Are we approaching AI development all wrong? In this eye-opening conversation, Dr. Sean Kennedy from Nokia Bell Labs challenges four widespread beliefs that are actually slowing down AI innovation.
🔍 What We Cover:
Myth 1: Regulation Kills Innovation Discover why uncertainty, not regulation itself, is the real barrier to AI progress and how Nokia's six pillars of responsible AI (fairness, reliability, privacy, transparency, sustainability, and accountability) provide a framework for moving forward with confidence.
Myth 2: Scaling Models Will Lead To AGI Learn why simply making AI models bigger won't achieve artificial general intelligence and why we need "Gen AI Plus," combining fast intuitive thinking with symbolic reasoners, knowledge graphs, and physical world models.
Myth 3: General Models Create Maximum Value Understand the hidden costs of general AI models and their impact on economic divides, particularly in rural communities versus metropolitan areas.
Myth 4: More Data Equals Better AI Find out why quality trumps quantity when it comes to data and how medium-sized language models trained on clean, proprietary data can outperform massive general models while being cheaper and more sustainable.
💡 Key Insights:
✅ How to build responsible AI frameworks that enable rather than constrain innovation
✅ The future of AI lies in hybrid systems, not just bigger models
✅ Physical world models are essential for the next leap in AI capability
✅ Why companies need to think beyond immediate metrics to societal impact
Dr. Sean Kennedy leads artificial intelligence research at one of the world's most prestigious innovation labs. His work spans AI-native networks, generative AI applications, and responsible AI development.
🎯 Perfect for business leaders, technologists, AI practitioners, and anyone interested in understanding where AI is really headed and what actually matters for progress.
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