The “Intelligent World 2035” report delves deeply into the development trends of artificial intelligence (AI) and information technology (ICT) over the next decade, as well as their impact on society, the economy, and daily life. The report outlines the ten major technological leaps that will profoundly change human production methods, lifestyles, and social structures. Below is a detailed summary of these ten trends:
Core Idea: The development of General Artificial Intelligence (AGI) requires AI to move from the digital world to the physical world, achieving an integration of perception, cognition, decision-making, and action through real-time interaction with the physical environment.
Technical Challenges: While AI has made significant progress in perception and generation, it still falls short in deep abstraction and reasoning capabilities for complex physical phenomena.
Future Outlook: In the next decade, AI will achieve the transformation from understanding the world to changing the world through new architectures and technologies, such as world models and embodied intelligence.
2. From Execution Tools to Decision Partners, AI Agents Drive Industrial Revolution
Core Idea: AI agents will evolve from simple execution tools to partners with autonomous decision-making capabilities, able to autonomously execute a variety of tasks in a closed loop.
Technical Challenges: The development of agents needs to overcome core technical challenges such as multi-agent collaboration, interaction in cloud environments, and long-term reasoning cognition.
Future Outlook: By 2035, Level 4 guiding agents will be implemented on a large scale in certain fields, driving a paradigm revolution across industries.
3. Human-Machine Collaborative Programming Reshapes the Future of Software
Core Idea: AI will deeply participate in the software development process, from code generation to testing and validation, significantly enhancing development efficiency and quality.
Technical Challenges: How to address the trustworthiness of complex software and how to achieve system decomposition, integration, and collaboration in large software engineering projects.
Future Outlook: The software development model will shift from traditional assembly line methods to an agent-based software development lifecycle (SDLC), making development processes smarter and more automated.
4. AI Elevates Dimensions in the Mirrored World, New Interactions Break Immersion Experience
Core Idea: AI will drive human-machine interaction from two-dimensional planes and single-modal to three-dimensional spaces and multi-modal, providing a more natural and immersive interaction experience.
Technical Challenges: How to achieve the fusion and alignment of multi-modal data, and how to enhance the performance of interaction devices and user experience.
Future Outlook: By 2035, Spatial Multi-Modal Interaction Interfaces (SMUI) will become mainstream, allowing users to interact with devices through various means such as eye movements, gestures, and body posture.
5. Mobile Internet Ecosystem Shifts from Apps to Multi-Agent Collaboration
Core Idea: The mobile internet will transition from an app-centered model to a multi-agent collaboration model centered around intelligent agents.
Technical Challenges: How to achieve efficient communication and collaboration among agents, and how to build a secure and reliable agent ecosystem.
Future Outlook: By 2035, users will complete complex tasks through a main agent calling multiple vertical and specialized agents for automatic service execution.
6. Embodied Intelligence Bridges the Gap, Forming Multiple Trillion-Dollar Industries
Core Idea: Embodied intelligence combines AI technology with physical entities, enabling AI to perceive and manipulate the physical world through its body.
Technical Challenges: The development of embodied intelligence needs to address a series of technical challenges such as hand operations, spatial perception, and tactile perception.
Future Outlook: By 2035, embodied intelligence will achieve large-scale applications in fields such as intelligent driving, intelligent robotics, and low-altitude economy, forming multiple trillion-dollar industries.
7. Breaking the Von Neumann Architecture, New Computing Power Meets Massive Demand
Core Idea: With the rapid development of AI technology, the demand for computing power will grow exponentially, and the traditional Von Neumann architecture will be unable to meet this demand.
Technical Challenges: How to overcome the bottleneck of separating storage and computation, achieving storage-computing synergy and innovating new computing paradigms.
Future Outlook: By 2035, new computing technologies such as optical computing, quantum computing, and storage-computing integration will gradually mature, driving a revolutionary enhancement in computing power.
8. Data as Intelligence, AgenticAl Drives Change in Storage Paradigms
Core Idea: The development of AI will push data storage from traditional file and object storage to a smarter and more efficient data storage paradigm.
Technical Challenges: How to manage the “memory flow” of agents to achieve efficient data storage, retrieval, and updating.
Future Outlook: By 2035, data storage will focus more on the relevance, state, and evolution of data, promoting the full release of data value.
9. Transitioning from Mobile Internet to Agent Internet, Building Intelligent Interaction Bridges from Physical Space to Digital Space
Core Idea: Future communication networks will evolve from serving “person-to-person communication” to building the next generation of networks for “agent interconnectivity”.
Technical Challenges: How to achieve efficient communication and collaboration among agents, and how to construct new network architectures that support the agent internet.
