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Will Uppington, TruEra

In this episode, I talk with Will Uppington, CEO of TruEra about how trust is a critical output of machine learning and AI systems and AI quality management must be baked into development in order to build trust-worthy systems. We delved into the five core dimensions of model quality, the importance of iterating data and models in parallel, the state of the model development platforms and tools market, the regulatory environment around trusted AI, and ended with some career advice for people entering the field.

In this discussion with Colin Toal, CTO of Chisel.ai, we uncover the challenges being faced by this 5000 year old industry. We walk through the structure and practices of the commercial insurance sector, discuss why it works the way it does, and how AI is now helping to transform it one step at a time. We unpack the differences between basic insurance which is standardized vs. commercial insurance where every policy is a unique snowflake and how that poses challenges for automation and interconnection. We dig into the historical value of automation, and then we touch on the never-ending debate of build vs. buy. Finally, we closed the conversation with some advice to aspiring AI and machine learning engineers looking to build a career.

Hear how the world’s best companies use Turing.com to hire the world’s best engineers. Listen to Vijay Krishnan, CTO and Co-Founder of Turing discuss how they match the best companies with the best global engineering talent using a combination of deep domain expertise and machine learning. Vijay also shares his lessons to founders and entrepreneurs as well as to aspiring machine learning and AI engineers.

How can an AI understand language? Computer-human communication is undergoing a revolution and AI can now listen to, understand, and speak back to us in much more powerful ways than it could before. On this episode, hear Scott Leishman discuss how AI can now write news articles, blog posts, poetry, and novels and how work done in the recent past is making it easier than ever to build incredibly powerful AI applications that can communicate with human beings.

Listen in to my conversation with Kevin Tu from DFJ Growth while we discuss the next ten years of the AI market, the difference between AI-enabled companies and AI-first companies, characteristics of well-funded startups, the structure of the AI ecosystem, whether AI businesses are really different from a business model perspective, when to build vs. buy AI infrastructure, and finally, some advice to entrepreneurs building AI focused companies.

It is now possible to radically grow your business by improving the hand-off between marketing, sales, customer success, and even finance through the use of advanced intelligent virtual assistants. In this podcast, we’ll talk to Jim Kaskade, CEO of Conversica about how they’re helping their 2000 global customers speed up communications, improve customer satisfaction, get better lead coverage, qualify prospects more effectively, and increase deal close rates (up to 400% improvement!)

Callan Schebella, Inference Solutions

It is possible to use AI based speech in many business situations. We’re entering a new era where computers are so good at communicating with us via both spoken word and text conversations that they can perform tasks traditionally handled by call centers. In this conversation with the CEO of Inference Solutions, you’ll learn about the long arc of Natural Language Processing, Conversational AI, and the rise of the Intelligent Virtual Agent Market. We also discuss AI product management and positioning and pricing that will be helpful for anybody building a complex AI-based product or service. Finally we close out with some advice to buyers who are trying to make sense of a noisy marketplace.

NOTE: Since the recording of this podcast, Inference was acquired by Five9, the leading provider of cloud contact center software.

Marketers today are drowning in data and have little insight. Too many dashboards from too many channels, all with different user interfaces and data schemas, means that making sense of it all takes too much time, and often doesn’t lead to clear insights such as “this channel doesn’t work and we should stop spending on it”. To make matters worse, each platform’s analytics are siloed and their goal is to increase, not decrease, your spend on that platform. GlanceHQ.ai was formed by a team of marketing agency experts to solve this problem Hear Roy Nallapeta discuss the state of the industry, why marketing software needs to be more like a Tesla, and how leveraging artificial intelligence and machine learning can help marketers make better and more effective allocation decisions in much less time.

Self-driving cars must get better at understanding people’s intentions by “reading” the body language of the humans around them, so that they can co-exist more safely with us. In this amazing discussion with the CTO and co-founder of Perceptive Automata, we will learn how a branch of cognitive science known as psychophysics is being used to teach cars about the intentions of the humans around them so that they can be better and safer drivers.

Neural networks can be made faster, cheaper, and smaller. This can result in higher performing and lower cost operation of complex AI applications at the edge of the network –where ever that edge might be such as a factory, vehicle, ship, or other remote location. In this episode, hear Jags Kandasamy explain how Latent AI’s development platform helps customers and suppliers in every industry compress and adapt neural networks to run “at the edge” and how this ultimately speeds up application development and delivery, as well as improves the performance of the AI application itself. Also we’ll touch on the relationship between Edge AI, and 5G.

Hear Seth Clark, Head of Product at Modzy, explain how the largest Military, Civil government, and Enterprises design, build, and deploy large-scale AI projects from the lab into production in a way that is quick, safe, and secure. Topics include: the AI Pipeline; the differences between model management, Model Ops, and MLOps; what all the members of an AI team should do (and more importantly, NOT do); how the answer is not build-or-buy, but build-AND-buy; what new threats exist in an AI application and how to defend against them; as well as how to build AI systems that can explain their decisions to humans.

It is now possible to radically grow your business by improving the hand-off between marketing, sales, customer success, and even finance through the use of advanced intelligent virtual assistants. In this podcast, we’ll talk to Jim Kaskade, CEO of Conversica about how they’re helping their 2000 global customers speed up communications, improve customer satisfaction, get better lead coverage, qualify prospects more effectively, and increase deal close rates (up to 400% improvement!)

Get a job in AI Product Management (and where to learn AI online)

Mark Cramer

Hear Mark Cramer explain his view on Product Management, his definitions of AI and related fields, why he thinks AI is cool and life-long learning is important, how the job of the AI Product manager is challenging (and more fun!) than a regular Product Management job, and what to do if you’re considering becoming an AI product manager.

Artificial Intelligence, Neural networks, and automation

Tom Taulli

Hear Tom Taulli discuss how Artificial Intelligence, Neural Networks, Deep Learning, and Automation will impact companies, jobs, and people. In addition to those points, we will also discuss: Strong vs. weak AI; if Artificial General Intelligence is a threat; what the next 10 years of AI will bring; what the state of the art is in AI; how and when AI will impact jobs; the relationship between AI and other technologies like 5G, edge computing, and quantum computing; and finally some advice for adopters considering bringing AI into their organizations.

First episode!

Welcome to the first episode of the Productive AI podcast. The goal of this podcast is to simplify Artificial Intelligence and Machine Learning so you can understand how to apply it to your organization.