Podcasts about prediction machines

In today's world, data underpins almost everything—from the financial decisions we make to the way businesses and governments operate. What's more, in the world of AI, data is the fuel and the ‘secret sauce' that produces the time saving outputs and future potential breakthroughs. But while companies are collecting more data than ever before, many are still struggling to store it effectively, let alone make sense of it, and most of us are not equipped with the skills we all need personally to have sustainable careers in this new, AI-powered era.In our episode this week, we speak with Pinar Ozcan, Professor of Entrepreneurship and Innovation at Said Business School, Oxford University, to explore the profound impact of AI on jobs, skills, and industries—and what you can do to stay relevant.Pinar is a leading expert on AI disruption, open banking, and the strategic role of data in innovation. From the rise of AI-driven financial services to the skills that will define the workforce of tomorrow, she shares invaluable insights on how individuals and businesses can navigate this changing landscape.In this episode you'll hear: How AI and data are reshaping industries, particularly finance and fintechPractical ways you can stay competitive in the AI-driven job marketWhy data literacy is becoming a must-have skill for professionalsPinar's take on which countries and companies are leading the way in AI regulation and educationHow AI is both creating and eliminating jobs, and what that means for your careerWe'll also hear about the personal AI tool that's transformed the way Pinar works.Don't miss this fascinating and thought-provoking conversation with Pinar Ozcan.Useful LinksPinar's websiteLearn more about Pinar's research: Oxford Future of Finance and Technology InitiativeRecommended book: Prediction Machines by Ajay AgrawalPinar's favourite AI tool: Superhuman – an AI-powered email assistantInfo on the EU AI Act Subscribe to Don't Stop Us Now – AI Edition wherever you get your podcastsShare this episode with a friend or colleague who needs to upskill for the AI era Hosted on Acast. See acast.com/privacy for more information.

Episode 127: Prediction Machines, Bigfoot & a Hip Campus discusses the brain, the mind, memory and perception and a bunch of things that have to do with our noggins. Oh, and some Emily Dickinson in there, of course. Bill and Shaun are joined by Bill's great-nephew Evan, who is very good at cutting through the nonsense. Brain jokes and sketchy knowledge of a variety of things ensue. NOTE: JW Ocker is the author of The United States of Cryptids, mentioned in the podcast.

The Economics of AI: Prediction Machines and Their Impact with Ajay Agrawal by Technology Policy Institute

In this engaging episode of the Partnering Leadership podcast, host Mahan Tavakoli engages in an insightful conversation with Paul Daugherty, the group chief executive of technology and chief technology officer at Accenture. During the episode, Paul Daugherty emphasizes the criticality of adopting a technology-focused mindset and embracing constant reinvention and agility in the face of evolving technologies. He highlights the importance of organizations becoming learning organizations equipped with empathetic listening capabilities to navigate the era of generative AI effectively. The conversation delves into the significance of responsible AI and data ethics within organizations utilizing AI. Paul Daugherty underscores the need for CEOs to prioritize the implementation of responsible AI, emphasizing its role in shaping the future of business and society. Additionally, the episode touches on the transformative impact of the metaverse on business operations, the integral role of data in AI, and the necessity of rescaling individuals displaced by automation. Finally, Paul Daugherty shares his predictions on the future impact of AI on organizations.Discover the untapped potential of AI. Find out why reskilling is crucial for individuals affected by automation.Uncover the origins of the digital revolution and the birth of artificial intelligence.Gain insights into the transformation of every business into a technology company, and learn why technological prowess is indispensable for successful digital transformation and total enterprise reinvention.Explore how AI can support learning within organizations.Understand the importance of placing technology at your company's core and adopting a mindset of total enterprise reinvention.Dive into the symbiotic relationship between humans and machines and unlock the potential and value that AI offers when they work together.Delve into responsible AI, establishing structured policies and tools to ensure ethical and unbiased outcomes while appropriately handling data.Discover the transformative impact of generative AI, affecting 40% of working hours across companies.Explore the metamorphosis of the metaverse and its profound influence on business operations.Embrace the concept of a Technology Quotient (TQ) as an essential addition to IQ and EQ in every company, and recognize the importance of training all employees in various technologies. Accenture Thought LeadershipAccenture Foresight App Accenture Technology Vision 2023 When Atoms Meet Bits  Connect with Paul DaughertyPaul Daugherty at Accenture Paul Daugherty on LinkedIn Also Referenced:Partnering Leadership Conversation with Ajay Agrawal on Prediction Machines & Power and PredictionConnect with Mahan Tavakoli: Mahan Tavakoli Website Mahan Tavakoli on LinkedIn Partnering Leadership Website

In this Partnering Leadership conversation, Mahan Tavakoli speaks with Professor Ajay Agrawal, the Geoffrey Taber Chair in Entrepreneurship and Innovation and Professor of Strategic Management at the University of Toronto's Rotman School of Management. Ajay Agrawal is also the founder of the Creative Destruction Lab (CDL), a not-for-profit program for early-stage, science-based companies, and coauthor of two outstanding books on Artificial Intelligence: Prediction Machines: The Simple Economics of Artificial Intelligence and Power and Prediction: The Disruptive Economics of Artificial Intelligence. In the conversation, Professor Agrawal shared the origin of his passion for studying the intersection of technology and economics and the increasing importance of artificial intelligence for organizations as a decision-making tool that brings down the cost of prediction. Ajay Agrawal then explained why this shift would significantly impact individuals, organizations, and industries as machines enable better predictions while humans focus on the judgment required for decision-making. Finally, Ajay Agrawal shared examples of the transformative impact of the reduction in the cost of prediction and how leaders can help guide their organizations through the significant changes ahead.Some highlights:- Three people that helped shape Ajay Agrawal's career path- Why looking at AI from an economic perspective clarifies its potential to transform organizations and industries- Ajay Agrawal on the role of predictions in artificial intelligence - The importance of human judgment in decision making- How AI decision-making will redefine roles in the workplace- The disruptive economics of artificial intelligence - How generative AI such as ChatGPT works and what causes mistakes and misstatements- Ajay Agrawal on the importance of upskilling professionals - How organizations can redesign their structures and processes to take into account the new predictive world- The impact of AI on systems-level change- How organizations can leverage AI for business success- Why we're on the brink of a set of transformations that none of us have seen in our lifetimes- How AI can help create a better futureConnect with Professor Ajay Agrawal:Ajay Agrawal website Ajay Agrawal at Rotman School of Management Ajay Agrawal on LinkedIn Prediction Machines: The Simple Economics of Artificial Intelligence on Amazon Power and Prediction: The Disruptive Economics of Artificial Intelligence on Amazon Connect with Mahan Tavakoli: Mahan Tavakoli Website Mahan Tavakoli on LinkedIn Partnering Leadership Website

Welcome to this week's episode of the Mixtape with Scott! This week we have an outstanding guest named Avi Goldfarb of the University of Toronto. Avi is a PhD economist who graduated from Northwestern in the early 2000s specializing in the economics of the internet. He is now at the University of Toronto where he is a professor in the marketing department as well as chief data scientist with a very interesting lab called the Creative Destruction lab that among other things specializes in the economics of artificial intelligence. He is the author of two very popular and probably both best selling books aimed at a general audience on the economics of artificial intelligence: Power and Prediction and Prediction Machines (both with Joshua Gans and Ajay Agrawal). Given the popularity of AI, as well as the recent turn of events with AI giant, OpenAI, I think there couldn't be a better time to to have him on the show. I loved this interview and accidentally went over, but Avi graciously hung in there with me. I hope you love it too. Don't forget to like, share and comment! Happy Thanksgiving to all!Scott's Substack is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. Get full access to Scott's Substack at causalinf.substack.com/subscribe

