In Part 1 of Episode 6, Amit Prakash and Dheeraj Pandey dive into the intriguing evolution of artificial intelligence, mapping its progress over the decades. This episode takes listeners through the origins of AI in the 1950s, where concepts initially stemmed from biological brain studies, to the major breakthroughs in computer science that have shaped AI development. Through analogies and real-world examples, they explore foundational ideas like neural networks, convergence, and the challenges of context and memory in recursive neural networks. They also delve into the impact of advancements in microprocessors, from Intel's complex instruction sets to NVIDIA's GPU innovations, explaining how these technologies enabled the computational leaps necessary for AI's growth.

Join Amit and Dheeraj for this first segment on AI history as they lay down the complex, layered journey that has led to the AI advancements we see today.
Key Topics & Chapter Markers:

• AI's Evolutionary Journey & Key Challenges [00:00:00]
• Neural Networks: Inspiration from Biology [00:01:00]
• Weighted Sum, Inputs & Mathematical Functions [00:05:00]
• Gradient Descent & Optimization in Neural Nets [00:10:15]
• Computing Architecture: CPUs vs. GPUs [00:39:56]
• RNNs and Early Problems in Memory & Context [01:03:00]
• The Emergence of Convolutional Neural Networks (CNNs) [01:10:00]
• ImageNet, GPUs & Scaling Neural Networks [01:24:00]
  

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