DeepMind releases ASI report: AI can offset R&D slowdown, but physical delay is the ultimate brake for super intelligence According to Beating monitoring, Google DeepMind has released its latest research report, pointing out that the transition from General Artificial Intelligence (AGI) to Super Intelligence (ASI) may not be a single social upheaval, but a series of continuous breakthroughs across multiple scientific fields. In response to the traditional bottleneck of increasing research difficulty, the report points out that although the number of R&D personnel required to maintain Moore's Law has increased by eighteen times compared to the 1970s, digital intelligent agents can be infinitely replicated, allowing humans to increase research resources by twenty times in a few hours, thereby systematically offsetting the decline in research productivity. There are four parallel paths towards super intelligence: expanding scale, evolving algorithms, recursive self-improvement, and multi-agent collaboration. However, the transformation process faces five major bottlenecks: data walls, resource costs, limitations in neural network paradigms, increasing difficulty in scientific research, and abstract barriers. The core constraint that limits scientific discoveries lies in the abstract barrier, which means that systems trained solely on existing human data are difficult to break away from existing conceptual frameworks. If intelligent agents want to discover new concepts, they must overcome embodied bottlenecks by interacting with the real physical world. The verification process is limited by physical latency, thus limiting the hardware's recursive self improving loop to the experimental speed of the real world. In terms of social and organizational structure, digital intelligence has lossless replication and high bandwidth information sharing, which makes super intelligence tend to appear in the form of swarm intelligence rather than a single model. Through multi-agent collaboration, AGI intelligent agents can form virtual economies or fully automated companies based on price signals. Due to the high bandwidth communication between AI, an AI decision-maker can instantly communicate with all members. The deep bureaucratic hierarchy designed to overcome communication bottlenecks in traditional human organizations will be completely erased in super intelligent organizations. [Original link]