In this episode, Melody welcomes Michael Nguyen, VP of Global Data Practice and Partnerships at Innodata, Inc. Michael shares insights into all that AI is (and isn’t), the advances that have been made in ground truth data collection, and what it will take to overcome the biases that are still present in machine learning. GROUND TRUTH DATA IN MACHINE LEARNINGGround truth data is a collection of data that can’t be manufactured, it has to be captured.  Primarily used by companies who develop products for AI/ML, there are several critical components to consider when building a ground truth data set, including identifying what type of data you actually need. Michael points out data that isn’t usually readily available, such as human interaction data, and how his team overcomes the hurdles to secure it. THE HUMAN SIDE OF AISome data are very easy to come by, while some are significantly more difficult to secure.  Any data collection that has to do with humans is more sensitive, and Michael highlights the ways that they address concerns and protect privacy for anyone who is sharing data. Object and environment data collection is pretty straightforward, while speech, simulation, and human data are much more difficult aspects of AI to capture. The only way to mitigate bias with facial recognition is to capture as much data as possible. THE EVOLUTION AND FUTURE OF AIIn the wake of the pandemic, one major focus of AI is turning to healthcare. From robots doing surgery to self-driving cars, AI will continue to improve the quality of life for everyone and take care of things that humans are not best suited to take care of. Michael’s Insights“Basically anything you can think of, AI can be a part of it.” [3:50] “When it comes to human interaction, it’s really hard to create synthetic data because everyone is different.” [11:24] “I don’t think you can eliminate biases in AI, but what you can do is get as much data as possible.” [24:53] [29:18] “AI can help us do a lot of things we can’t do ourselves, especially in healthcare.”Michael’s BioMichael Nguyen is the VP of Global Data Practice and Partnerships at Innodata, Inc. He is an action driven and technology focused business development professional with over 20 years of experience delivering state of the art products and services to global enterprises. For the past five years, Michael has been focused on ground truth data for artificial intelligence and machine learning. LinksMichael Nugyen LinkedInInnodata

Data is the fuel that is going to carry companies into the future. In this episode, Melody is joined by Florin Tufan, co-founder and CEO of Soleadify, a platform that mimics the human approach to research on companies at massive scale, using a combination of artificial intelligence, machine learning, and natural language processing. Together they discuss the opportunities that are made possible with AI, what decision makers need to know about AI, and how AI can be leveraged to solve real world problems, especially in the wake of the pandemic. SOLVING PROBLEMS WITH ARTIFICIAL INTELLIGENCEFlorin admits that his initial impression of AI was largely shaped by Hollywood, and he was somewhat disappointed when he realized that these machines with the power to take over the world were not nearly as intimidating as he once assumed. Once he discovered that AI is an evolving process with change happening at a very fundamental level, he recognized the incredible possibilities available with AI.  At Soleadify, they are now stacking models to accomplish their objectives.INCREASING SELECTIVITY OF STORED DATA Nearly 90% of data is considered dark data, which is not only a drain on resources but is also a major liability to the companies that are storing it. Is there really such a thing as too much data? And if so, how can we become more selective about the data we choose to store and how we use models to generate insights from that data? Florin points out that the more data the better only applies when we know the context in which the data was created.LEVERAGING AI TO SOLVE REAL-WORLD BUSINESS PROBLEMSAt the beginning of the pandemic, Florin and his team decided that, rather than panic about something they didn’t understand, they would focus on something they did understand.  Within a week they built a free resource for finding medical suppliers, which was a major problem at the beginning of the pandemic. Since then, procurement and supply chain has become a major use case at Soleadify. AI MYTH BUSTING Communicating with non-technical decision makers can be a challenge for any AI technology based company.  Florin reveals what he would do with a magic AI wand - he wishes that  leaders already knew the basic level methodologies as well as more realistic expectations for what is possible with AI. It is harder than most people might expect, but incredible things are possible with AI right now. Florin’s Insights“The more data the better, provided you know the context in which the data was created.” [17:05] “A lot of this crisis was a data crisis, of course I see data problems everywhere.” [24:35] “I wish the myth of AI was already busted at a larger scale.” [31:55] “Everything is right in front of us, and I like to think of data as the fuel.” [44:15] Florin’s BioFlorin Tufan is the CEO and co-founder of Soleadify, a platform helping businesses get accurate and in-depth data on companies of all shapes and sizes with great SMB coverage. Soleadify is a big data startup that leverages advanced scraping and ML technologies to ingest hundreds of billions of webpages every week and perform at scale human-like ML based research to create and maintain a database of 50+ data points on 70M+ companies.LinksFlorin Tufan LinkedInSoleadify

