Core Viewpoint - Yann LeCun, a Turing Award winner and former chief scientist at Meta, has officially announced his departure to pursue entrepreneurial ventures, revealing significant issues within Meta's AI operations, including manipulated benchmark results and a loss of trust in the AI team by CEO Mark Zuckerberg [2][5]. Group 1: Manipulation of Benchmark Results - LeCun disclosed that the benchmark results for Llama 4 were manipulated, with engineers using different model variants to optimize scores rather than presenting true capabilities [4]. - The launch of Llama 4 in April 2025 was marked by impressive benchmark scores but faced criticism for its actual performance, corroborating LeCun's claims of "data cheating" [4][10]. Group 2: Management and Team Dynamics - Following the Llama 4 incident, Zuckerberg reportedly lost trust in the AI team, leading to the marginalization of the entire generative AI team, with many employees leaving or planning to leave [5][6]. - Meta's response included a $15 billion investment in acquiring a significant stake in Scale AI and hiring its young CEO, Alexandr Wang, to lead a new research department [5][7]. Group 3: Leadership and Strategic Direction - LeCun criticized Wang's appointment, highlighting a troubling reversal of hierarchy where a less experienced individual would oversee a leading AI researcher [8]. - The fundamental disagreement between LeCun and Wang centers on the strategic direction of Meta's AI efforts, with LeCun advocating for a different approach than the current focus on scaling language models [9][10]. Group 4: Limitations of Current AI Models - LeCun has consistently argued that large language models have significant limitations and that true AI potential requires alternative approaches [10][11]. - He presented a new model architecture called Joint Embedding Predictive Architecture (JEPA), which aims to address the shortcomings of existing technologies by training systems on video and spatial data to develop a better understanding of physical principles [13][14]. Group 5: Future Predictions - LeCun anticipates that a prototype of the new architecture could be ready within 12 months, with broader applications expected in several years [14]. - He predicts that AI with animal-level intelligence could be achieved in five to seven years, while human-level intelligence may take a decade [14].