硅谷“钱太多”毁了AI ？！前OpenAI o1负责人炮轰：别吹谷歌，Q-Star 被炒成肥皂剧，7年高压被“逼疯”！

Core Viewpoint - The departure of Jerry Tworek from OpenAI highlights the growing divide between AI research and commercialization, emphasizing the need for risk-taking in foundational research that is increasingly difficult in a competitive corporate environment [3][4][5]. Group 1: Departure and Industry Insights - Jerry Tworek's exit from OpenAI was met with shock among employees, indicating his significant influence within the company [3][10]. - Tworek criticized the AI industry for a lack of innovation, stating that major companies are developing similar technologies, which pressures researchers to prioritize short-term gains over experimental breakthroughs [4][5]. - He pointed out that Google's success in catching up with OpenAI was due to OpenAI's own missteps, including slow actions and failure to leverage its initial advantages [4][5]. Group 2: Organizational Challenges - Tworek identified organizational rigidity as a barrier to innovation, where team structures limit cross-team research and collaboration [4][22]. - He expressed concern that the current state of the AI industry resembles a soap opera, where personal movements and internal conflicts overshadow genuine research progress [6][7]. Group 3: Future Research Directions - Tworek emphasized the importance of exploring new research paths rather than following the mainstream trajectory, advocating for more diversity in AI model development [30][31]. - He highlighted two underexplored areas: architectural innovation beyond the Transformer model and the integration of continual learning into AI systems [45][47]. - Tworek believes that significant advancements in AI will require a shift away from the current focus on scaling existing models and towards more innovative approaches [26][28]. Group 4: AGI and Industry Evolution - Tworek updated his perspective on the timeline for achieving AGI, acknowledging that while current models are powerful, they still lack essential capabilities like continuous learning and multimodal perception [49][50]. - He noted that the rapid evolution of AI technology and increasing investment in the field could lead to breakthroughs sooner than previously anticipated [51].