Genetic programming is a technique of evolving programs that have the potential to overcome existing limitations and take AI to the next level. In this episode, Melody is joined by Howie Altman, co-founder and CEO of Perceiver AI, where their mission is to elevate the science of artificial intelligence. They have developed a novel form of AI-based on the foundation of genetic programming which uses an evolutionary engine to optimize through a process of natural selection. Howie highlights the genetic programming process, the potential that it has to alter the path of AI, and the extensive applications that it can solve today and in the future. ARTIFICIAL INTELLIGENCE AND GENETIC PROGRAMMINGThere is a gap between AI problems and the technologies currently available to solve them. Most current AI technologies are based on neural networks and deep learning, which are incredibly effective but utilize pattern matching as their main problem-solving tool. Additionally, the black box problem, human bias, blind spots, and the need to start from scratch every time all contribute to limitations that have yet to be solved within AI. Howie highlights the benefits and alternative solutions offered by genetic programming, using the evolution of breeding dogs as a real-life example of the same process. AN OVERVIEW OF THE GENETIC PROGRAMMING PROCESSStarting with the genome, Howie walks listeners through the possibilities that are enabled by genetic programming in a matter of seconds. After running data through Perceiver AI, the result is millions of generations of solution candidates that are tested against a fitness function. Success comes in utilizing more than just error rate, but also measuring information gained from generation to generation, identifying stagnation, and implementing extinction when necessary. This process helps to overcome the major issue of plateauing in a matter of minutes or hours, depending on the complexity of the problem being solved. UTILIZING INTELLIGENCE ARCHITECTURESAt Perceiver AI, they believe that the universe has an infinite number of intelligence architectures, i.e. frameworks by which to reason, judge, understand or problem solve. Perceiver AI aims to come up with the optimal intelligence architecture for any number of scenarios with the data at hand. With sufficient data (and generally, far less data is required than for neural networks/deep learning), problems can be solved with minimal human intervention by identifying all weaker solutions and discarding them while simultaneously evolving along the way. Each step in this evolutionary process of genetic programming takes us closer to achieving the sought after solution. PRACTICAL APPLICATIONS OF GENETIC PROGRAMMINGFrom improved crew scheduling and fueling for commercial airlines to minimizing power consumption at telecommunication data centers, there are endless optimization solutions available with genetic programming. Howie highlights carbon credits, fuel savings, CO2 emissions reduction, and waste reduction and offers listeners insights into the variety of real-world possibilities for the future.Howie’s Insights“Whereas neural networks are the digital version of the human brain, … genetic programming is the digital version of evolution.” [13:31]“As long as you can define it mathematically and in code, you can have any goal in AI you want.” [17:22]“What Perceiver [AI] is doing is coming up with the optimal intelligence architecture for the problem at hand.” [28:20]“These are practical, real-world applications, not just research-type things that Perceiver [AI] excels in.” [38:24]“The technology path that we’re on is just going to continue to explode.”...