Future Outlook: By 2035, communication networks will support 10 million connections per square kilometer, with network latency under 100 microseconds, achieving ubiquitous interconnectivity for agents.
10. Token Management Energy Networks, Making Intelligence the “Nervous System” of Energy
Core Idea: AI technology will be deeply integrated into energy networks, achieving efficient distribution and management of energy through token management.
Technical Challenges: How to realize intelligent management and optimization of energy networks, and how to solve the problem of stable power supply from new energy sources.
Future Outlook: By 2035, breakthroughs in new technologies such as controllable nuclear fusion and space-based energy will promote a revolutionary reconstruction of energy systems, achieving absolute abundance in energy.
The “Intelligent World 2035” report provides profound and comprehensive insights into artificial intelligence (AI), covering the current state of AI, future development trends, technical challenges, and impacts on society and the economy.
1. Current Status and Future Trends of AI Technology
Status: AI technology has developed rapidly since the beginning of this century, especially with the emergence of generative AI, marking a new era in technological revolution. Currently, AI applications are mainly focused on AI assistants centered on question-and-answer functions, but these systems are often viewed as “black boxes” with properties that are difficult to fully understand and guarantee.
Future Trends: Over the next decade, AI will develop from perception and generation capabilities to more advanced reasoning and decision-making abilities. The report predicts that AI will gradually realize the transformation from understanding the world to changing the world, particularly driven by embodied intelligence and world models, allowing AI to better interact with the physical world.
2. Applications of AI in Various Fields
Healthcare: AI will push healthcare from “curing diseases” to “comprehensive health management.” Through AI-driven predictive and intervention measures, over 80% of chronic diseases are expected to be effectively prevented. AI will also assist in drug development and the generation of personalized treatment plans.
Education: AI will achieve personalization and intelligence in education. By dynamically analyzing students’ learning progress and knowledge mastery, AI can provide real-time personalized teaching plans for teachers, ensuring that each student receives a tailored learning experience.
Transportation: AI will promote the development of autonomous driving technology, gradually evolving from Level 3 to Level 5. By 2035, most scenarios will achieve Level 4+ autonomous driving, significantly improving transportation efficiency and safety.
Manufacturing: AI will drive the manufacturing industry from “mass standardization” to “mass personalization.” Through embodied intelligence and industrial AI, manufacturing companies will achieve higher production efficiency and product quality.
Finance: AI will reconstruct financial services, shifting from “key user-centered” to “individual user-centered” approaches. Financial agents will provide ultra-personalized financial services for each user.
3. Challenges in AI Technology
Technical Challenges: The development of AI still faces numerous technical challenges, including but not limited to model interpretability, data privacy and security, and algorithmic bias. The report emphasizes that the reliability, safety, and transparency of AI systems are key to future development.
Ethical Challenges: The decision-making logic of AI lacks transparency and interpretability; ensuring that AI’s values align with human values is a core challenge. The report calls for the establishment of a global AI ethics framework to ensure that AI development aligns with human interests and values.
Social Challenges: The rapid development of AI may exacerbate the digital divide and lead to adjustments in employment structures. The report emphasizes that inclusive AI and ethical governance are key to ensuring the sharing of technological benefits and promoting global sustainable development.
4. The Relationship Between AI and Humanity
Human-Machine Collaboration: The report emphasizes that in the future, AI will form a closer collaborative relationship with humans. AI will not only be a tool but also a partner that can help humans better understand and transform the world.
Ethics and Safety: The development of AI must adhere to ethical and safety principles, ensuring that technological advancement aligns with human interests and values. The report calls for the establishment of a global AI ethics framework to ensure that AI development meets human interests and values.
Inclusiveness: The development of AI needs to be inclusive, ensuring that everyone can enjoy the convenience and opportunities brought by AI. The report calls for bridging the digital divide through a dual approach of technology and governance to achieve global sustainable development.
5. Future Vision for AI
Evolution of Agents: AI will evolve from simple execution tools to intelligent agents with autonomous decision-making capabilities, able to autonomously execute various tasks in a closed loop. By 2035, Level 4 guiding agents will be implemented on a large scale in certain fields.
Technological Integration: AI will deeply integrate with technologies such as the Internet of Things, cloud computing, and big data, promoting intelligent transformation across various industries. The report predicts that by 2035, the demand for computing power in society will increase by 100,000 times, and data storage needs will increase by 500 times.
Social Impact: AI will profoundly impact human production methods, lifestyles, and social structures. The report calls for global collaboration to promote the healthy development of AI technology, ensuring that technological advancement aligns with human interests and values.返回搜狐，查看更多
