The Potential and Challenges of the Voluntary Carbon Market

Climate Rising

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Understanding the Elegant Math Behind Modern Machine Learning 1:14:43

7 days ago1:14:43

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Artificial intelligence is evolving at an unprecedented pace—what 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 today’s 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 AI’s pioneers about the road to AGI—should we be concerned, or are we still missing key pieces of the puzzle? The conversation also delves into AI’s philosophical implications—could 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, Anil’s latest book on the math behind AI https://www.amazon.com/Why-Machines-Learn-Elegant-Behind/dp/0593185749 Learn more about Anil Ananthaswamy’s work and writing https://anilananthaswamy.com/ Watch Anil Ananthaswamy’s TED Talk on AI and intelligence https://www.ted.com/speakers/anil_ananthaswamy Discover the MIT Knight Science Journalism Fellowship that shaped Anil’s 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/323533a0…

about a year ago 56:59

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Our second episode on the voluntary carbon market is a bonus episode of a panel discussion recorded at Harvard Climate Action Week in 2024. Harvard Kennedy School Professor Joe Aldy

moderates this discussion with Nat Keohane from the Center for Climate and Energy Solutions, Donna Lee from Calyx Global, UC San Diego Professor David Victor, and Carolyn Weinberg, formerly of Blackrock. Together, they bring perspectives from policy, business, and academia. The conversation explores the role of voluntary carbon markets in mobilizing finance for decarbonization, ensuring the integrity of carbon credits, and scaling high-quality projects. They also discuss emerging standards, innovative financial products, and how companies can leverage VCMs to achieve net-zero goals while addressing climate risks.

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#MBA #Business #Harvard Business School #Environment Initiative #Climatechange #Globalwarming #Science #Natural Sciences #HBS