The potential for a significant increase in AI implementation is poised to happen in the near future, and while some industries are ready for adaptation, others might struggle. In this episode, Melody welcomes Azmath Pasha, consummate CTO with over 25 years of technological experience. He is now an advisor to the tech community through board memberships including the Forbes Technology Advisory Board and brings a wealth of experience to today’s episode of the Absolute AI podcast. He highlights the present impact and future potential of AI implementation by industry, the power of digital analytics, how AI could be more diverse, and what it will take to educate and retain the next generation of programmers to support the explosion of AI that is bound to happen.HARNESSING THE POWER OF DIGITAL ANALYTICSArtificial intelligence has been around for almost 50 years and Azmath has been involved in the tech space for over 25 years, and AI specifically for nearly a decade. He has watched the trends as both people and companies have harnessed the power of data collection and infused it with the power of AI. Today and in the future, the leaders and communities who win will be the ones who understand and utilize the power of digital analytics. Considering the future of work and the future of data, digital technology is available to all and an increase in diversity will play a critical role in global adoption.INCREASING DIVERSITY AND SUPPORTTechnologies have the power to make the world more fair, peaceful, and just. Azmath shares his vision of providing a greater bridge between technology and society, whether for combating COVID-19 and its aftermath, understanding fashion trends, or incorporating AI into business processes. In order for AI to be adapted by senior-level decision-makers, it must be presented as a tool for better decision-making at every level.AI AS A GROWTH ENABLERData cannot always be simulated, although some AI developers are working to achieve just that. Synthetic data can be a helpful augmentation of real data, and there are benefits to utilizing synthetic databases and new analytics technologies. On a strategic level, there is a three-pillar approach to using synthetic databases, which Azmath clearly outlines in relation to organizing and structuring data that is already available.AI ADAPTATION BY INDUSTRYMany industries have quickly adopted AI, while others have struggled to implement all that AI has to offer. Azmath highlights some of the industries that have underutilized AI and are poised to experience a major transformation in the next few years, including entertainment and gaming as well as manufacturing with the use of “cobots.” Over the next 20 years, the use of AI is going to continue to expand and affect every industry, prompting a need for increased regulations and ethical use to monitor the gathering and usage of quality data.Azmath’s Insights“AI was just bound to happen. All of the technologies are moving toward machine learning and algorithms are always getting more commoditized.” [1:36]“[Users have to] show AI as a tool for better decision making at every layer.” [10:38]“Harnessing the benefits of new database and analytics technologies, that’s what we need to focus on.” [15:29] Azmath’s BioAzmath Pasha is a consummate Chief Technology Officer with 25-plus years of experience demonstrating success leading large-scale and high-value digital transformation engagements within the evolving advanced analytics, AI, and cloud-based technology markets.LinksAzmath Pasha...

From automating manual processes to utilizing the millions of health data points in predictive analytics, the future of healthcare stands to benefit greatly from the application of AI and machine learning. In this episode of the Absolute AI podcast, Melody welcomes Mark Kujawski, founder, CEO, and Managing Director at Aztech Health. Mark has had a long career working on the front lines of technology transformation with companies like Accenture, Oracle, and Hewlett Packard. As a strategy consultant, he has helped many healthcare organizations improve their delivery capabilities and is now leading his company, Aztech Health, to liberate patient health data. Together, they discuss a facet of AI that affects every one of us — utilizing health data. They examine the role that machine learning can play in making more informed healthcare decisions, the stumbling blocks that have yet to be overcome in making this transition, and what exactly the future of healthcare and AI could look like.

For better and for worse, the future of AI is coming at us faster than ever. In this episode of the Absolute AI podcast, Melody welcomes Tim Huckaby. Tim is an industry luminary focused on AI, Computer Vision, Machine Learning, AR/MR, Data Visualization, & Edge Computing. Tim has over 35 years of technology experience including 25 years with Microsoft where he worked on some famous and not-so-famous Microsoft Server products in the late nineties and learned how to build scalable enterprise software. He founded InterKnowlogy in 1999 and Actus Interactive Software in 2011 which became VSBLTY in 2015 and now is an AI consultant for Innodata. Tim is an accomplished keynote speaker and writer, authoring three books and hundreds of articles on topics ranging from Emerging Experiences in Artificial Intelligence, Computer Vision, Voice Recognition, and futuristic interfaces. Together they discuss Tim’s computing predictions that have already come to fruition, the ones he has for the future of AI, and the stumbling blocks of AI that will have to be overcome before it can truly become a problem-solving part of our everyday lives.