In the first of a special mini-series focused on AI in the workplace, guest hosts Pauline James and David Creelman ask "what exactly is AI all about and where is it heading?"Joining Pauline and David on the podcast is Avi Goldfarb, the Rotman Chair in Artificial Intelligence and Healthcare and a professor of marketing at the Rotman School of Management, University of Toronto. He is also Chief Data Scientist at the Creative Destruction Lab, a faculty affiliate at the Vector Institute and the Schwartz-Reisman Institute for Technology and Society, and a Research Associate at the National Bureau of Economic Research. Avi's research focuses on the opportunities and challenges of the digital economy. Along with Ajay Agrawal and Joshua Gans, Avi is the author of the bestselling books Prediction Machines and Power and Prediction.He has published academic articles in marketing, statistics, law, management, medicine, political science, refugee studies, physics, computing, and economics. Avi has testified before the U.S. Senate Judiciary Committee on related work in competition and privacy in digital advertising. His work has been referenced in White House reports, European Commission documents, the New York Times, the Economist, and elsewhere.Questions for Avi include:You have been studying AI for a long time; well before its advances garnered the attention of the general population. Is anything taking you by surprise with the current advances?You have talked about AI automating prediction in ways that we had only understood humans could do well/reasonably well previously. Can you explain this for our audience?You have an interesting (and hopeful) perspective that AI may become more of an equalizer across professions than past advances have been, can you tell us more about that?Can you provide your thoughts on how long it will be until we see broad sweeping changes in work and how it is organized?With your extensive work with entrepreneurs on the bleeding edge of new technology, what advice do you have for those on the other side of the equation: those who are making recommendations and purchasing tech for their organization. How should we balance not being left behind with appropriate diligence?We do our best to ensure editorial objectivity. The views andFeature Your Brand on the HRchat PodcastThe HRchat show has had 100,000s of downloads and is frequently listed as one of the most popular global podcasts for HR pros, Talent execs and leaders. It is ranked in the top ten in the world based on traffic, social media followers, domain authority & freshness. The podcast is also ranked as the Best Canadian HR Podcast by FeedSpot and one of the top 10% most popular shows by Listen Score. Want to share the story of how your business is helping to shape the world of work? We offer sponsored episodes, audio adverts, email campaigns, and a host of other options. Check out packages here and contact sales@hr-gazette.com. Follow us on LinkedIn Subscribe to our newsletter Check out our in-person events

Are you strategic enough to survive the digital future? In this Partnering Leadership episode, global strategy expert Michael Lenox, UVA Professor and author of Strategy in the Digital Age: Mastering Digital Transformation shares indispensable insights to help leaders craft agile strategies in the age of AI. Drawing from decades of research and firsthand experience steering his own business school's digital transformation, Mike Lenox reveals how to spot exponential change before it disrupts you, why strategy must drive technology (not vice versa), how to identify your unique competitive advantage, and the critical human skills machines will never replicate. If you're anxious about AI, automation, and competing in the digital age, don't miss Michael Lenox's thoughtful perspectives and advice to help any organization build a strategy for long-term resilience.Some Actionable Takeaways:Learn why starting digital transformation with IT upgrades can run you into an iceberg quicker.Gain insights on monitoring technology adoption S-curves to see disruptive exponential change coming.Find out what competitive moves historically resilient companies make and how you can do the same.Discover how to empower “digital champions” throughout your organization to drive strategic adoption.Listen to discover which human skills will remain uniquely valuable in an AI-powered world.Learn how to combine judgment with data to avoid over-indexing on an unknowable future.Connect with Michael LenoxMichael Lenox Website Michael Lenox on LinkedIn Strategy in the Digital Age: Mastering Digital Transformation on Amazon  ResourcesPartnering Leadership conversation with Ajay Agrawal on Prediction Machines and Power & Prediction Partnering Leadership conversation with Azeem Azhar on the Exponential Age Connect with Mahan Tavakoli: Mahan Tavakoli Website Mahan Tavakoli on LinkedIn Partnering Leadership Website

This episode of Partnering Leadership features Mahan Tavakoli being interviewed on AI and its potential impact by David Gardner on the Rule Breaker Investing podcast.  In the conversation, David and Mahan talk about the growing influence of artificial intelligence; they explore where we are on the AI exponential growth curve, how organizations can leverage AI strategically and operationally, and share predictions for AI's transformative impact and how individuals and organizations can take advantage of the opportunities ahead. Some of The Insights You will Gain from This Episode:Hear Mahan's answer to the question he has asked every one of his 250+ podcast guests (upbringing and its impact)Learn prompting strategies to unlock AI's true potential for your organizationFind out how to leverage AI to democratize information understanding, not just accessUse AI to future-proof your team through constant learning and skill development How AI could replace the web and change how you distribute informationLearn how to use AI to stress-test ideas and strengthen argumentsHear about resources to start experimenting with AI systems Recommended Resources:Partnering Leadership Conversation with Ajay Agrawal, coauthor of Prediction Machines and Power & PredictionPartnering Leadership Conversation with Paul Daugherty, coauthor of Human + Machine and Radically HumanPartnering Leadership Conversation with Azeem Azhar, author of The Exponential AgeRule Breaker Investing Podcast Connect with Mahan Tavakoli: Mahan Tavakoli Website Mahan Tavakoli on LinkedIn Partnering Leadership Website

When Joshua Gans and his co-authors released their book Prediction Machines in 2018, they were writing about a topic that seemed quite niche. At this time, machine learning was just starting out. In the last year, the speed at which artificial intelligence has advanced has surprised almost everyone.In this conversation, we hear how the analytical framework that he and his colleagues developed helps to sort through the hype. He argues artificial intelligence is best thought of as a prediction machine. You'll hear why he's optimistic that artificial intelligence will be able to help people remove some of the drudgery from some jobs, but at this time, doesn't seem likely to take over full jobs. He'll share how understanding artificial intelligence as an advance in predictive statistics will help leaders assess how artificial intelligence may or may not be useful. About our guest:Joshua Gans is a Professor of Strategic Management and holder of the Jeffrey S. Skoll Chair of Technical Innovation and Entrepreneurship at the Rotman School of Management, the University of Toronto (with a cross-appointment in the Department of Economics). Joshua is also Chief Economist of the University of Toronto's Creative Destruction Lab. Prior to 2011, he was the foundation Professor of Management (Information Economics) at the Melbourne Business School, University of Melbourne and before that, he was at the School of Economics, University of New South Wales. At Rotman, he teaches MBA students entrepreneurial strategy. He has also co-authored (with Stephen King and Robin Stonecash) the Australasian edition of Greg Mankiw's Principles of Economics (published by Cengage), Core Economics for Managers (Cengage), Finishing the Job (MUP), Parentonomics (New South/MIT Press) and Information Wants to be Shared (Harvard Business Review Press) and The Disruption Dilemma (MIT Press, 2016);

