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The article discusses the historical context of artificial intelligence, highlighting the two significant AI winter periods that led to disillusionment and reduced funding. It emphasizes the transition to the current AI spring, where advancements in computational power and data availability have revitalized interest and investment in AI technologies. The author reflects on personal experiences during the second AI winter, particularly the challenges faced while founding the company INTERVAL.
The piece also explores the distinctions between research, technology, development, and innovation, clarifying how these stages impact the evolution of AI. It argues that understanding these phases is crucial for investors, especially in emerging fields like quantum computing, which has seen fluctuating valuations due to premature expectations. The author concludes by suggesting that innovation often occurs at the edges of different fields, particularly in regions rich in cultural and economic diversity.
• AI winter periods caused significant disillusionment and funding reductions.
• Current AI spring benefits from advancements in computational power and data availability.
AI winter refers to periods of reduced interest and funding in artificial intelligence due to unmet expectations.
AI spring signifies a resurgence in interest and investment in AI technologies, driven by recent advancements.
Machine learning involves algorithms that allow computers to learn from and make predictions based on data.
INTERVAL was founded to develop a fourth-generation AI language, reflecting early AI ambitions during the second AI winter.
Bose's research contributions highlight the gap between theoretical discoveries and practical applications in AI.
Apple's involvement in AI research illustrates the challenges of translating research into marketable products.
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