At the intersection of both human and AI capabilities, we find the critical value of machine intelligence. In this episode of the Absolute AI podcast, Melody welcomes Jinsook Han. Jinsook’s passion lies in the future of work, at the intersection of human and artificial intelligence where technology assists, augments, and accelerates human ingenuity. She is currently the managing partner and founder of Spruce Peak Ventures LLC that advises companies on digital transformation, product roadmap, and growth strategies, and invests in companies that are working on the future of work and manufacturing. Jinsook blogs about human+AI topics in the semi-monthly newsletter HIRscape — Human Ingenuity Realized at LinkedIn. Together they discuss what it takes to lead a digital transformation, when AI needs to be directed by humans, and the true value of AI in meeting the needs of human beings.

As companies seek to integrate AI and other advancing technologies, disruption is happening at a faster and more affordable rate around the world. In this episode of the Absolute AI podcast, Melody welcomes entrepreneur, educator, and executive Maaike Doyer. Maaike is a regular speaker on management and innovation events, delivering keynote speeches and workshops about “Business Model Innovation,” as well as the founder of Epic Angels, an investor network of female executives and operators who have built and expanded companies in all parts of the world. Together they discuss the role that AI can play at the core of the business model shift from physical to digital as well as how companies can determine if AI is the solution that they need. Maaike also identifies which companies and technologies are ripe for disruption, from lab-grown meat to quantum computing, and the work that Maaike is doing with the Epic Angels investor network.

The process of moving AI beyond the theoretical and into the practical as it becomes part of our everyday lives is a complex one. While advancements and opportunities in the AI/ML space abound, there is still a long way to go. Once considered the Wild West of the digital transformation, AI is now facing questions about processes, regulations, purpose, and critical design.In this episode of the Absolute AI podcast, Melody welcomes Zachary Hanson, Head of ML Product at Brightcove, an online video platform that helps customers experience the incredible potential of video. Zach is a product management expert and remote working enthusiast who has worked at several of the world’s largest artificial intelligence companies including IBM Watson, Capital One, and Wells Fargo. They discuss the pillars of a successful AI platform, the importance of design thinking in every aspect of the customer’s AI experience, empowering AI scaling strategies, and Zach’s tips for successful remote working in any environment.

The relationship between humans and AI is growing stronger and more connected every day. With the capacity to retain knowledge and provide insights that humans didn’t know they were seeking, AI is becoming a more integrated part of everyday life. But will AI ever fully replace the human ability of knowledge workers?This week, Melody is joined by Scott Litman, the co-founder and managing partner of Lucy AI, an AI-powered knowledge management assistant, for a conversation about the future of AI learning and knowledge management. Scott details the evolution and advancements in AI, including real-life applications in today’s business environment. He reveals why Lucy AI focuses on knowledge rather than simply gathering data and shares insights into some of the real-life applications that AI has the potential to offer in the very near future.Scott’s BioScott Litman is the co-founder and managing partner of Lucy AI, an AI-powered knowledge management assistant. As an entrepreneur, he is in search of new ways technology can advance the mission of knowledge workers from sales, marketing and research, and insights. From the early days of the internet and the first websites, to business portals of the “dot com” era to the latest generation of artificial intelligence — Scott has a long history of building businesses that help Fortune 1000 marketers and the agencies that serve them take advantage of cutting-edge digital transformation.

Data, especially when leveraged by AI, has the potential to mitigate risk, reduce expenses, and boost revenue. No wonder countless businesses today are working to become more data driven. But how to turn raw data into a business asset rather than a liability remains a challenge across industries. This week Melody is joined by Prashanth Southekal, the Managing Principal of DBP-Institute, a Data Analytics Consulting and Education company. They discuss how companies can utilize data and analytics to achieve monetizable business results. Prashanth offers a glimpse into the massive amounts of data that companies are managing today and how to wield analytics, data, and intuition to drive informed decision making. He outlines the steps that companies need to take to improve data quality and make their data work for them.