In this engaging episode of the Partnering Leadership podcast, host Mahan Tavakoli engages in an insightful conversation with Paul Daugherty, the group chief executive of technology and chief technology officer at Accenture. During the episode, Paul Daugherty emphasizes the criticality of adopting a technology-focused mindset and embracing constant reinvention and agility in the face of evolving technologies. He highlights the importance of organizations becoming learning organizations equipped with empathetic listening capabilities to navigate the era of generative AI effectively. The conversation delves into the significance of responsible AI and data ethics within organizations utilizing AI. Paul Daugherty underscores the need for CEOs to prioritize the implementation of responsible AI, emphasizing its role in shaping the future of business and society. Additionally, the episode touches on the transformative impact of the metaverse on business operations, the integral role of data in AI, and the necessity of rescaling individuals displaced by automation. Finally, Paul Daugherty shares his predictions on the future impact of AI on organizations.Discover the untapped potential of AI. Find out why reskilling is crucial for individuals affected by automation.Uncover the origins of the digital revolution and the birth of artificial intelligence.Gain insights into the transformation of every business into a technology company, and learn why technological prowess is indispensable for successful digital transformation and total enterprise reinvention.Explore how AI can support learning within organizations.Understand the importance of placing technology at your company's core and adopting a mindset of total enterprise reinvention.Dive into the symbiotic relationship between humans and machines and unlock the potential and value that AI offers when they work together.Delve into responsible AI, establishing structured policies and tools to ensure ethical and unbiased outcomes while appropriately handling data.Discover the transformative impact of generative AI, affecting 40% of working hours across companies.Explore the metamorphosis of the metaverse and its profound influence on business operations.Embrace the concept of a Technology Quotient (TQ) as an essential addition to IQ and EQ in every company, and recognize the importance of training all employees in various technologies.Accenture Thought LeadershipAccenture Foresight App Accenture Technology Vision 2023 When Atoms Meet Bits Connect with Paul DaughertyPaul Daugherty at Accenture Paul Daugherty on LinkedInAlso Referenced:Partnering Leadership Conversation with Ajay Agrawal on Prediction Machines & Power and PredictionConnect with Mahan Tavakoli: Mahan Tavakoli Website Mahan Tavakoli on LinkedIn Partnering Leadership Website

In this episode, Xavier Bonilla has a dialogue with Andy Clark about prediction processing, embodiment, and reality. They discuss the predictive processing model, Bayesian brain, and the role of human growth and development for the brain. They question what is reality, Friston's Free Energy Principle, controlled hallucinations, and computational psychiatry. They also talk about reward vs. salience, prediction error, body budget, consciousness, the extended mind, and many other topics.Andy Clark is a Philosopher and Professor of Cognitive Philosophy at the University of Sussex. His main research interests are embodied cognition, computational neuroscience, and artificial intelligence. He is the author of numerous books including his most recent book, The Experience Machine. You can find his work here.Twitter: @cogsandy This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit convergingdialogues.substack.com

My guest today is Avi Goldfarb. Avi is a Professor at the University of Toronto's Rotman School of Management, the Rotman Chair in Artificial Intelligence and Healthcare, as well as the co-author of two bestselling books on AI and its economic impact. His most recent book, Power and Prediction, is probably the best piece of content I have read in explaining how AI may reshape business models, systems, and products. We recorded this before GPT-4's release last week which, if anything, makes Avi's ideas on AI's impact all the more poignant. Please enjoy my conversation with Avi Goldfarb.   For the full show notes, transcript, and links to mentioned content, check out the episode page here.    -----   This episode is brought to you by Tegus. Tegus is the modern research platform for leading investors. I'm a longtime user and advocate of Tegus, a company that I've been so consistently impressed with that last fall my firm, Positive Sum, invested $20M to support Tegus' mission to expand its product ecosystem. Whether it's quantitative analysis, company disclosures, management presentations, earnings calls - Tegus has tools for every step of your investment research. They even have over 4000 fully driveable financial models. Tegus' maniacal focus on quality, as well as its depth, breadth and recency of content makes it the one-stop, end-to-end research platform for investors. Move faster, gather deep research to build conviction and surface high-quality, alpha-driving insights to find your differentiated edge with Tegus. As a listener, you can take the Tegus platform for a free test drive by visiting tegus.co/patrick.   -----   Invest Like the Best is a property of Colossus, LLC. For more episodes of Invest Like the Best, visit joincolossus.com/episodes.    Past guests include Tobi Lutke, Kevin Systrom, Mike Krieger, John Collison, Kat Cole, Marc Andreessen, Matthew Ball, Bill Gurley, Anu Hariharan, Ben Thompson, and many more.   Stay up to date on all our podcasts by signing up to Colossus Weekly, our quick dive every Sunday highlighting the top business and investing concepts from our podcasts and the best of what we read that week. Sign up here.   Follow us on Twitter: @patrick_oshag | @JoinColossus   Show Notes (00:03:15) - [First question] - His initial reaction to chat GPT when it first launched  (00:07:08) - Prediction Machines; The impact price has on how much something is used by humans (00:11:07) - The shift from steam powered factories to electric ones and the transition between the two in regards to systems and application solutions; Power and Prediction (00:17:06) - Midpoints between a point solution and a systems solution and applications that are being built in the middle of them (00:19:10) - What application, system, and point solutions feel like today in the world of AI (00:27:03) - The transition from a world governed by rules to one by decisions   (00:30:58) - How the power of prediction moves us from a binary to a decimal framework (00:34:48) - Ways power disruption will occur as we navigate the emerging AI frontier (00:44:33) - Other functions like personalization that entrepreneurs should think about putting into their products and features (00:47:18) - How we should be thinking about the generation of information and data  (00:51:32) - A future where technology either desimates or empowers specific industries (00:54:16) - What he's most excited and worried about given the emerging frontier of AI  (00:55:41) - The kindest thing anyone has ever done for him 

Disruption resulting from the proliferation of AI is coming. The authors of the bestselling Prediction Machines describe what you can do to prepare. Banking and finance, pharmaceuticals, automotive, medical technology, retail. Artificial intelligence (AI) has made its way into many industries around the world. But the truth is, it has just begun its odyssey toward cheaper, better, and faster predictions to drive strategic business decisions--powering and accelerating business. When prediction is taken to the max, industries transform. The disruption that comes with such transformation is yet to be felt--but it is coming. How do businesses prepare?  In Prediction Machines, eminent economists Ajay Agrawal, Joshua Gans, and Avi Goldfarb explained the simple yet game-changing economics of AI. Now, in Power and Prediction: The Disruptive Economics of Artificial Intelligence (HBR Press, 2022), they go further to reveal AI as a prediction technology directly impacting decision-making and to teach businesses how to identify disruptive opportunities and threats resulting from AI. Their exhaustive study of new developments in artificial intelligence and the past history of how technologies have disrupted industries highlights the striking phase we are now in: after witnessing the power of this new technology and before its widespread adoption--what they call "the Between Times." While there continue to be important opportunities for businesses, there are also threats of disruption. As prediction machines improve, old ways of doing things will be upended. Also, the process by which AI filters into the many systems involved in application is very uneven. That process will have winners and losers. How can businesses leverage, or protect, their positions? Filled with illuminating insights, rich examples, and practical advice, Power and Prediction is the must-read guide for any business leader or policy maker on how to make the coming AI disruptions work for you rather than against you. Interviewee Avi Goldfarb is the Rotman Chair in Artificial Intelligence and Healthcare and a professor of marketing at the Rotman School of Management, University of Toronto. Avi is also Chief Data Scientist at the Creative Destruction Lab and the CDL Rapid Screening Consortium, a faculty affiliate at the Vector Institute and the Schwartz-Reisman Institute for Technology and Society, and a Research Associate at the National Bureau of Economic Research. Avi's research focuses on the opportunities and challenges of the digital economy. He has published academic articles in marketing, statistics, law, management, medicine, political science, refugee studies, physics, computing, and economics. Avi is a former Senior Editor at Marketing Science. His work on online advertising won the INFORMS Society of Marketing Science Long Term Impact Award. He testified before the U.S. Senate Judiciary Committee on competition and privacy in digital advertising. His work has been referenced in White House reports, European Commission documents, the New York Times, the Economist, and elsewhere. Peter Lorentzen is economics professor at the University of San Francisco. He heads USF's Applied Economics Master's program, which focuses on the digital economy. His research is mainly on China's political economy. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/new-books-network

