While the tech world buzzes with predictions of artificial general intelligence (AGI) on the horizon, Meta's Yann LeCun offers a critical view. Amidst claims by tech leaders like Nvidia's Jensen Huang and Elon Musk on the imminent arrival of AGI, LeCun—a prominent AI scientist and Turing Award winner—suggests caution. According to LeCun, human intelligence encompasses abilities that AI currently lacks, including reasoning, planning, persistent memory, and understanding the physical world. He underscores that current AI systems and large language models (LLMs), despite their linguistic prowess, lack a deep understanding of reality, at best simulating a mere echo of human intellect. LeCun criticizes the LLMs' over-reliance on textual data to mimic intelligence, highlighting the contrast with human learning that significantly draws from interactions with the physical world. He puts forth that the architecture of AI needs substantial revision if it is to aspire to a human level of understanding. To bridge this gap, LeCun proposes an 'objective-driven AI,' where systems are trained through sensory experiences and video data to develop world models. These models enable the AI to anticipate the outcomes of actions and learn from experience in a manner that is closer to how humans understand the world around them. Moving beyond the shortcomings of LLMs, objective-driven AI as envisioned by LeCun would aim for specific human-set goals. By simulating the impact of actions within their world models, such systems would build a memory of potential consequences, thus facilitating better planning and action-taking capabilities. LeCun tempers the AGI enthusiasm with a message of patience, inferring that surpassing human intelligence is a more distant goal than some might suggest. His commitment to the development of objective-driven AI systems reflects a step toward machines that can learn and interact with the physical world more intuitively, paving the way for more substantial AI advancements in the future.