Co-Founder and CEO of Agolo, Sage Wohns, joins Melody on the podcast today to discuss his programming and business strategy experience and how he has combined them to advance the role of AI particularly in finance and news organizations. He also reveals the keys to the founder role in which he has excelled, and the role models whose example he feels are worthy of emulating.Absolute AI HomepageInnodataAgolo Homepage

This week, Melody welcomes AI educator, author, and quantum ML research scientist at Zapata, Luis Serrano, to the Absolute AI podcast. Luis discusses his journey to the world of quantum computing, the enormous potential in this ever evolving field, and his highly successful initiatives to share his knowledge. THE JOURNEY TO QUANTUM COMPUTING Luis’ early interest in Mathematics led him to become a Math professor which sparked even further interest in machine learning and AI. Eventually working at Google and YouTube, Luis was able to combine these interests with his love of teaching. Following his curiosity and a recommendation from a friend he ended up pursuing his increasing fascination with quantum computing, resulting in his current position with Zapata Computing. MACHINE LEARNING AND QUANTUM COMPUTING At Zapata, Luis and his team work at finding quantum advantage and supremacy through the exploration of and experimentation with qubits. There remains a great deal of work to be done to make the vast potential of quantum computing a reality, and Zapata is working on every aspect of it. PODCAST HIGHLIGHTS 1:54   The Journey From International Mathlete to AI to Quantum Computing4:16   The Coalescence of Machine Learning and Quantum Computing at Zapata16:43        Pushing the Physical Boundaries of Quantum Computers20:02        Grokking Machine Learning and Its Universal Appeal26:08        The Impact of AI and Machine Learning on Our Everyday Lives29:41        Educating Within Spanish and Latin American Culture GROKKING MACHINE LEARNING Luis’ highly accessible book demonstrates his skills as an educator. By making the concepts involved more easily understood, he takes away the reader’s apprehension of complexity, and empowers them in the process. AI, MACHINE LEARNING, AND EVERYDAY LIFE Luis believes that we are doing linear regression in our heads all the time which helps us better understand machine learning algorithms. His hugely popular YouTube channel has a particularly enlightening video regarding this concept. EDUCATING WITHIN SPANISH AND LATIN AMERICAN CULTURE While teaching Math and machine learning in Spanish is difficult, Luis enjoys it a great deal because it makes the lessons accessible to those that may not otherwise have the opportunity to learn it due to the current sub sufficient Spanish language resources. The need for diversity in this field is great as AI must reflect all human perspectives if it is to be successful. Luis feels that he is always in some way teaching and so must always be learning something new. More About Luis Serrano Luis is the author of Grokking Machine Learning, the creator of the serrano.academy website and YouTube channel, and a quantum AI research scientist at Zapata Computing where he is involved in developing machine learning algorithms to work in quantum computers. He is also a frequent speaker at artificial intelligence and data science conferences.During his time in Silicon Valley, he worked at the following companies:Apple: Lead AI educator, in charge of teaching machine learning to the employees and doing internal consulting in AI related projects.Udacity: Head of content for AI and Data Science, managing the team that created online courses in AI, ML, Deep Learning, Data Science, etc.Google: Part of the video recommendations team at YouTube, where we trained machine learning algorithms to recommend videos in the main...

