Eye On A.I.

Jonathan Gillham, founder of Originality AI, discusses the origins and use cases of AI detection technology to distinguish between AI and human-generated content. He talks about the ethical considerations of AI-generated content, the challenges faced by web publishers using AI, and Google's stance on AI-generated spam. The podcast also explores the importance of differentiating between AI and human content, and advancements in testing new AI models like Gemini 1.5.

CTO at WorkFusion Peter Cousins discusses how AI fights financial crimes through sanction screening, adverse media analysis, and KYC processes. The podcast delves into the challenges of implementing generative AI in finance, the importance of explainability, and the ongoing arms race against financial criminals.

Join Rahul Sonwalkar, CEO of Julius AI, as he discusses the future of programming with AI-powered code generation. Learn about Julius AI's innovative approach to data analysis, challenges in AI code generation, and real-world applications in financial analysis and biostatistics. Explore how Julius AI is revolutionizing programming with simple English commands and making data science accessible to everyone.

Edward Balassanian, CEO of Aimi, discusses AI music creation, training models with quality data, legal challenges in the music industry, and the applications of AI music in gaming, social media, and content creation. He explores Aimi's unique platform for generative music, emphasizing the importance of human elements in music creation and the future plans for the company.

Mohamed Elgendy from Kolena talks about systematic testing for AI models, emphasizing the importance of structured frameworks, human evaluation, and collaboration with industry bodies to shape AI standards. They discuss challenges in testing AI models, defining metrics, fine-tuning generative AI models, and risk mitigation strategies, highlighting the importance of ongoing monitoring and standardization.

Ronen Dar, CTO of Run:ai, discusses maximizing GPU utilization for AI, tackling GPU shortage challenges, evolving towards larger models like GPT-4, and predicting an exponential increase in demand for computational power. The conversation delves into the intricacies of managing and optimizing GPU clusters efficiently and addressing the future of AI deployment across industries.

Damon Rasheed and Saurabh Jain of Opyl & Trialkey.ai discuss achieving 90% accuracy in predicting drug clinical trial outcomes using AI. They share insights on using past trials data, optimizing trial designs, and employing NLP for data processing. The episode highlights the impact of AI on revolutionizing pharmaceutical research and making trials more efficient.

Professor André van Schaik discusses DeepSouth, a brain-scaled neuromorphic computing system simulating 100 billion neurons in real-time. The conversation delves into spiking neurons, synapses, FPGAs, and the potential to transform AI models. Discover the unique hardware setup, testing on excitation-inhibition networks, and how this technology could facilitate large-scale simulations. Explore the intersection of neuroscience, AI, and computational technology.

William Falcon, ML model deployment expert, discusses Lightning Studio, a cloud-based AI platform. He explains PyTorch Lightning's evolution, democratizing AI development. The podcast explores coding on the cloud, AI deployment challenges, and the rapid growth of the PyTorch Lightning community.

Dragomir Anguelov from Waymo discusses the future of autonomous driving, highlighting advancements in machine learning, challenges of scaling complex systems, and breakthroughs in deploying robotaxis. He explores the evolution of neural networks and the convergence of AI, robotics, and transportation for developing safe and reliable self-driving cars.