Disruption resulting from the proliferation of AI is coming. The authors of the bestselling Prediction Machines describe what you can do to prepare. Banking and finance, pharmaceuticals, automotive, medical technology, retail. Artificial intelligence (AI) has made its way into many industries around the world. But the truth is, it has just begun its odyssey toward cheaper, better, and faster predictions to drive strategic business decisions--powering and accelerating business. When prediction is taken to the max, industries transform. The disruption that comes with such transformation is yet to be felt--but it is coming. How do businesses prepare?  In Prediction Machines, eminent economists Ajay Agrawal, Joshua Gans, and Avi Goldfarb explained the simple yet game-changing economics of AI. Now, in Power and Prediction: The Disruptive Economics of Artificial Intelligence (HBR Press, 2022), they go further to reveal AI as a prediction technology directly impacting decision-making and to teach businesses how to identify disruptive opportunities and threats resulting from AI. Their exhaustive study of new developments in artificial intelligence and the past history of how technologies have disrupted industries highlights the striking phase we are now in: after witnessing the power of this new technology and before its widespread adoption--what they call "the Between Times." While there continue to be important opportunities for businesses, there are also threats of disruption. As prediction machines improve, old ways of doing things will be upended. Also, the process by which AI filters into the many systems involved in application is very uneven. That process will have winners and losers. How can businesses leverage, or protect, their positions? Filled with illuminating insights, rich examples, and practical advice, Power and Prediction is the must-read guide for any business leader or policy maker on how to make the coming AI disruptions work for you rather than against you. Interviewee Avi Goldfarb is the Rotman Chair in Artificial Intelligence and Healthcare and a professor of marketing at the Rotman School of Management, University of Toronto. Avi is also Chief Data Scientist at the Creative Destruction Lab and the CDL Rapid Screening Consortium, a faculty affiliate at the Vector Institute and the Schwartz-Reisman Institute for Technology and Society, and a Research Associate at the National Bureau of Economic Research. Avi's research focuses on the opportunities and challenges of the digital economy. He has published academic articles in marketing, statistics, law, management, medicine, political science, refugee studies, physics, computing, and economics. Avi is a former Senior Editor at Marketing Science. His work on online advertising won the INFORMS Society of Marketing Science Long Term Impact Award. He testified before the U.S. Senate Judiciary Committee on competition and privacy in digital advertising. His work has been referenced in White House reports, European Commission documents, the New York Times, the Economist, and elsewhere. Peter Lorentzen is economics professor at the University of San Francisco. He heads USF's Applied Economics Master's program, which focuses on the digital economy. His research is mainly on China's political economy. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/medicine

Disruption resulting from the proliferation of AI is coming. The authors of the bestselling Prediction Machines describe what you can do to prepare. Banking and finance, pharmaceuticals, automotive, medical technology, retail. Artificial intelligence (AI) has made its way into many industries around the world. But the truth is, it has just begun its odyssey toward cheaper, better, and faster predictions to drive strategic business decisions--powering and accelerating business. When prediction is taken to the max, industries transform. The disruption that comes with such transformation is yet to be felt--but it is coming. How do businesses prepare?  In Prediction Machines, eminent economists Ajay Agrawal, Joshua Gans, and Avi Goldfarb explained the simple yet game-changing economics of AI. Now, in Power and Prediction: The Disruptive Economics of Artificial Intelligence (HBR Press, 2022), they go further to reveal AI as a prediction technology directly impacting decision-making and to teach businesses how to identify disruptive opportunities and threats resulting from AI. Their exhaustive study of new developments in artificial intelligence and the past history of how technologies have disrupted industries highlights the striking phase we are now in: after witnessing the power of this new technology and before its widespread adoption--what they call "the Between Times." While there continue to be important opportunities for businesses, there are also threats of disruption. As prediction machines improve, old ways of doing things will be upended. Also, the process by which AI filters into the many systems involved in application is very uneven. That process will have winners and losers. How can businesses leverage, or protect, their positions? Filled with illuminating insights, rich examples, and practical advice, Power and Prediction is the must-read guide for any business leader or policy maker on how to make the coming AI disruptions work for you rather than against you. Interviewee Avi Goldfarb is the Rotman Chair in Artificial Intelligence and Healthcare and a professor of marketing at the Rotman School of Management, University of Toronto. Avi is also Chief Data Scientist at the Creative Destruction Lab and the CDL Rapid Screening Consortium, a faculty affiliate at the Vector Institute and the Schwartz-Reisman Institute for Technology and Society, and a Research Associate at the National Bureau of Economic Research. Avi's research focuses on the opportunities and challenges of the digital economy. He has published academic articles in marketing, statistics, law, management, medicine, political science, refugee studies, physics, computing, and economics. Avi is a former Senior Editor at Marketing Science. His work on online advertising won the INFORMS Society of Marketing Science Long Term Impact Award. He testified before the U.S. Senate Judiciary Committee on competition and privacy in digital advertising. His work has been referenced in White House reports, European Commission documents, the New York Times, the Economist, and elsewhere. Peter Lorentzen is economics professor at the University of San Francisco. He heads USF's Applied Economics Master's program, which focuses on the digital economy. His research is mainly on China's political economy. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/public-policy

