174 | AI Evolution | AI Applications | Neural Networks and Challenges with Jamie Smith from Imandra.ai

💡 Key Talking Points:🗝️ AI Evolution: Reflecting on the past decade, AI has transformed industries. Challenges in data analysis and variance led to innovative solutions.🤖 AI Applications: From predictive maintenance to controls applications, AI's power was harnessed. The potential for viable business ventures became evident.🌐 Neural Networks and Challenges: Neural networks excel in language translation but struggle with reasoning. Symbolic AI offers mathematical reasoning for improved accuracy.➡️ Book a Call with Chad📜 Episode Summary:In this episode 174 of "Failing to Success", Jamie Smith, VP of Product Management at Imandra, discusses the evolution of AI over the past decade. He started with predictive maintenance and leveraged AI's potential in various applications, including controls. Neural networks excel in language translation but lack reasoning abilities. Jamie introduces Symbolic AI, based on mathematical reasoning, which can prove correctness in systems. He highlights its application in addressing biases and offers unique insights into the world of AI.SUBSCRIBE TO THE PODCAST ON YOUTUBEListen on:APPLE PODCASTS‍SPOTIFY‍CASTBOX‍PODCAST ADDICTGOOGLE PODCASTS‍Add us on:INSTAGRAMTIKTOKTWITTERLINKEDINAI evolution, business insights, entrepreneurship, AI applications, Symbolic AI, neural networks, AI challenges, AI industry, business advice, AI innovation, Jamie Smith, Imandra, AI reasoning, AI trends, AI future, machine learning, predictive maintenance, controls applications, neural network limitations, mathematical reasoning, AI bias, AI accuracy