Exploring the debate on AI progress limits, rise of synthetic data usage, and advancements in specialized AI models. Financial challenges of running AI operations and the gap between AI adoption among workers and managers are discussed.
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Quick takeaways
The pace of improvement in AI may be slowing due to challenges in data availability for training, raising questions about the limits of current technologies.
High costs of AI operations, such as Microsoft's acquisition of Inflection, could impact stock evaluations and market trends, highlighting the need to value long-term AI investments.
Deep dives
AI Pace of Improvement
Christopher Mims discusses the narrative that the pace of improvement in AI is slowing down due to challenges in generating enough data for training. The use of synthetic data for training AI models has raised questions about the potential limits of current technologies. While Gary Marcus highlights a plateau in the core capabilities of AI systems like GPT models, OpenAI's approach adds uncertainty about potential progress and internal advancements.
AI as a Commodity
The podcast explores the idea that AI could become a commodity, where technology advancements become widely known and available, reducing competitive edges. Companies like OpenAI focus on maintaining a state-of-the-art position in AI, while others like Google prioritize integrating AI across multiple products. The discussion considers implications for the industry if AI technologies reach a point where performance differentiators diminish.
AI Expense and Market Impact
Addressing the high costs of AI operations, the podcast reflects on Microsoft's acquisition of Inflection as a notable expense in the AI space. It critiques short-term Wall Street perspectives that may undervalue long-term AI investments, impacting stock evaluations and market trends. The narrative also delves into AI's disruptive potential to challenge existing SaaS models, impacting software and company valuations in the evolving AI landscape.
That's the argument in a new WSJ piece: https://www.wsj.com/tech/ai/the-ai-revolution-is-already-losing-steam-a93478b1
In this episode, NLW goes section by section through the argument -- that AI is reaching a peak of performance, that it's too expensive, and that uses are limited, discussing where he agrees and disagrees with each one.
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