM: 100%.

JAMES: But then there will also be technology vendors out there who offer the same datasets to everybody. So, you may end up with a hybrid where you license some tech and then you maintain some tech internally. The end output is a compiled model file, right? It is a file on a computer. And it does not learn in real - time, does it? Do you have to schedule the time for learning?

GRAHAM: That's exactly right. The processes is you give you a data set and it splits it in half. And what it does with that first half is it learns from it. And the second half it tests to see how accurate it is. And you know that is the whole second half is training because at first, it is not going to be accurate at all. You know it will be finding hot dogs everywhere. And over the course the process gets more and more accurate as it learns and adjusts and tries to get that second half more and more accurate.

JAMES: Yeah. Yeah, there are some great examples. If you want to play with this type of image recognition, a website you can go to by the way is captionbot.ai. oh, side note, before we go to Caption Bot because we will load some test images into Caption Bot and see how it does in just a second. I thought it was interesting when I started seeing the caption companies. If you don't know what the caption is, is that annoying thing where do you have to interpret the squiggly letters and lines and you have to tell it what the word is that it's trying to, or the numbers and letters, so they can prevent bots from logging into accounts. Well, Caption Bot they realized then opportunity to use it as a giant mechanical Turk bot and so they started putting in images that they thought they understood with their current model, and it can test you on, but then have humans click on, have you seen when you have to log into something it says, click on all the buses. Click on all the storefronts. What is the street sign say? It is using you for free to Crowdsource its learning model for computer vision.

GRAHAM: That's why caption services are free to developers you know? Google is the leading one with its recapture service.

JAMES: Yeah recapture is super popular, and they are doing this. They are crowdsourcing image capture and it is amazing.

GRAHAM: Feeding all of that data into maps, into their storefront detection.

4

Connect with Graham Leslie