A picture’s worth a thousand words. So, why wouldn’t retailers want shoppers using an image search instead of a keyword search? The thing is… they do. And one company called ViSenze is making it possible. On the latest episode of AI: IRL, I speak with Oliver Tan, co-founder and CEO of ViSenze. We discuss:  How an image search engine can work for apparel shopping Data on how shoppers have responded to AI visuals Digital experiences that transcend online shopping  &nbsp; Resources:  Visual Search - Why Retailers Should Care &nbsp; To listen to our other episodes, check us out  on Apple Podcasts. Or if you don’t use Apple Podcasts, you can also find every episode here.

42. How AI Visuals are Revolutionizing Shopping

Typically, we feed our AI invented datasets that don't represent real life situations and scenarios. These models are preparing AI for an unrealistic environment that doesn’t work IRL. But James Dean is changing models at his company, SenSat. They’re using breakthroughs in camera and inexpensive drone technology to capture real geographies. They layer these geographies with everyday obstacles — like people, temperature, lighting — to develop models that replicate real life geographies, creating what James calls “digital twins.” James came on this episode of AI:IRL to tell us all about how he’s creating “a SimCity of the real world.” What we talked about:  AI models 3D Geographies 3D Geometries&nbsp; Digital twins LIDAR Large datasets How AI is impacting the construction industry AI in the infrastructure industry  This discussion with James Dean was taken from our AI: In Real Life podcast. If you want to hear more AI episodes like this one, check us out  on Apple Podcasts here. &nbsp;

43. How Real-World Models Drive Rapid Insights for Everyday Application

Manufacturing has long had robots carrying out certain tasks — but those robots require a high amount of inputs on the front end. Then, once those inputs are created, the robots are “stuck” in that position. Throw off the temperature of the manufacturing floor, the orientation of an object, or any other small detail, and that robot has very little ability to respond. But now, with advanced robotics, at least one company is trying to create more aware robots that can respond to their environment. On this episode, Costas Boulis joined us to share how  Bright Machines is reinventing manufacturing with advanced robotics Costas is the Chief Scientist at Bright Machines, and was previously an Applied Scientist at Amazon and a Data Scientist for Microsoft, among other advanced science positions. He has a PhD in Electrical Engineering, and received scholar positions at both John Hopkins and Stanford. What we talked about:  Industrial manufacturing IIOT AI, robotics, and the future of industrial manufacturing  This discussion with Costas Boulis was taken from our AI: In Real Life podcast. If you want to hear more AI episodes like this one, check us out  on Apple Podcasts. &nbsp; If you don’t use Apple Podcasts, you can also find every episode here.

44. The Intersection of AI & Manufacturing

Authentication used to be an easy process.&nbsp; It all started with the king.&nbsp; The king would require a wax seal around any form of parchment or communication that was produced, verifying that it was actually coming from the person that it was supposed to be coming from. If it wasn’t sealed with the king’s seal, it wasn't legitimate communication.&nbsp; It’s become a little more complicated since then.&nbsp; On the most recent episode of AI:IRL, we sat down with John Baird, Founder at CEO at Vouched for a talk about:  The challenges we face with authentication. How to eliminate the friction present in identify verification.&nbsp; What AI can do to make those challenges less of a burden.&nbsp;

45. AI & The Future of Verification

This week's episode is just me — Ryan Lester — looking back at 2019 and reflecting on what we've seen this year. I've done about 50 podcasts, so I had a lot of great conversations with my guests as well as with my clients and with many of you who listen in. Here's what I learned:  Tech titans such as Google, Amazon, and Microsoft invested heavily in tools that make AI more accessible and easier to use All this investment is still the exception, not the norm These non-traditional people who should be coming to your table ...and why you should be cautious about making tech your scapegoat  This conversation was taken from our AI: In Real Life. If you want to hear more AI episodes like this one, check us out on  Apple Podcasts here. If you don’t use Apple Podcasts, you can find every episode here.

46. A Look Back at AI:IRL in 2019

The White House recently released  to guide the future of AI in the US. Did they go far enough? In this episode,  discussed his 3 takeaways on the AI principles, and what they could mean for the future of AI with the US and around the globe.&nbsp; Ryan Lester is the Sr. Director of Product Marketing at . What we talked about:  The US government involvement gave us a platform to discuss AI At least 2 areas of AI need further exploration (eliminating bias and demystifying AI)&nbsp; The US government can be a catalyst for the private sector  This discussion with  was taken from our AI: In Real Life podcast. If you want to hear more AI episodes like this one, check us out . If you don’t use Apple Podcasts, you can also find every episode .

47. 3 Takeaways from the the US Government’s 10 AI Principles

Twenty years of Google and Wikipedia, but information is still not at our fingertips.&nbsp; What if we could automate the collection of information using both AI and humans? And what if we could do it by indexing and creating a better entity map? On this episode, I interview , Founder and CEO of , the world's first self-constructing knowledge database built by artificial and human intelligence, about how to think about, compile, and organize knowledge. What we talked about:  Building an index of human readable information and machine readable information How to automate the collection of information Getting good at topic prediction ...and how humans can fill the gaps left by AI.  This discussion with  was taken from our AI: In Real Life. If you want to hear more AI episodes like this one, check us out on . If you don’t use Apple Podcasts, you can find every episode .

48. The Ways AI and Humans Work Together to Compile Knowledge

Responding to high-quality leads who raise their hand and are ready to buy is the icing on the sales cake. But the actual cake is made up of mid-funnel prospects who have some level of interest, but aren’t ready to talk with a sales rep … and this part of the cake is thick with leads.  (Founder of ) came on this episode of AI: IRL to share how he’s helping customers use AI to respond to thousands of mid-funnel leads, feed info back into the CRM, and then pass off communications to sales reps when the buyer is ready.&nbsp; What we talked about:  The problem: determining intent without soaking up sales reps’ time How Exceed.ai responds to customers Secondary benefits of AI email responses:   1) Ensure you add qualification questions to automated responses 2) Push data to your CRM 3) Analytics    This discussion with  was taken from our AI: In Real Life podcast. If you want to hear more AI episodes like this one, check us out . If you don’t use Apple Podcasts, you can find every episode .

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