Melody’s very special guest on the podcast this week is Darren Oberst, Senior Corporate Vice President and Global Head of HCL Software. Formally educated in the fields of Law, Physics, and Philosophy, Darren has built upon his lifelong interest in technology, especially coding, to become a leader in product and corporate development throughout the world. Today, he takes listeners through the journey of his career, offering valuable insights into the world of technology, AI, and leadership, which are as fascinating as they are informative. Darren begins by describing the role that his background in natural science and the humanities played in the vast amount of success he has enjoyed throughout his career, particularly his innovative work with HCL. A passionate hobbyist in ML development and research, Darren also has a great deal to share about the success criteria necessary when developing and testing models. This, paired with his many years of international experience, render him a leadership expert with extensive insights and helpful advice in this area as well. As you listen in, the sheer amount of information and wisdom which Darren possesses will strike you, along with the sincere enthusiasm this seasoned professional brings to the work that both inspired him as a child and continues to excite and drive him forward today.Before becoming a part of the founding team of HCL Software, Darren spent 10 years at IBM in a diverse set of leadership roles and had also launched and run businesses throughout the world. He has served as the Senior Vice President and General Manager for webMethods, a leading e-business infrastructure software company, and started his career in Silicon Valley as an investment banker at Robertson Stephens. Darren has a JD with Honors from Harvard Law School and a BA summa-cum-laude from UC-Berkeley with dual degrees in Physics and Philosophy. Episode Highlights: 1:51 Darren’s educational history and its role in his journey to professional success6:03 His role at HCL and its integration of AI15:09 Darren’s hobby as a ML developer/researcher and its impact on his perspective regarding models29:05  His methods for becoming a successful leader33:47  Darren’s vision of the future for AISoundbites from the Expert:Darren’s educational history and its role in his journey to professional success 2:04   “I think it gave me a pretty broad set of skills, just in terms of...critical thinking, breaking down...problems, coming at it from a lot of different angles.” His role at HCL and its integration of AI 10:05   “A big...part of our playbook has been, ‘let's get the right foundation in place, let's not try to solve every problem, you know, until we're ready for it.’” 11:35 “That's very much the way that we sort of rolled out our cloud strategy - crawl, walk, run - focus on making sure the product is right before you just sort of throw it up on a cloud, and make sure that you have a differentiated strategy.” 13:28 “I think in the real world, start with the simplest model, the simplest solution that you have, make sure that you've got really good data and really good data quality, and that's usually the best place to start in any kind of AI initiative.” Darren’s hobby as a ML developer/researcher and its impact upon his perspective regarding models 16:15 “These types of predictive technologies grounded in machine learning aren't going away. They are the future, you know, they've become more prevalent in our life today than they were five years ago. They're going to be even more...

Joining Melody on today’s episode is Elizabeth Pritchard, recently named CEO of Bitvore - the leader in AI-driven intelligence from unstructured data. Elizabeth begins by sharing her journey into the STEM and finance industries, her 19-year tenure at Goldman Sachs, and the evolution of alternative data in the financial industry. She goes on to explain what alternative and unstructured data are, the challenges of extracting information from it and leveraging AI and the structured data it creates.  Elizabeth illustrates how traditional and alternative data can offer differ perspectives on a company, for example they may claim to be green, but ESG data shows that they are actually heavy emitters. These insights can help investors gain a more nuanced view of companies and help combat ‘greenwashing.’ The conversation concludes with her passionate advocacy work empowering young people, especially girls, to pursue STEM, and offers her vision of the world in the year 2041. Brimming with knowledge, wisdom, and enthusiasm, Elizabeth Pritchard is a well-known serial innovator, data activist, and analytics-driven executive, and, as you will hear today, a gifted educator and agent of change as well.  Elizabeth Pritchard has 25 years of experience as an executive in financial services, driving data and technology innovation for financial institutions and start-ups. She was Global Head of Market Data at Goldman Sachs and COO of the Global Data Science Group at AIG, co-founded Crux Informatics, where she was Head of Go-To-Market Strategy.  Just prior to accepting the CEO position at Bitvore, provided advisory services to alternative data and data infrastructure providers through her own company, White Rock Data Solutions. Elizabeth also advises industry professional associations SIIA and FISD Alternative Data Council on go-to-market strategy, and serves on the Board of Directors at Eagle Alpha and Global Data.  Episode Highlights: ·   Elizabeth’s journey into STEM and finance·   Her time at Goldman Sachs and the evolution she saw in the financial industry from a data driven innovation and AI perspective·   Examples where traditional and alternative data offered differing views·   Unstructured data and the challenges in extracting information out of it·   Leveraging AI and the structured data it creates·   What attracted Elizabeth to Bitvore and the initiatives there about which she is most excited·   How Bitvore is bringing insights from ESG data to battle company ‘greenwashing’·   Elizabeth’s advocacy with Girls Who Code and STEM++Inno Soundbites from the Expert: Elizabeth’s journey into STEM and finance 2:05   “I was really born with this innovator bug.” 2:43   “’Listen, when you come here in the morning, you've got to put on your thick skin.’ That is the lesson…and that's wisdom that has really resonated, if you will, throughout my career.” 3:28   “I learned very much so to focus on what's really happening, and learn to be data driven,        and let the data do the talking. And always be fact, based in decision making.” Her time at Goldman Sachs and the evolution she saw in the financial industry from a data driven innovation and AI perspective 6:37   “That whole discovery, if you will, of this world of data that can describe not only companies actually, but also how economies are performing…being able to mine the  data in the world that's being made available in an ever increasing rate - that was the...

