Recent developments in the landscape of Large Language Models (LLMs) and their pursuit of Artificial General Intelligence (AGI) have revealed significant shortcomings. Key events from mid-2025 illustrate these challenges. In June, Apple’s studies indicated LLMs struggle with distribution shift, a core issue in neural networks. GPT-5, launched in August, failed to meet expectations. By September, renowned AI researcher Rich Sutton acknowledged the critiques of LLMs, validating longstanding concerns. In October, Andrej Karpathy and Nobel Laureate Sir Demis Hassabis voiced skepticism about LLMs’ readiness for AGI, indicating that true advancements are a decade away. These findings reinforce that while LLMs serve a utility, they fall short of achieving AGI. Renowned expert Gary Marcus has long predicted such outcomes, emphasizing the need for alternative strategies in AI development. For insights and updates, consider subscribing to the newsletter that has consistently provided accurate assessments of AI trends.
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