Disruption resulting from the proliferation of AI is coming. The authors of the bestselling Prediction Machines describe what you can do to prepare. Banking and finance, pharmaceuticals, automotive, medical technology, retail. Artificial intelligence (AI) has made its way into many industries around the world. But the truth is, it has just begun its odyssey toward cheaper, better, and faster predictions to drive strategic business decisions--powering and accelerating business. When prediction is taken to the max, industries transform. The disruption that comes with such transformation is yet to be felt--but it is coming. How do businesses prepare?  In Prediction Machines, eminent economists Ajay Agrawal, Joshua Gans, and Avi Goldfarb explained the simple yet game-changing economics of AI. Now, in Power and Prediction: The Disruptive Economics of Artificial Intelligence (HBR Press, 2022), they go further to reveal AI as a prediction technology directly impacting decision-making and to teach businesses how to identify disruptive opportunities and threats resulting from AI. Their exhaustive study of new developments in artificial intelligence and the past history of how technologies have disrupted industries highlights the striking phase we are now in: after witnessing the power of this new technology and before its widespread adoption--what they call "the Between Times." While there continue to be important opportunities for businesses, there are also threats of disruption. As prediction machines improve, old ways of doing things will be upended. Also, the process by which AI filters into the many systems involved in application is very uneven. That process will have winners and losers. How can businesses leverage, or protect, their positions? Filled with illuminating insights, rich examples, and practical advice, Power and Prediction is the must-read guide for any business leader or policy maker on how to make the coming AI disruptions work for you rather than against you. Interviewee Avi Goldfarb is the Rotman Chair in Artificial Intelligence and Healthcare and a professor of marketing at the Rotman School of Management, University of Toronto. Avi is also Chief Data Scientist at the Creative Destruction Lab and the CDL Rapid Screening Consortium, a faculty affiliate at the Vector Institute and the Schwartz-Reisman Institute for Technology and Society, and a Research Associate at the National Bureau of Economic Research. Avi's research focuses on the opportunities and challenges of the digital economy. He has published academic articles in marketing, statistics, law, management, medicine, political science, refugee studies, physics, computing, and economics. Avi is a former Senior Editor at Marketing Science. His work on online advertising won the INFORMS Society of Marketing Science Long Term Impact Award. He testified before the U.S. Senate Judiciary Committee on competition and privacy in digital advertising. His work has been referenced in White House reports, European Commission documents, the New York Times, the Economist, and elsewhere. Peter Lorentzen is economics professor at the University of San Francisco. He heads USF's Applied Economics Master's program, which focuses on the digital economy. His research is mainly on China's political economy. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/economics

Disruption resulting from the proliferation of AI is coming. The authors of the bestselling Prediction Machines describe what you can do to prepare. Banking and finance, pharmaceuticals, automotive, medical technology, retail. Artificial intelligence (AI) has made its way into many industries around the world. But the truth is, it has just begun its odyssey toward cheaper, better, and faster predictions to drive strategic business decisions--powering and accelerating business. When prediction is taken to the max, industries transform. The disruption that comes with such transformation is yet to be felt--but it is coming. How do businesses prepare?  In Prediction Machines, eminent economists Ajay Agrawal, Joshua Gans, and Avi Goldfarb explained the simple yet game-changing economics of AI. Now, in Power and Prediction: The Disruptive Economics of Artificial Intelligence (HBR Press, 2022), they go further to reveal AI as a prediction technology directly impacting decision-making and to teach businesses how to identify disruptive opportunities and threats resulting from AI. Their exhaustive study of new developments in artificial intelligence and the past history of how technologies have disrupted industries highlights the striking phase we are now in: after witnessing the power of this new technology and before its widespread adoption--what they call "the Between Times." While there continue to be important opportunities for businesses, there are also threats of disruption. As prediction machines improve, old ways of doing things will be upended. Also, the process by which AI filters into the many systems involved in application is very uneven. That process will have winners and losers. How can businesses leverage, or protect, their positions? Filled with illuminating insights, rich examples, and practical advice, Power and Prediction is the must-read guide for any business leader or policy maker on how to make the coming AI disruptions work for you rather than against you. Interviewee Avi Goldfarb is the Rotman Chair in Artificial Intelligence and Healthcare and a professor of marketing at the Rotman School of Management, University of Toronto. Avi is also Chief Data Scientist at the Creative Destruction Lab and the CDL Rapid Screening Consortium, a faculty affiliate at the Vector Institute and the Schwartz-Reisman Institute for Technology and Society, and a Research Associate at the National Bureau of Economic Research. Avi's research focuses on the opportunities and challenges of the digital economy. He has published academic articles in marketing, statistics, law, management, medicine, political science, refugee studies, physics, computing, and economics. Avi is a former Senior Editor at Marketing Science. His work on online advertising won the INFORMS Society of Marketing Science Long Term Impact Award. He testified before the U.S. Senate Judiciary Committee on competition and privacy in digital advertising. His work has been referenced in White House reports, European Commission documents, the New York Times, the Economist, and elsewhere. Peter Lorentzen is economics professor at the University of San Francisco. He heads USF's Applied Economics Master's program, which focuses on the digital economy. His research is mainly on China's political economy. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/science-technology-and-society

Disruption resulting from the proliferation of AI is coming. The authors of the bestselling Prediction Machines describe what you can do to prepare. Banking and finance, pharmaceuticals, automotive, medical technology, retail. Artificial intelligence (AI) has made its way into many industries around the world. But the truth is, it has just begun its odyssey toward cheaper, better, and faster predictions to drive strategic business decisions--powering and accelerating business. When prediction is taken to the max, industries transform. The disruption that comes with such transformation is yet to be felt--but it is coming. How do businesses prepare?  In Prediction Machines, eminent economists Ajay Agrawal, Joshua Gans, and Avi Goldfarb explained the simple yet game-changing economics of AI. Now, in Power and Prediction: The Disruptive Economics of Artificial Intelligence (HBR Press, 2022), they go further to reveal AI as a prediction technology directly impacting decision-making and to teach businesses how to identify disruptive opportunities and threats resulting from AI. Their exhaustive study of new developments in artificial intelligence and the past history of how technologies have disrupted industries highlights the striking phase we are now in: after witnessing the power of this new technology and before its widespread adoption--what they call "the Between Times." While there continue to be important opportunities for businesses, there are also threats of disruption. As prediction machines improve, old ways of doing things will be upended. Also, the process by which AI filters into the many systems involved in application is very uneven. That process will have winners and losers. How can businesses leverage, or protect, their positions? Filled with illuminating insights, rich examples, and practical advice, Power and Prediction is the must-read guide for any business leader or policy maker on how to make the coming AI disruptions work for you rather than against you. Interviewee Avi Goldfarb is the Rotman Chair in Artificial Intelligence and Healthcare and a professor of marketing at the Rotman School of Management, University of Toronto. Avi is also Chief Data Scientist at the Creative Destruction Lab and the CDL Rapid Screening Consortium, a faculty affiliate at the Vector Institute and the Schwartz-Reisman Institute for Technology and Society, and a Research Associate at the National Bureau of Economic Research. Avi's research focuses on the opportunities and challenges of the digital economy. He has published academic articles in marketing, statistics, law, management, medicine, political science, refugee studies, physics, computing, and economics. Avi is a former Senior Editor at Marketing Science. His work on online advertising won the INFORMS Society of Marketing Science Long Term Impact Award. He testified before the U.S. Senate Judiciary Committee on competition and privacy in digital advertising. His work has been referenced in White House reports, European Commission documents, the New York Times, the Economist, and elsewhere. Peter Lorentzen is economics professor at the University of San Francisco. He heads USF's Applied Economics Master's program, which focuses on the digital economy. His research is mainly on China's political economy. Learn more about your ad choices. Visit megaphone.fm/adchoices

