When our computers are solving problems faster than people ever could, what do we do with the answers? How do we use the data in a way that serves everyone? This week, host Derek is joined by two experts to talk about the revolution happening now in machine learning and data collection. First, Mike Tamir is the Head of Data Science and AI for the Susquehanna International Group. Then, Nuria Oliver is the Co-Founder and Director of the Institute of Human Centered AI.  The two discuss how AI will be able to create and test products in the future, and how we can best succeed in the intersection between AI and creativity. 

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• What is LIDAR (Light Detection and Ranging) technology, and what type of information and data can it help us generate? 
• How do we hone data to make self-driving cars even safer and make the testing process even more efficient? 
• How cars have become more computerized, and what that automation will look like down the road. 
• Nuria discusses a high stakes user study that underwent ethics approval from MIT, and how they brought in the proper safety precautions.
• Some of the foundational things you need to be able to train machine learning models in a supervised fashion.  
• We can have systems that not only automatically detect and recognize the maneuver of drivers, but predict them. What are the opportunities for this, but also, what are the challenges? 
• What capturing human behavioral data looks like on a massive scale, and how machine learning can help identify business opportunities and create better customer satisfaction. 
• Human decisions have gotten us through a lot of situations, but we have unciouscnsess biases, we are susceptible to corruption, we have emotions that get in the way, physical needs, etc. 
• Nuria talks about the value in human collaboration and how automated work may help us be able to develop deeper relationships and free up time and energy to be more creative. 

Resources Mentioned: 

• NI
• Nuria Oliver
• Mike Tamir 

Our ears only have a limited range to pick up sounds, so how do we make the loud things soft enough and the quiet things loud enough that we can hear them? We test. This week, it’s all about sound as host Derek welcomes two experts in the field. First, Jim Underbrink is a Former Boeing Technical Fellow with 35 years of experience in Dynamic Data Acquisitions Systems and Test Methods. He details some of the rigorous testing a plane goes through to make sure it can operate correctly and determine not only how loud the airplane is, but how we can locate and reduce the loudest sources an aircraft emits. Then, Kevin Seitz-Paquette, Director of Phonak Audiology Research Center, shares some of the exciting advancements in hearing aid technology that combat hearing loss while lessening the surrounding stigmas that come with it. He touches on testing to make sure the products are built in a way that gives us real-world solutions in a safe and effective manner. 

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• How testing sound in aviation has developed over the years, and Jim gives us a behind-the-wings look at what goes on at Boeing’s noise lab. 
• How testers started studying different components of the whole airplane using models to see where certain noises were coming from, and how loud they were. 
• Why it matters to test the different volume noises given off by airplanes, not only to passengers and airline workers but also the community surrounding the airports. 
• How 800 microphones in a mathematical pattern were used to essentially take pictures of noise as airplanes approached and took off from a runway. 
• What race track patterns are and how they apply to testing. 
• Kevin talks about how the technological development of hearing aids can help lessen the stigma of hearing loss and having to wear a hearing device. 
• How they test hearing aids with a “crash test dummy” that models an actual human being and recreates real world examples of how the hearing aid may both work and malfunction.

Resources Mentioned: 

• NI
• James Underbrink 
• Kevin Seitz-Paquette 
• Phonak 

As our need for mobile and wireless connectivity becomes more essential, the technology and testing around our phones are also developing at breakneck speed. Cameras get bigger and better screens, confirming our identity becomes more seamless, and how we can quickly collaborate matches our need for connectivity on the go. This week, host Derek Burrows talks with two experts about the testing behind innovation, who’s got a front-row seat watching the need for speed, and who’s in the race to get us our data as fast as possible. First, Jennifer Alvarez is the CEO of Aurora Insight, an IT company that uses its proprietary technology to measure the radio frequency spectrum, and Jeremy McKinney is an associate attorney with Dunlap Codding, a law firm that specializes in intellectual property. They talk about testing in a race of innovation, the future of acceleration, and how times have changed from our flip phones in the 90s. 

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•  5G is not just enhanced 4g. It’s going to enable brand new applications that we can only imagine. Jennifer breaks down the different “G’s” and how we can drive innovation to solve problems. 
• Aurora is agnostic of the network operator and technology, making it easy to be independent and truly reflect what the network is doing. 
• The more data your signal can carry, the harder it is to actually transmit. 
• How do we connect machines and get rid of all those cables and instead, enable wireless connectivity that is super fast, low latency, very reliable, yet able to communicate high bandwidths of data? 
• How do we even begin to test tech that has to go through a sea change every time a new iteration drops? 
• A few of the pros and cons of technology where the speed of innovation is so important. 
• With Aurora Insight’s technology, the real innovation is its ability to vacuum  up all the spectrum, not just focusing on collecting cellular or LTE from a mobile network. 
• As an associate attorney specializing in intellectual property, Jeremy is able to observe the speed of innovation firsthand. 
• What is a standard essential patent? 
• Aurora Insight’s approach has been to make the software do all the work, and have relatively generic hardware. 

Resources Mentioned: 

• NI
• Aurora Insight 
• Dunlap Codding