In 2017, researchers at Chinese technology firm Baidu demonstrated that pouring more data and computing power into machine learning algorithms yielded mathematically predictable improvements, regardless of whether the system was designed to recognize images, speech, or generate language.
Reports suggested that leading AI companies are experiencing diminishing returns on scaling their AI systems, with OpenAI's Orion model failing to meet expectations in internal testing.
The co-founders of Andreessen Horowitz noted that increasing computing power is no longer yielding the same "intelligence improvements" as before, signaling a potential shift in AI development strategies.
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