Between ChatGPT generating limericks in the style of George Costanza and Lensa turning your profile picture into a cartoon, AI seems to have finally broken into mainstream awareness in the past few months. But what's going on below the surface? How did the technology advance to this point? Who has been funding its development, and how does it actually work? We dig into all of those issues (and other very basic questions we had about the technology) in this conversation with Ryan Khurana, Chief of Staff at WOMBO [www.w.ai], a Generative AI for entertainment company whose app Dream [www.dream.ai] won the Play Store App of the Year in 2022. ----- Book recommendations: Prediction Machines by Ajay Agrawal, Joshua Gans, Avi Goldfarb Power and Prediction by Ajay Agrawal, Joshua Gans, Avi Goldfarb Architects of Intelligence by Martin Ford Deep Learning by Ian Goodfellow, Yoshua Bengio, Aaron Courville ----- Links: More episodes of Free Lunch by The Peak: https://readthepeak.com/shows/free-lunch Follow Taylor on Twitter: @taylorscollon Follow Sarah on Twitter: @sarahbartnicka Subscribe to The Peak's daily business newsletter: https://readthepeak.com/b/the-peak/subscribe

Welcome to episode #859 of Six Pixels of Separation - The ThinkersOne Podcast. Here it is: Six Pixels of Separation - The ThinkersOne Podcast - Episode #859. How does artificial intelligence affect the structure and dynamics of the global economy? What are the potential benefits and risks associated with artificial intelligence on the future of humanity? Joshua Gans is the co-author of the recently published book, Power and Prediction - The Disruptive Economics of Artificial Intelligence. He is also widely known as the co-author of Prediction Machines and over ten other books at the intersection of technology, disruption and economics. Joshua is a Professor of Strategic Management and holder of the Jeffrey S. Skoll Chair of Technical Innovation and Entrepreneurship at the Rotman School of Management at the University of Toronto. He is also the Chief Economist at the Creative Destruction Lab and a Research Associate at the National Bureau of Economic Research. He is a leading expert in the field of economics, particularly in the areas of innovation, technology, and entrepreneurship. Along with book writing, he is a regular contributor to The New York Times, The Atlantic, and The Wall Street Journal. He has also done extensive work on entrepreneurship, the digital economy, and the management of intellectual property. Joshua is a recipient of the John Kenneth Galbraith Prize for his work on the economics of the digital economy and was recently named one of the world's top 25 most influential economists by Bloomberg. Enjoy the conversation... Running time: 47:06. Hello from beautiful Montreal. Subscribe over at Apple Podcasts. Please visit and leave comments on the blog - Six Pixels of Separation. Feel free to connect to me directly on Facebook here: Mitch Joel on Facebook. Check out ThinkersOne. or you can connect on LinkedIn. ...or on Twitter. Here is my conversation with Joshua Gans. Power and Prediction - The Disruptive Economics of Artificial Intelligence. Prediction Machines. Rotman School of Management. Creative Destruction Lab. Follow Joshua on Twitter. Follow Joshua on LinkedIn. This week's music: David Usher 'St. Lawrence River'.

What does "AI" really look like in businesses today? What is a Prediction Machine, and what is AI Economics? This week, we chat with Dr. Avi Goldfarb, author of Prediction Machines and Power and Prediction: The Disruptive Economics of Artificial Intelligence. Through a sequence of fascinating stories, Avi helps us demystify the stigma around artificial intelligence, and he helps us understand how AI has transformed and can transform business and industry the way electricity transformed steam-powered factories. Avi is the Rotman Chair in Artificial Intelligence and Healthcare and a professor of marketing at the Rotman School of Management, University of Toronto, Chief Data Scientist at the Creative Destruction Lab and the CDL Rapid Screening Consortium.

Joshua Gans is a Professor of Strategic Management and the holder of the Jeffrey S. Skoll Chair of Technical Innovation and Entrepreneurship at the Rotman School of Management at the University of Toronto. He is also the Chief Economist of the University's Creative Destruction Lab. In 2018, together with Ajay Agrawal and Avi Goldfarb, he published Prediction Machines, an exploration of how basic tools from economics provide clarity about the AI revolution and a basis for action by leaders. The trio's latest book, “Power and Prediction: The Disruptive Economics of Artificial Intelligence” explains the economics of A.I. through the lens of decision systems. In conversation with Martin Reeves, Chairman of BCG Henderson Institute, Joshua discusses how the transformational potential of A.I. is only unlocked if decision systems are reconsidered holistically, mirroring the pattern observed in previous technological revolutions like the application of steam power, electricity, or digital communication. *** About the BCG Henderson Institute The BCG Henderson Institute is the Boston Consulting Group's think tank, dedicated to exploring and developing valuable new insights from business, technology, economics, and science by embracing the powerful technology of ideas. The Institute engages leaders in provocative discussion and experimentation to expand the boundaries of business theory and practice and to translate innovative ideas from within and beyond business. For more ideas and inspiration, sign up to receive BHI INSIGHTS, our monthly newsletter, and follow us on LinkedIn and Twitter.

In the seventh episode of ReBootHealth, I speak with Avi Goldfarb. Avi is Professor of Marketing and the Rotman Chair of Artificial Intelligence and Healthcare at the University of Toronto. He is also co-author of the Book Prediction Machines: The Simple Economics of Artificial Intelligence. This interview with Avi was fascinating as he unpacked AI and healthcare through an economic lens. The content in this episode won't help you build a better AI but it will do one better—help set the context for the profound impact of AI on the business and structure of healthcare. We talked about AI's impact on the anatomy of a decision, the pace of adoption in healthcare, its potential role in clinical medicine and design implications, and a utopian/dystopian view of the future of health. I highly recommend Avi's book (linked below) for a novel way to view AI without all the hype and buzz. I must admit that this episode was quite enjoyable to research as it opened a whole new perspective for me. I promise it will do the same for you. As always, I hope you find the episode valuable. Prediction Machines: The Simple Economics of Artificial Intelligence Avi Goldfarb's publications Please write a review on Apple Podcast. For other episodes or to learn more you can visit us at ReBootHealth or follow us on Twitter: @Reboothealth1 Episode recorded on August 13, 2021. 05:00—AI and its role in decision-making and healthcare. 15:04—Estimating the pace of change for AI in medicine. 19:20—How to capture value with AI. 27:10—Applying lessons of the past and present to AI adoption. 39:40—Decision support versus automation. 44:15—How to design technology for the task. 47:31—Will 'ship-to-shop' apply to healthcare? 54:27—Canada's status in AI/healthcare.

