Tom and Nate discuss the growth of open AI models, Gartner Hype Cycle, infrastructure constraints, AI risks as public health problems, and the relationship between AI ecosystem and models. They reflect on releasing open model weights, AI's impact on public health, and navigating the 'trough of disillusionment'. The podcast explores historical narratives, legislative challenges, and staying grounded in the AI landscape.
Open models are expanding, necessitating a shift to managing risks and infrastructure over open versus closed debates.
Experiencing a solar eclipse highlights the insignificance of humanity in cosmic phenomena, contrasting the artificial hype around AI models.
The AI industry's transition from hype to disillusionment calls for a focus on practical applications, risk management, and regulatory frameworks for public health.
Deep dives
The Significance of Lunar Nodes in Astronomy
Lunar nodes, also known as dragon points, represent the intersections of the moon's orbit and the ecliptic. The ascending node symbolizes the head of the dragon, while the descending node represents its tail, crucial for calculating the calendar and predicting solar and lunar eclipses in classical astronomy.
Challenges and Developments in AI Model Releases
Amidst an array of AI model releases, the lack of documentation for new versions like Chat GPT raises concerns. OpenAI's approach and the release of models like Gemini 1 million context length have sparked discussions on the accessibility and practical usage of such models.
Reflections on Cosmic Phenomena and Human Existence
Experiencing a solar eclipse and witnessing celestial alignments prompts reflections on humanity's insignificance amidst cosmic forces. Contrasting AI models' artificial hype, the eclipse underscores nature's transformative power, fostering a sense of celestial connection and awe.
Transitioning Towards AI Regulation and Reevaluation of Ambitions
An evolving perception of AI's impact leads to calls for regulatory frameworks, analogous to the historical establishment of agencies like the EPA. The trajectory from AI's glory to disillusionment signals a shift towards managing AI's tangible risks, emphasizing public health and policy considerations.
From AI Model Enthusiasm to a Pragmatic Approach
As enthusiasm wanes, focusing on AI's tangible applications and risk management emerges as a pragmatic necessity. Embracing maturity in AI discourse involves grasping the effects of open model weights, transitioning from speculative hype to grounded understanding and actionable insights.
Tom and Nate catch up after a few weeks off the pod. We discuss what it means for the pace and size of open models to get bigger and bigger. In some ways, this disillusionment is a great way to zoom our into the big picture. These models are coming. These models are getting cheaper. We need to think about risks and infrastructure more than open vs. closed.
00:00 Introduction 01:16 Recent developments in open model releases 04:21 Tom's experience viewing the total solar eclipse 09:38 The Three-Body Problem book and Netflix 14:06 The Gartner Hype Cycle 22:51 Infrastructure constraints on scaling AI 28:47 Metaphors and narratives around AI risk 34:43 Rethinking AI risk as public health problems 37:37 The "one-way door" nature of releasing open model weights 44:04 The relationship between the AI ecosystem and the models 48:24 Wrapping up the discussion in the "trough of disillusionment"
We've got some links for you again: - Gartner hype cycle https://en.wikipedia.org/wiki/Gartner_hype_cycle - MSFT Supercomputer https://www.theinformation.com/articles/microsoft-and-openai-plot-100-billion-stargate-ai-supercomputer - Safety is about systems https://www.aisnakeoil.com/p/ai-safety-is-not-a-model-property - Earth day history https://www.earthday.org/history/ - For our loyal listeners http://tudorsbiscuitworld.com/
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