AI Today Podcast: Artificial Intelligence Insights, Experts, and Opinion

Understanding Artificial Intelligence (AI) and all its various details including Machine Learning (ML) and Deep Learning is not easy. So it's always a great delight when someone like Siraj Raval can explain these concepts and work through them in a practical way on his YouTube channel, and his new School of AI. In this podcast, we talk about the importance of data for AI, his thoughts on the future of AI, the connection between AI and blockchain, China's adoption of AI, and the role of ML and other concepts within the larger strategy of AI.

One of the other trends making the news and getting lots of attention is Blockchain. Proponents of blockchain claim that it will have fundamental, ground-breaking impact on all industries, changing the way that we transact with one another. Blockchain will enable greater degrees of transparency, trust, and decentralized control where governments and companies can't own or manipulate the data at their will. Sounds profound! Surely, blockchain would have some impact on AI and vice-versa? In this podcast, we talk a bit about Blockchain from our AI-centric perspective, and talk about the ways in which AI can impact and influence blockchain, and ways in which blockchain will be able to add value to AI. Or perhaps this is all just double the hype? Let us know your thoughts a

Every once in a while we have a podcast interview with someone that really makes us rethink some of the popular positions in Artificial Intelligence (AI) and Machine Learning (ML). This podcast's interview with Luis Perez-Breva was one of those that really got us thinking about the relationship between data and Machine Learning and between Machine Learning and AI. Luis asks the question as to whether most ML projects are truly AI projects or are just exercises in statistics and math-based analytics. He further goes on to question whether many of the AI implementations in the retail industry are going to achieve the outcomes that the retail industry hopes for AI, and whether they are going about it the right way. Regardless of where you currently stand with regard to the relationship between ML and AI and AI adoption in retail, this podcast will get you thinking. We'd love to hear your thoughts on the subject as well!

On Sunday, March 18, 2018, an autonomous Uber vehicle operating in autonomous mode struck and killed a pedestrian crossing the road -- the first fatal autonomous vehicle accident on a public road to occur. We've now crossed the realm from the theoretical of what could happen in this scenario to the reality of the situation actually happening. In this podcast, we explore what happened in this particular situation (based on the limited information available at the time of recording), who and what could potentially be liable or have fault in this and future cases, where the autonomous vehicle industry is heading now that we're in a new reality, and what potential new laws and regulations could emerge around autonomous vehicles

In this podcast, Cognilytica analysts Kathleen Walch and Ronald Schmelzer explain their vision for what the AI-Enabled Future looks like. Cognilytica believes that AI will impact all aspects of business, personal, and social life, and in this podcast, they explain the four major aspects in which AI will impact our every day lives. In particular, we'll discuss the following key concepts

AI is impacting all industries and aspects of society, and music is no exception. In this AI Today podcast, we interview YouTube Celebrity, actress, and musician Taryn Southern who has released an album entirely produced and composed by AI called "I AM AI". We discuss the four (and maybe even five) tools that Taryn used to produce this album as well as how easy it is for creatives to get started with AI in composing and working with music. In the show notes we'll share links to Taryn's album and the various tools she used.

Chatbots, er... maybe we really mean Conversational Interfaces... are becoming more and more ubiquitous and part of our every day business and consumer lives. There's a wide variety of both text- and voice-based conversational interfaces and devices. But the ones we're most familiar with are the voice-based ones that sit on our countertops and office desks. Just how good are the voice assistants? Perhaps more tellingly, these are really just voice conversational interfaces to the machine learning capabilities of Google, Amazon, Microsoft, and others, so really, how good are those capabilities? We put a few of the voice assistants to the test and you might be surprised at the results. We explore in this podcast just how sophisticated these new and ever-present class of AI-enabled voice assistants are, and we answer the question whether the term "chatbot" is even the right one.

In this podcast, we interview Matt Gardner who heads digital strategy for the St. Louis Blues professional hockey team (NHL). The St. Louis Blues have implemented an AI-powered Facebook Messenger bot tool to enhance the fan and spectator experience. Matt realized that fans want to be engaged through social media moreso than websites and email. To help increase fan engagement, instead of building something new, they leveraged existing social media channels to have automated interactions with fans using technology from Pico.buzz. According to the linked article, The St. Louis Blues receives over 1,900 chatbot messages weekly from over 1.4 million Facebook and Instagram followers. They are now expanding their pilot program to address a broader range of use cases. Learn more about how Matt and the St. Louis Blues are using AI and chatbot technology and what they see in store for the future.