How can artificial intelligence benefit your business? Ajay Agrawal, Author and Geoffrey Taber Chair of Rotman talks about A.I. and how it generates predictions. In this episode, Ajay and Greg unpack the book Prediction Machines: The Simple Economics Of Artificial Intelligence.The episode focused on how A.I. predictions require enough data. As more data becomes available, it becomes easier to find critical relationships, leading to better forecasts. In the past, data analytics was limited to the amount of data that could be analyzed for correlations. Today, people can tailor data to their specific needs, whether it is for banks, streaming services, or e-commerce. Ajay emphasized that data gathered is not limited to be used to forecast, but it can also be used to address situation-specific problems. Make sure to tune in until the end to listen to tips on how A.I. and its predictors can help businesses in product design and service development. Finally, Ajay talks about how these predictors are helping jobs evolve and possible applications in the academe, in creating a curriculum that'll help students succeed.Episode Quotes:On the Economics of A.I.:"So the main insight here -- after we started probing into a number of different applications and what various techniques that were gaining popularity in machine learning -- was recognizing that all of this was effectively prediction. [...] What people didn't realize was how deeper a phenomenon prediction was. [...] When people started to realize, wait a minute, image recognition is a prediction problem and it's not just a neat party trick. When people can develop machines that can label images and pictures, then effectively machines can see. And when machines can see that means things like cars can drive themselves. [...] And then back to economics 101, when the cost of prediction falls we use more of it. And then that started us down the chain of, okay, if we're going to use more prediction, how are we going to use it? And so, that became the insight that then led to a number of the key points in the book.Does A.I. pose a real threat to jobs?"And so as AI drops the cost of prediction, as you say, we do more prediction. And then because we do more prediction, now there's more demand for the complement to prediction. The other stuff. [...] And so we do more of everything where there's more prediction. And everything that we do more of, there's more demand for the complements. And those complements drive more jobs. And so that's the part that I feel the popular press keeps missing."On the possibility that A.I. could replace human work:"The example that is very often trotted out are horses. There used to be all these horses that have this job. And then when automobiles came along the horses kind of disappeared. And there was an untimely demise for many horses that used to be in some sense employed. And so there's a fear, are we going to be the horses? And I think the key difference between the horses and the bank tellers is that humans have general-purpose capabilities. So in other words, horses were able to do, effectively, one thing - which was pull the cart. Whereas humans have the capacity to do multiple different things."Show Links:Guest ProfileAjay Agrawal's Profile on RotmanAjay Agrawal on TwitterAjay Agrawal on LinkedInHis WorkThe Economics of Artificial Intelligence: An Agenda (National Bureau of Economic Research Conference Report)Prediction Machines: The Simple Economics of Artificial Intelligence 

In this episode I interview James Cham from Bloomberg Beta.  We discuss the book "The Man Who Lied to His Laptop" and the book "Prediction Machines" about the economics of AI.  We discuss how startups compete with big companies when it comes to AI and the data sets needed, and we have a spirited debate about whether or not AI is the new electricity.

Harikrishna Narayanan is the co-founder of a YC-backed stealth startup. He was previously a Principal Engineer at Yahoo, a Director in Workday's Machine Learning organization, and holds an M.S. from Georgia Tech. Every Thursday I send out the most useful things I've learned, curated specifically for the busy machine learning engineer. Sign up here: https://cyou.ai/newsletter (https://cyou.ai/newsletter) Follow Charlie on Twitter: https://twitter.com/CharlieYouAI (https://twitter.com/CharlieYouAI) Subscribe to ML Engineered: https://mlengineered.com/listen (https://mlengineered.com/listen) Comments? Questions? Submit them here: http://bit.ly/mle-survey (http://bit.ly/mle-survey) Take the Giving What We Can Pledge: https://www.notion.so/charlieyou/Content-Pipeline-af923f8b990646369a85a00a348a1e12 (https://www.givingwhatwecan.org/) Timestamps: 02:45 How Hari got started in computer science and machine learning 06:00 Making the transition from IC to manager 14:35 What it means to be an effective engineering manager 19:20 Differences in managing machine learning vs traditional software teams 24:30 The importance of explaining complicated topics simply 30:15 How he thinks about hiring for data science and machine learning 36:50 Mistakes Workday made as it adopted machine learning 41:50 Essential skills for machine learning engineers 54:05 Why the future of AI is augmentation, not automation 58:30 His experience so far with YC 01:02:00 Rapid fire questions Links: https://www.brainpickings.org/2014/01/29/carol-dweck-mindset/ (Growth Mindset) https://fs.blog/2012/04/feynman-technique/ (The Feynman Technique) https://www.radicalcandor.com/ (Radical Candor) https://www.trilliondollarcoach.com/ (Trillion Dollar Coach) https://thewisemangroup.com/books/multipliers/ (Multipliers) https://www.jimcollins.com/article_topics/articles/good-to-great.html#articletop (Good to Great) https://hbr.org/books/watkins (The First 90 Days) https://www.harpercollins.com/products/crossing-the-chasm-3rd-edition-geoffrey-a-moore?variant=32130444066850 (Crossing the Chasm) https://en.wikipedia.org/wiki/Zero_to_One (Zero to One) http://theleanstartup.com/ (The Lean Startup) https://hardthings.bhorowitz.com/ (The Hard Thing About Hard Things) https://www.ynharari.com/book/sapiens-2/ (Sapiens) https://www.penguinrandomhouse.com/books/20549/a-short-history-of-nearly-everything-special-illustrated-edition-by-bill-bryson/ (A Short History of Nearly Everything) https://numenta.com/resources/on-intelligence/ (On Intelligence) https://www.predictionmachines.ai/ (Prediction Machines) https://algorithmstoliveby.com/ (Algorithms to Live By) https://sdv.dev/ (The Synthetic Data Vault)

In Episode 3 we continue our mini-theme on Artificial Intelligence with award-winning economist and professor Joshua Gans, speaking about his book Prediction Machines: the simple economics of Artificial Intelligence, co-written with professors, Ajay Agrawal and Avi Goldfarb. This is an expansive career that features several books, numerous publications and awards. Aside from all the books and accolades, we think you'll find professor Gans, not only a great mind, but a gregarious one as well. This interview was conducted just before the COVID-19 pandemic gripped the world. On that note, you may want to check out professor Gans newest, short, but thoughtful and very timely book, Economics In the age of COVID-19 published by the MIT press, available on digital and audio. For more information on Josh or his books, visit https://www.joshuagans.com. He's also on Twitter @joshgans.

In this episode, our guest is Eugene Dubossarsky, who is the chief data scientist at AlphaZetta and co-founder at multiple data science companies in Australia. He is a managing partner of the Global Training Academy and he is teaching too. Eugene is dealing with machine learning since the 80s, so you can imagine he has a very strong opinion about different topics in this industry. We talked about random forests, neural nets, boosting strategies, the importance of understanding data and statistics. We couldn't skip talking about the effects of the current and upcoming crisis either. Eugene's LinkedIn: https://www.linkedin.com/in/eugene-dubossarsky-09208a1/ AlphaZetta: https://alphazetta.ai/ Reask Track cyclons: https://reask.earth/ The Prediction Machines book: https://www.predictionmachines.ai/ Hopfield network: https://en.wikipedia.org/wiki/Hopfield_network Bengio talk: https://slideslive.com/38922304/from-system-1-deep-learning-to-system-2-deep-learning Finnian Lattimore and Cheng Soon Ong Paper https://arxiv.org/pdf/1806.01488.pdf ---General Info--- About the host: Miklos Toth is a Machine Learning enthusiast who is also teaching Machine Learning and Deep Learning at international companies, working on various ML projects as an engineer. About the co-host: Levente Szabados is a Deep tech leader, consultant, and manager with a special interest in artificial intelligence, cognitive sciences, data science, and deep learning. He is teaching various ML courses at the Frankfurt School of Finance and Management. About the podcast: The podcast was created to serve the technical community with details of ML algorithms, use-cases. The episodes are recorded in Budapest, Hungary, Europe. Website of the podcast: http://machinelearningcafe.org/ Host's LinkedIn: https://www.linkedin.com/in/miklostoth/ Co-Host LinkedIn: https://www.linkedin.com/in/levente-szabados-76334728/ Write an email to the host: miklos@machinelearningcafe.org Equipment: On the host's side the show is recorded with Rode Procaster and with Roland Quad-Capture audio interface. ---Copyright Info--- Music is from https://filmmusic.io, intro first part is by Miklos Toth and some free garage band loops. :) intro second part: "Aces High" by Kevin MacLeod, outro "Acid Trumpet" by Kevin MacLeod (https://incompetech.com), License: CC BY (http://creativecommons.org/licenses/by/4.0/)

