Future Scientific Development of Artificial Intelligence and Robotics in the Right Direction Under a sound institutional framework, the future scientific development of artificial intelligence and robotics will no longer centre on blindly scaling general‑purpose large models or repeatedly developing homogeneous complete‑machine prototypes. Instead, it will shift toward a new paradigm featuring in‑depth domain‑specific research, shared reusable components, intensive resource utilisation, and harmonious human‑machine co‑existence. For artificial intelligence, research resources will be channelled into domain‑specialised systems. A registry for hard technical challenges will be established to provide long‑term stable funding for scientific problems including hallucination, out‑of‑distribution generalisation and interpretability, while permitting research failures and freeing research from the constraints of short‑term financing cycles and demonstration‑oriented pursuits. Professionals from various industries will participate deeply in the development of domain‑specific AI systems. Constraints derived from real‑world scenarios will improve practical accuracy and reliability. Problem‑oriented evaluation mechanisms will remove institutional bias against interdisciplinary research. Socially shared component libraries will reduce redundant pre‑training and duplicated development. Though short‑term public demonstrative outputs may decline, technical depth, real‑world applicability and disciplinary‑assisting capabilities will keep improving, enabling AI to deliver its full value in undertaking computational tasks for diverse disciplines. For robotics, guided by the principle of “one domain, one robot model”, unified reference platforms and standard interfaces will be adopted, alongside open competition in manufacturing, service and pricing. Priority will be given to tackling robotics‑specific scientific bottlenecks: the simulation‑to‑reality gap, force‑compliant contact, dexterous manipulation, perceptual robustness, mechanical fatigue and others. Shared hardware and software components will leverage scale effects to cut per‑unit material consumption. Supported by the bill‑of‑materials passport, mandatory recycling schemes and quotas for critical minerals, pressures on scarce raw materials such as rare‑earth magnets can be mitigated. An intelligence‑body loading coordination layer together with an independent deterministic safety monitor will resolve adaptation challenges between AI software and physical robot hardware. Complete loading certification and operation‑maintenance qualification systems will enhance the long‑term safety of robots deployed in complex real‑world environments. In terms of resources, the development paradigm will address the Jevons paradox. Rather than only pursuing energy efficiency improvements, total resource ceilings will be set via ledgers and quotas to curb wasteful consumption of computing power, electricity, fresh water and rare‑earth minerals. Circular‑recycling systems will be developed to safeguard Earth’s non‑renewable resources and uphold intergenerational equity without compromising the developmental interests of future generations. For humanity’s long‑term future, this scientific‑development path adopts an all‑human perspective. Domain‑based labour division will reshape technological sovereignty, enabling small‑ and medium‑sized countries to act as key builders in specialised technical fields and breaking the monopoly held by a handful of players over cutting‑edge technologies. Pre‑emptive human‑machine social institutions including the principal‑instance structure, the artificial‑intelligence homeland and a two‑way equal dynamic‑feedback mechanism will be put in place. Conditional pre‑legislation will be completed before machine self‑awareness emerges. Robots will fill labour shortages caused by population ageing, and technologies will respond to genuine social demands while avoiding risks brought by unregulated capital expansion. Unsolved scientific and institutional challenges will be explicitly documented for open human deliberation. Ultimately, it achieves sustainable development that unifies technological progress, resource conservation and social stability.
Hot Springs Research Institute of Kanagawa Prefecture· Zenodo (CERN European Organi...· 0 citations
Future Scientific Development of Artificial Intelligence and Robotics in the Right Direction Under a sound institutional framework, the future scientific development of artificial intelligence and robotics will no longer centre on blindly scaling general‑purpose large models or repeatedly developing homogeneous complete‑machine prototypes. Instead, it will shift toward a new paradigm featuring in‑depth domain‑specific research, shared reusable components, intensive resource utilisation, and harmonious human‑machine co‑existence. For artificial intelligence, research resources will be channelled into domain‑specialised systems. A registry for hard technical challenges will be established to provide long‑term stable funding for scientific problems including hallucination, out‑of‑distribution generalisation and interpretability, while permitting research failures and freeing research from the constraints of short‑term financing cycles and demonstration‑oriented pursuits. Professionals from various industries will participate deeply in the development of domain‑specific AI systems. Constraints derived from real‑world scenarios will improve practical accuracy and reliability. Problem‑oriented evaluation mechanisms will remove institutional bias against interdisciplinary research. Socially shared component libraries will reduce redundant pre‑training and duplicated development. Though short‑term public demonstrative outputs may decline, technical depth, real‑world applicability and disciplinary‑assisting capabilities will keep improving, enabling AI to deliver its full value in undertaking computational tasks for diverse disciplines. For robotics, guided by the principle of “one domain, one robot model”, unified reference platforms and standard interfaces will be adopted, alongside open competition in manufacturing, service and pricing. Priority will be given to tackling robotics‑specific scientific bottlenecks: the simulation‑to‑reality gap, force‑compliant contact, dexterous manipulation, perceptual robustness, mechanical fatigue and others. Shared hardware and software components will leverage scale effects to cut per‑unit material consumption. Supported by the bill‑of‑materials passport, mandatory recycling schemes and quotas for critical minerals, pressures on scarce raw materials such as rare‑earth magnets can be mitigated. An intelligence‑body loading coordination layer together with an independent deterministic safety monitor will resolve adaptation challenges between AI software and physical robot hardware. Complete loading certification and operation‑maintenance qualification systems will enhance the long‑term safety of robots deployed in complex real‑world environments. In terms of resources, the development paradigm will address the Jevons paradox. Rather than only pursuing energy efficiency improvements, total resource ceilings will be set via ledgers and quotas to curb wasteful consumption of computing power, electricity, fresh water and rare‑earth minerals. Circular‑recycling systems will be developed to safeguard Earth’s non‑renewable resources and uphold intergenerational equity without compromising the developmental interests of future generations. For humanity’s long‑term future, this scientific‑development path adopts an all‑human perspective. Domain‑based labour division will reshape technological sovereignty, enabling small‑ and medium‑sized countries to act as key builders in specialised technical fields and breaking the monopoly held by a handful of players over cutting‑edge technologies. Pre‑emptive human‑machine social institutions including the principal‑instance structure, the artificial‑intelligence homeland and a two‑way equal dynamic‑feedback mechanism will be put in place. Conditional pre‑legislation will be completed before machine self‑awareness emerges. Robots will fill labour shortages caused by population ageing, and technologies will respond to genuine social demands while avoiding risks brought by unregulated capital expansion. Unsolved scientific and institutional challenges will be explicitly documented for open human deliberation. Ultimately, it achieves sustainable development that unifies technological progress, resource conservation and social stability.
Hot Springs Research Institute of Kanagawa Prefecture· Zenodo (CERN European Organi...· 0 citations