In this podcast, we are thrilled to interview Ofer Ronen, who is a general manager of Chatbase, which is a special project within the Google 120 internal project incubator. Chatbase is pioneering the space of chatbot analytics, and with the backing of Google it's sure to be dominant in the market. In this podcast, we talk with Ofer about Chatbase, so-called "UMM" errors in chatbots, and also how the Google Area 120 internal incubator works to provide a hybrid startup / large company experience

In today's podcast, we'll address some interesting hot topics that have recently been making news in the AI industry. In particular, Cognilytica senior analysts Kathleen Walch and Ronald Schmelzer talk about Hanson Robotics' Sophia Robot that's been making significant waves in popular media and press. We talk about whether Sophia is really advanced, how it's helping ... or not... the field of AI, and if it's making advances in the field of Artificial General Intelligence (AGI). Also recently, Andrew Ng announced the launch of a new $175 Million fund for AI. However, there's more to the fund than would seem at an initial read. First, it's not setup as a usual VC fund making investments in third-party startups. Rather, it's a fund for internally developed projects. And second, there's a sub-story here about how it's easier to raise money for AI-related efforts than it is to hire people to work in those efforts. Money might be easier to get these days than talent.

Robotic Process Automation (RPA) is making significant improvements into company’s operations by replacing rote human activity with automated tasks. Artificial Intelligence (AI) is poised to give this new engine of productivity a gigantic boost. Systems that leverage machine learning (ML) to dynamically adapt to new information and data will shift these systems from mere robots that automate processes to Intelligent Process Automation (IPA) tools that can significantly impact the face of the knowledge worker economy. Cognilytica is forecasting the total market for Intelligent Process Automation (IPA) solutions will grow from $0.8 Billion in 2017 to over $8.3 Billion by end of 2023. In this podcast, learn about process automation, the evolution of RPA, and the emerging IPA market and space. Also check out our official Cognilytica report on the Intelligent Process Automation market which includes market sizing, overview of the vendors in the space, and more detail on how the IPA market is evolving including more specifics about the Cognilytica IPA AI Levels we discuss in the podcast.

In this podcast, we interview Santiago Braje, Global Head of Credit Trading at ING, who is the primary lead of "Project Katana", a special AI-driven internal project funded by ING's innovation fund. The goal of project Katana is to provide an Augmented Intelligence platform that assists bond traders in market making. The primary problem they are solving is how to respond to request to bond clients where there isn't a central exchange and orders are done over the counter. The intelligent assistant and UI they built has significantly improved overall response and quality and is driving further innovation at ING.

Instead of replacing humans with autonomous agents, businesses and agencies can see significant value in enhancing the capabilities of their existing staff and leveraging AI as a “force multiplier” that enables them to do more with their existing resources. This is the key idea behind the concept of Augmented Intelligence. In much the same way that robotics engineers have created exoskeletons that empower humans to perform activities that were previously impossible or required great effort or fatigue, so too can Augmented Intelligence systems provide assistance that can enable humans to perform information tasks that were previously impossible, too difficult, or require significant amounts of time and effort.

To solve the needs of customers trying to evaluate the constantly changing landscape of AI solutions, we’re introducing the Cognilytica AI Positioning Matrix (CAPM)™. The goals of the CAPM matrix are two-fold: identify for each particular application of AI, what the “sweet spot” of required complexity for AI solutions are and how broadly applicable to a range of AI problem areas that solution needs to be; and position various solutions against that same matrix. This podcast provides a quick overview of what the CAPM is, why it's needed, how it works, and how we're using it in our research and beyond.

2018 is here! And we expect it to be a significant year for AI advancement. In particular, we have eight predictions that we believe will come to fruition in this upcoming year. Listen to this podcast and check out the accompanying article to hear about what we believe 2018 has in store for AI and the industry as a whole.