EP 508 Book Review Prediction Machines หนังสือเล่มนี้ที่ผมมา Review จะบอกเราว่า AI คืออะไร และจะเปลี่ยนชีวิตและธุรกิจไปในทิศทางไหน ลองฟังกันดูนะครับ

EP 508 Book Review Prediction Machines หนังสือเล่มนี้ที่ผมมา Review จะบอกเราว่า AI คืออะไร และจะเปลี่ยนชีวิตและธุรกิจไปในทิศทางไหน ลองฟังกันดูนะครับ

You may not be aware, but artificial intelligence (AI) has already established itself in our daily lives. From Amazon to Alexa, sophisticated algorithms affect much of what we do. The next ten years will see advancements in electronic decision-making, facial recognition, language translation, and voice-to-text. Are you willing to accept the cost in loss of privacy due to AI’s insatiable thirst for data for the benefit in added productivity? What will be the new careers in AI world? Abhijeet Chavan and IV Ashton walk us through some of the inner workings of AI, some expectations in areas like Natural Language Processing, and give us advice on how to prepare for the future of this technology. This is a fascinating episode for listeners interested in court technology, Natural Language Processing, algorithms, individual privacy, language translation, and emerging technologies. There is a link to a short segment of the book Prediction Machines by Ajay Agrawal, Joshua Gans, Avi Goldfarb, in the Show Notes section on our website. https://nacmnet.org/podcasts Leave a comment or question about the podcast at clapodcast@nacmnet.org.

Avi Goldfarb is the Rotman Chair in Artificial Intelligence and Healthcare and a Professor of Marketing at the Rotman School of Management, University of Toronto. He is also Chief Data Scientist at the Creative Destruction Lab, Senior Editor at Marketing Science, a Research Associate at the National Bureau of Economic Research, and President of Goldfarb Analytics Corporation. In his new book, “Prediction Machines,” Goldfarb explains how artificial intelligence (AI) will affect business, public policy, and society in terms that work for decision makers in virtually all fields. Perhaps his most important role is coming up this October in Boston, when he will be the featured speaker at the FP&A Luncheon at AFP 2019. Goldfarb recently joined us on the AFP Conversations podcast, and we discussed using AI to make predictions in all areas of life and business. AFP 2019, this October in Boston, is where treasury and finance professionals separate the hype from the reality. Visit www.afp2019.org/register to sign up and use discount code PODCASTAFP2019 at checkout to save $100.

Are you optimistic about our future with ARTIFICIAL INTELLIGENCE? Avi Goldfarb (professor and author of “Prediction Machines”) shares a brief history of AI, various AI applications that are being used in the marketplace, and specific reasons why we should be optimistic about our future with AI. SHOWNOTES Contents Key Learnings References & Links Andrea’s Commentary […] The post #15 (S2) ARTIFICIAL INTELLIGENCE: TALKING WITH SIRI & ALEXA with professor & author Avi Goldfarb appeared first on Talk About Talk.

In this episode, we speak with Joshua Gans who is a professor of strategic management and the chair in technical innovation and entrepreneurship at the Rotman School of Management at the University of Toronto.   Major Topics Include: The economics of technological innovation as it pertains to blockchain and artificial intelligence His work on the book Prediction Machines and the paper “Some Simple Economics of the Blockchain” How blockchain reduces the cost of verification and what this means for evaluating the potential of future blockchain uses and projects The Creative Destruction Lab’s blockchain stream and its growing network of tech startups The tradeoffs for startups between ICO fundraising and traditional venture capital Third party verification, regulation, security tokens vs. utility tokens, bitcoin mining, smart contracts, etc.  

How are we supposed to think about Machine Learning? How are businesses going to change? This week I interview Joshua Gans, Professor of Strategic Management at the Rotman School of Business at the University of Toronto and the Chief Economist at the University's Creative Destruction Lab. Joshua is the co-author, along with Ajay Agarwal and Avi Goldfarb, of Prediction Machines: The Simple Economics of Artificial Intelligence. Are you an actuary? Someone you know? Check out the Not Unprofessional Project, for the price of a CAS webinar you get unlimited access to content dedicated to Continuing Education Credits for Actuaries, especially Professionalism credits. CE On Your Commute! Subscribe to the Not Unreasonable Podcast in iTunes, stitcher, or by rss feed. Sign up for the mailing list at notunreasonable.com/signup. See older show notes at notunreasonable.com/podcast.

In episode 5 we talk to Joshua Gans, who is a Professor of Strategic Management and holder of the Chair of Technical Innovation and Entrepreneurship at the Rotman School of Management, University of Toronto. He is also the Chief Economist of the Creative Destruction Lab. Joshua has written various books ranging from general economics, the disruption dilemma to applying principals from economics to parenting. In today's episode, we talk about his latest book, "Prediction Machines: The Simple Economics of Artificial Intelligence", which explains what AI means for businesses, policy-makers, and society in general.

Special guest Joshua Gans, economist and co-author of, Prediction Machines. When AI is framed as cheap prediction, its extraordinary potential becomes clear: Prediction is at the heart of making decisions under uncertainty. Our businesses and personal lives are riddled with such decisions. Uncertainty constrains strategy. Better prediction creates opportunities for new business structures and strategies to compete.

Will AI machines destroy humanity as we know it? Actually, quite the contrary. AI matters to the everyday business owner more than they might know. There’s a lot to be learned in prediction technology and today’s guest shares advice on how you can use this knowledge to grow your marketing and sales potential.   Avi Goldfarb is the Ellison Professor of Marketing at the Rotman School of Management, University of Toronto. Avi is also Chief Data Scientist at the Creative Destruction Lab, Senior Editor at Marketing Science, and a Research Associate at the National Bureau of Economic Research. Avi is also the author of Prediction Machines, which he will be discussing on today’s show!   In 2012, there were only a couple of companies at the time that were calling themselves AI companies. However, that slowly grew and by 2015, Avi had seen a huge increase of at least 50 companies being created a year. Avi and his co-authors decided to investigate and research what this technology meant for our modern society.   The Mosaic web browser made the internet accessible to the general population, but it took us about a decade to figure out how to really commercialize it. Avi believes the same will hold true with AI. We are going to see businesses use AI tools in various ways to solve key problems.   Although AI will not improve the general intelligence of your company, prediction is still really, really valuable. Why? Because it cuts down on all the unknown variables in your decision-making process when you are faced with uncertainty. Through prediction, you can be much more confident (and you have the data to prove it) on what’s the correct direction to take your business in.   Interview Links: Avigoldfarb.com Creativedestructionlab.com   Resources: Scaling Up for Business Growth Workshops: Take the first step to mastering the Rockefeller Habits by attending one of our workshops. Scaling Up Website Gazelles Website Bill on YouTube  

Institute of Philosophy The Chandaria Lectures 2016 Lecture 1 - Prediction Machines Professor Andy Clark (University of Edinburgh) The Institute of Philosophy is delighted to announce that this year's Chandaria Lecture series will be given ...

Institute of Philosophy The Chandaria Lectures 2016 Lecture 1 - Prediction Machines Professor Andy Clark (University of Edinburgh) The Institute of Philosophy is delighted to announce that this year's Chandaria Lecture series will be given ...