一封来自Transformer之父的分手信：8年了，世界需要新的AI架构

Core Viewpoint - The co-author of the Transformer paper, Llion Jones, expresses concerns about the current state of AI research, stating that the influx of capital and talent has led to a narrow focus on existing architectures rather than exploring new ones. He advocates for a return to curiosity-driven research instead of performance metrics and competition [1][4][5]. Group 1: Current State of AI Research - AI research has become increasingly narrow, with researchers focusing on optimizing existing models rather than innovating new architectures [4][5]. - The overwhelming attention and funding in the AI sector have resulted in a competitive environment where researchers prioritize quick results over genuine exploration [5][9]. - Jones compares the current situation to the era before the Transformer, where incremental improvements to RNNs were made without significant breakthroughs [7][9]. Group 2: The Need for Freedom in Research - Jones emphasizes that the success of the Transformer was due to a free and exploratory environment, contrasting it with the current pressure to meet performance indicators [10][12]. - He argues that creativity and imagination are stifled in the current research climate, where many are hesitant to take risks due to performance expectations [12][13]. - At Sakana AI, Jones aims to recreate an environment that fosters curiosity and natural inspiration, moving away from strict KPIs [16][20]. Group 3: Future Directions and Innovations - Jones believes that the next significant breakthrough in AI could be just around the corner if the focus shifts from competition to collaboration and exploration [24]. - He suggests that the current strength of the Transformer technology may be hindering the search for better alternatives, as researchers are less motivated to innovate when existing solutions are already effective [21][22]. - The call for a collective approach to research, where discoveries are shared openly, could lead to the next transformative advancement in AI [23][24].