Core Insights - The article discusses the establishment of a new company named Advanced Machine Intelligence Labs (AMI Labs), founded by Yann LeCun, which aims for a valuation of €3 billion (approximately ¥24.7 billion) and plans to officially launch in January 2026 [2][11]. Group 1: Company Overview - AMI Labs will focus on the research direction of "world models," which LeCun has been advocating, and will adopt an open-source approach while maintaining collaboration with Meta [3][5]. - The company is seeking to raise €500 million (approximately ¥4.1 billion) in its first round of funding [11]. - The CEO of AMI Labs will not be LeCun but rather Alexandre LeBrun, a former subordinate of LeCun [4][14]. Group 2: Technical Direction - AMI Labs will pursue a more challenging path than mainstream large language models (LLMs) by focusing on "world models," as LeCun believes that current LLMs have fundamental logical flaws and do not truly understand the physical world [6]. - The company will utilize a Joint Embedding Predictive Architecture (JEPA) to build its technological foundation, emphasizing "abstraction" and "planning" rather than predicting every pixel like video generation models [8][9]. - This approach aims to enable AI to focus on understanding key dynamic changes, akin to human or animal reasoning and planning capabilities [9]. Group 3: Leadership and Background - Alexandre LeBrun, the new CEO, has a strong background in AI and has previously worked closely with LeCun at Meta, where he was responsible for engineering at FAIR [25][28]. - LeBrun's experience includes founding the AI company Nabla and has a history of successful entrepreneurship in the tech sector [17][24]. - The leadership structure at AMI Labs is expected to be a dual-core model, with LeCun focusing on research and LeBrun on commercial aspects [29].

Core Viewpoint - Yann LeCun criticizes the current AI development path focused on scaling large language models, arguing it leads to a dead end and emphasizes the need for a different approach to achieve true AI capabilities [1][2]. Group 1: AI Development Path - LeCun believes the key limitation in AI progress is not reaching "human-level intelligence" but rather achieving "dog-level intelligence," which challenges the current evaluation systems centered on language capabilities [2]. - He advocates for the development of "world models" that can understand and predict the world, contrasting with mainstream models that focus on generating text or images [2][8]. - LeCun's new company, AMI, aims to pursue this alternative technical route, emphasizing cognitive and perceptual fundamentals rather than merely scaling existing models [2][7]. Group 2: Research and Open Science - LeCun stresses the importance of open research, arguing that true research must be publicly shared and scrutinized to avoid the pitfalls of insular corporate environments [5][6]. - He believes that allowing researchers to publish their work fosters better research quality and motivation, which is often overlooked in many industrial labs [6]. Group 3: World Models and Learning - The concept of world models involves creating abstract representations of the world to predict outcomes, rather than relying on pixel-level predictions, which are ineffective in high-dimensional data [8][10]. - LeCun emphasizes that effective learning requires filtering out unpredictable details and focusing on relevant aspects of reality, which is crucial for developing intelligent systems [10][22]. Group 4: Data and Training - LeCun highlights the vast difference in data requirements between language models and video data, noting that video data is richer and more valuable for learning due to its structural redundancy [18][19]. - He argues that relying solely on text data will never lead to human-level intelligence, as it lacks the necessary complexity and richness found in real-world data [19][25]. Group 5: Future of AI and AGI - LeCun expresses skepticism about the concept of "general intelligence," suggesting it is a flawed notion and that true progress will be gradual rather than sudden [30][32]. - He predicts that achieving "dog-level intelligence" will be the most challenging part of AI development, with significant advancements expected in the next 5 to 10 years if no unforeseen obstacles arise [32][34]. Group 6: Industry Trends and Company Direction - LeCun's departure from Meta and the establishment of AMI reflect a desire to pursue a different technological path amid a trend of companies focusing on large language models [1][48]. - He notes that the competitive environment in Silicon Valley often leads to a monoculture where companies pursue similar technological routes, which can stifle innovation [48].