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Monday, March 23, 2020

Linking Gamification and AI

Steve Omohundro talks some favorite topics of mine in a recent presentation, slides at the link.  Integration of gamification a favorite.  We used gamification as a means to find alternative 'expert crowdourcing' to explore alternative solutions to wicked problems.   In the supply chain space.  Makes mention of Bytedance, that I had not heard of, will take a look.

Talk: The AI Platform Business Revolution, Matchmaking Empathetic technology and AI Gamification.

On October 15, Steve Omohundro spoke at FXPAL (FX Palo Alto Laboratory) about “The AI Platform Business Revolution, Matchmaking, Empathetic Technology, and AI Gamification”:

Popular media is full of stories about self-driving cars, video deepfakes, and robot citizens. But this kind of popular artificial intelligence is having very little business impact. The actual impact of AI on business is in automating business processes and in creating the “AI Platform Business Revolution”. Platform companies create value by facilitating exchanges between two or more groups. AI is central to these businesses for matchmaking between producers and consumers, organizing massive data flows, eliminating malicious content, providing empathetic personalization, and generating engagement through gamification. The platform structure creates moats which generate outsized sustainable profits. This is why platform businesses are now dominating the world economy. The top five companies by market cap, half of the unicorn startups, and most of the biggest IPOs and acquisitions are platforms. For example, the platform startup Bytedance is now worth $75 billion based on three simple AI technologies.

In this talk we survey the current state of AI and show how it will generate massive business value in coming years. A recent McKinsey study estimates that AI will likely create over 70 trillion dollars of value by 2030. Every business must carefully choose its AI strategy now in order to thrive over coming decades. We discuss the limitations of today’s deep learning based systems and the “Software 2.0” infrastructure which has arisen to support it. We discuss the likely next steps in natural language, machine vision, machine learning, and robotic systems. We argue that the biggest impact will be created by systems which serve to engage, connect, and help individuals. There is an enormous opportunity to use this technology to create both social and business value.  .... '

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