Published Jun 8, 2020

Explaining AI explainability

Sheldon Fernandez shares insights on generative synthesis and its transformative role in refining AI models for optimal performance, while emphasizing the necessity of AI explainability in understanding decision-making and preventing failures. The discussion also explores the impact of Edge AI across industries, focusing on the benefits of deploying compact, efficient networks.

Episode Highlights

Topics covered

Generative Synthesis
01
AI Explainability
02
AI at the Edge
03

Explaining AI explainability

Topics covered

Popular Clips

Future of AI

AI Bias and Explainability

AI Innovations Journey

Generative Model Technology

AI Explainability Primer

Human-AI Collaboration

AI Explainability Insights

AI Efficiency Insights

AI at the Edge

AI at the Edge

AI Innovations Journey

AI Workflow Integration

Edge AI Deployment

Episode Highlights

Generative Synthesis

AI Explainability

AI at the Edge

Explaining AI explainability

Topics covered

Popular Clips

Episode Highlights

Generative SynthesisGenerative synthesis offers a novel approach to AI model optimization, producing compact and explainable networks. Sheldon Fernandez discusses its advantages over traditional methods like AutoML, emphasizing the role of human intuition in refining AI models.

Generative Synthesis

AI Explainability

AI at the EdgeSheldon Fernandez, CEO of Darwin AI, discusses the significance of Edge AI and its impact on various industries. He highlights the challenges and opportunities in deploying AI at the edge, emphasizing the need for compact, efficient networks.

AI at the Edge