OpenAI’s GPT-5 was anticipated as a significant leap toward achieving artificial general intelligence (AGI), but reality fell short of expectations. CEO Sam Altman initially expressed confidence that AGI construction was achievable by 2025, yet critiques from experts like Gary Marcus labeled GPT-5 as “overhyped and underwhelming.” A recent MIT report revealed that 95% of generative AI deployments in businesses yielded no returns, leading to stagnant tech stock performance. Experts suggest the field is entering Gartner’s “trough of disillusionment,” where inflated expectations are met with reality. Despite initial excitement, recent AI tool launches received lukewarm feedback, and user dissatisfaction led OpenAI to restore its previous GPT-4 model. Additionally, AI struggles with tasks requiring soft skills, highlighting a significant gap in training data. While advancements are possible through enhanced data practices, the industry faces challenges in proving AI’s effectiveness in high-skill areas, casting doubt on the rapid realization of AGI.
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