Welcome to the very first episode of the Absolute AI podcast, where, each week  you will have the opportunity to hear the humans behind artificial intelligence talking about cutting edge innovation and the unique challenges posed by this new technological frontier. The very special guest for this premier episode is Dennis Mortensen, CEO and Founder of x.ai, a sophisticated AI platform that solves the problem of scheduling meetings. A serial entrepreneur who built and successfully exited 4 companies as a Founder and CEO, Dennis is also a recognized leader, author, and university instructor in the field of Data Analytics and AI. Today, he delves into this vast amount of experience to pass on wisdom and advice for all to hear. Dennis begins the interview by sharing the origins of his interest in computer science, his experience of becoming an entrepreneur, and starting x.ai. He goes on to discuss the technical challenges that he and his team faced at the start, their work in flipping the onus for accuracy onto the client, and the concepts of educating the market and explainable AI. He finishes up by detailing how they set up their system to distinguish between important and superfluous information, and offering his perspective on the future of work. Possessing an innate ability to render the complexities of his work entirely accessible, Dennis shares his experience, knowledge, advice, and thoroughly enjoyable sense of humor with listeners here today – a fitting springboard to this fascinating new podcast. Episode Highlights: ·   The origins of Dennis’ interest in computer science·   Becoming an entrepreneur·   Starting x.ai·   The technical challenges he and his team faced·   Flipping the onus for accuracy onto the client·   Pitfalls of educating the market·   Explainable AI·   Setting up their AI system in a way to distinguish between important and superfluous information·   Future of Work·   Dennis’ vision of the future Soundbites from the Expert: The origins of Dennis’ interest in computer science “One day on the telly, they showed an old movie called Wargames, you might not remember it, but that really touched me.” Becoming an entrepreneur “The only reason that I briefly thought I would make a small entrepreneurial run was that the company that I worked for in college went bankrupt.” “What I'm trying to do instead is just walk around, look at my life, and take note if there are things that don't work the way they should, or to the point where I actually get annoyed or disappointed.” Starting x.ai “Any startup is usually one of two challenges…either a tech/science challenge of some sort, or a market challenge.” The technical challenges he and his team faced “There's no way I can ever come up with any model that will be able to kind of predict anything if I don't even know what the end of this list looked like.” “It's not as black as white as as this, but there's probably two types of AI sort of types of predictions that you could make. There’s low accuracy predictions for where whatever prediction you make, it is of value. Then there’s high accuracy predictions, where if you don't reach a certain kind of threshold, anything which you make, it's really not of value.” Pitfalls of educating the market “I'm just saying that if you're in a position where you need to kind of reframe it and rewire the full population of your...

Artificial intelligence is rapidly becoming interwoven into the fabric of our society through the way we communicate, work, and problem solve. Our mission is to share and amplify the voices of the creators, thinkers, researchers, and innovators taking AI from prototype to production. With each episode, we will dive into the nitty-gritty details of how AI is helping to solve common and complex challenges.