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TechSurge: Deep Tech VC Podcast
Artificial intelligence is evolving at an unprecedented paceтАФwhat does that mean for the future of technology, venture capital, business, and even our understanding of ourselves? Award-winning journalist and writer Anil Ananthaswamy joins us for our latest episode to discuss his latest book Why Machines Learn: The Elegant Math Behind Modern AI . Anil helps us explore the journey and many breakthroughs that have propelled machine learning from simple perceptrons to the sophisticated algorithms shaping todayтАЩs AI revolution, powering GPT and other models. The discussion aims to demystify some of the underlying math that powers modern machine learning to help everyone grasp this technology impacting our lives, even if your last math class was in high school. Anil walks us through the power of scaling laws, the shift from training to inference optimization, and the debate among AIтАЩs pioneers about the road to AGIтАФshould we be concerned, or are we still missing key pieces of the puzzle? The conversation also delves into AIтАЩs philosophical implicationsтАФcould understanding how machines learn help us better understand ourselves? And what challenges remain before AI systems can truly operate with agency? If you enjoy this episode, please subscribe and leave us a review on your favorite podcast platform. Sign up for our newsletter at techsurgepodcast.com for exclusive insights and updates on upcoming TechSurge Live Summits. Links: Read Why Machines Learn, AnilтАЩs latest book on the math behind AI https://www.amazon.com/Why-Machines-Learn-Elegant-Behind/dp/0593185749 Learn more about Anil AnanthaswamyтАЩs work and writing https://anilananthaswamy.com/ Watch Anil AnanthaswamyтАЩs TED Talk on AI and intelligence https://www.ted.com/speakers/anil_ananthaswamy Discover the MIT Knight Science Journalism Fellowship that shaped AnilтАЩs AI research https://ksj.mit.edu/ Understand the Perceptron, the foundation of neural networks https://en.wikipedia.org/wiki/Perceptron Read about the Perceptron Convergence Theorem and its significance https://www.nature.com/articles/323533a0тАж
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