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An Artificial Intelligence Conversation with Andrew Ng
FYI - For Your Innovation
The Erosion of Competitive Moats
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The rapid decline in the cost of training foundational models presents significant challenges in establishing competitive moats within the AI industry. Companies may struggle to maintain long-term advantages if rivals can replicate their models at increasingly lower costs over time. Although switching costs for language models are currently low, there seems potential for performance differentiation due to a shift towards secrecy in model development, as teams no longer share their methodologies as openly as before. However, the fluidity of talent and ideas among companies makes it difficult to keep proprietary techniques under wraps indefinitely. While certain technologies might offer short-term competitive edges, their defensibility in the long term remains questionable. Historical patterns suggest that concerns over safety often lead to premature secrecy, yet these concerns eventually subside as similar technologies emerge. Overall, it indicates a dynamic landscape where collaboration and shared advancements may ultimately outweigh initial competitive advantages.
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