Azeem Azhar's Exponential View

The podcast discusses the challenges in AI research and product development, democratizing information access, the 'innovator's dilemma' for Google Search, conversational interfaces, and interests shaping AI regulation debate.

The podcast delves into the ideological schism within OpenAI and its impact on AI safety and development. It explores the power dynamics in the tech industry and the potential future implications. The guest discusses real-world examples and tension surrounding the development of GPT-4. It also highlights the influence of cultural norms and the need for transparency and accountability in technology development.

Fei-Fei Li, pioneering AI scientist and professor at Stanford, discusses the transformation of AI development from computer vision, rethinking human and machine value systems, and how the road to AGI can help us learn about human cognition.

Murray Shanahan, veteran AI scientist at Imperial College London and principal scientist at DeepMind, discusses the importance of embodied interaction in AI progress, potential breakthroughs in the field, and how salary inflation for commercial AI engineers may hinder research.

Leading expert on AI governance, Joanna Bryson, discusses the concept of intelligence and AI, the benefits and dangers of developing AI, and the challenge of explainability in AI systems.

Artificial Intelligence (AI) is on every business leader’s agenda. How do you ensure the AI systems you deploy are harmless and trustworthy? This month, Azeem picks some of his favorite conversations with leading AI safety experts to help you break through the noise. Today’s pick is Azeem’s conversation with Meredith Whittaker, president of the Signal Foundation. Meredith is a co-founder and chief advisor of the AI Now Institute, an independent research group looking at the social impact of artificial intelligence. They discuss: How discriminatory culture influences the values embedded in AI. Whether ethics officers can actually influence firms and their products. Why responsible AI design must include recognition of the shadow workforce helping to create it.

Dr. Rumman Chowdhury, a pioneer in applied algorithmic ethics, discusses assessing and diagnosing bias in 'black box' algorithms, top-down organizational change necessary for responsible AI, and the emerging field of 'Responsible Machine Learning Operations'.

Leaders face the challenge of making future-proof decisions in the age of exponential technologies. A new podcast explores new perspectives on our collective future. Guests like OpenAI CEO Sam Altman and Silicon Valley investor Vinod Khosla discuss topics like owning thoughts and reducing global inequality with AI.

In his brief commentary, Azeem Azhar discusses the increasing complexity and capabilities of large language models (LLMs) and the transformative potential they hold. Just as the Copernican Revolution forced us to reassess our understanding of the universe and led to numerous societal and scientific changes, Azeem proposes that rapid advancements in AI could lead to a similar paradigm shift that challenges established norms and systems. @azeem @exponentialview Further resources: Exponential LLMs and the Copernican Moment, Azeem Azhar, 2023

Azeem Azhar discusses the potential of large-language models to revolutionize the web, serving as the successor to web 2.0. He explores the challenges of web 3.0 and highlights the benefits and new behavioral interactions that large-language models can bring to the internet. He also delves into the future of the web, examining the possibility of a single dominant winner or fragmented services driven by large language models. concerns about centralized models, the importance of cultural heritage and privacy-safe on-device models, and the prediction of a variety of systems with slight differences.