Practical AI Application, with Denver Hunter

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

7일 전1:14:43

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1:14:43

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 mathematical concepts that power 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…

약 1년 전 36:12

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Denver Hunter serves as the Director of Information Technology at PenServ Plan Services, a full-service, third-party administrator offering retirement plan recordkeeping and administration services. In addition to his role leading their IT team, he shares perspectives on technology trends, writing for the Forbes Technology Council. Today we discuss practical applications of AI to automate tasks for the technology leader and the possibilities for help desks. We also dive into why hyperconverged technology makes sense in a cloud-centric world.
Conversation Highlights:
[02:14] Introducing our guest, Denver Hunter
[04:45] AI and banking
[09:32] Safe AI usage
[12:04] Introducing Microsoft Copilot
[15:36] Leveraging AI features
[21:49] Hunter's Forbes article
[22:55] Wins with hyperconverged technology
[29:49] Measuring project ROI
[32:10] Hunter's message to the world
Notable Quotes:
"My mindset with AI is that this hype is gonna cool a little bit and there's still going to be some amazing things to come out of it." Denver Hunter [8:14]
"The grass is greener on the other side, but the water bill is higher." Denver Hunter [33:33]
Connect With Denver Hunter
LinkedIn: https://www.linkedin.com/in/james-anderson-74894a5a/
Hunter's Small Town Blog: https://smalltownco.com/
The IT Matters Podcast is about IT matters and matters pertaining to IT.

챕터

1. Introducing our guest, Denver Hunter (00:02:14)

2. AI and banking (00:04:45)

3. Safe AI usage (00:09:32)

4. Introducing Microsoft Copilot (00:12:04)

5. Leveraging AI features (00:15:36)

6. Hunter's Forbes article (00:21:49)

7. Wins with hyperconverged technology (00:22:55)

8. Measuring project ROI (00:29:49)

9. Hunter's message to the world (00:32:10)

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