AI generations: from AI 1.0 to AI 4.0
This paper proposes that Artificial Intelligence (AI) progresses through several overlapping generations: AI 1.0 (Information AI), AI 2.0 (Agentic AI), AI 3.0 (Physical AI), and a speculative AI 4.0 (Conscious AI). Each AI generation is driven by shifting priorities among algorithms, computing power...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-06-01
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| Series: | Frontiers in Artificial Intelligence |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/frai.2025.1585629/full |
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| author | Jiahao Wu Hengxu You Jing Du |
| author_facet | Jiahao Wu Hengxu You Jing Du |
| author_sort | Jiahao Wu |
| collection | DOAJ |
| description | This paper proposes that Artificial Intelligence (AI) progresses through several overlapping generations: AI 1.0 (Information AI), AI 2.0 (Agentic AI), AI 3.0 (Physical AI), and a speculative AI 4.0 (Conscious AI). Each AI generation is driven by shifting priorities among algorithms, computing power, and data. AI 1.0 accompanied breakthroughs in pattern recognition and information processing, fueling advances in computer vision, natural language processing, and recommendation systems. AI 2.0 is built on these foundations through real-time decision-making in digital environments, leveraging reinforcement learning and adaptive planning for agentic AI applications. AI 3.0 extended intelligence into physical contexts, integrating robotics, autonomous vehicles, and sensor-fused control systems to act in uncertain real-world settings. Building on these developments, the proposed AI 4.0 puts forward the bold vision of self-directed AI capable of setting its own goals, orchestrating complex training regimens, and possibly exhibiting elements of machine consciousness. This paper traces the historical foundations of AI across roughly 70 years, mapping how changes in technological bottlenecks from algorithmic innovation to high-performance computing to specialized data have stimulated each generational leap. It further highlights the ongoing synergies among AI 1.0, 2.0, 3.0, and 4.0, and explores the ethical, regulatory, and philosophical challenges that arise when artificial systems approach (or aspire to) human-like autonomy. Ultimately, understanding these evolutions and their interdependencies is pivotal for guiding future research, crafting responsible governance, and ensuring that AI’s transformative potential benefits society. |
| format | Article |
| id | doaj-art-ec97b01ae67b4f588e2f5e86eac72023 |
| institution | Kabale University |
| issn | 2624-8212 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Artificial Intelligence |
| spelling | doaj-art-ec97b01ae67b4f588e2f5e86eac720232025-08-20T03:32:37ZengFrontiers Media S.A.Frontiers in Artificial Intelligence2624-82122025-06-01810.3389/frai.2025.15856291585629AI generations: from AI 1.0 to AI 4.0Jiahao WuHengxu YouJing DuThis paper proposes that Artificial Intelligence (AI) progresses through several overlapping generations: AI 1.0 (Information AI), AI 2.0 (Agentic AI), AI 3.0 (Physical AI), and a speculative AI 4.0 (Conscious AI). Each AI generation is driven by shifting priorities among algorithms, computing power, and data. AI 1.0 accompanied breakthroughs in pattern recognition and information processing, fueling advances in computer vision, natural language processing, and recommendation systems. AI 2.0 is built on these foundations through real-time decision-making in digital environments, leveraging reinforcement learning and adaptive planning for agentic AI applications. AI 3.0 extended intelligence into physical contexts, integrating robotics, autonomous vehicles, and sensor-fused control systems to act in uncertain real-world settings. Building on these developments, the proposed AI 4.0 puts forward the bold vision of self-directed AI capable of setting its own goals, orchestrating complex training regimens, and possibly exhibiting elements of machine consciousness. This paper traces the historical foundations of AI across roughly 70 years, mapping how changes in technological bottlenecks from algorithmic innovation to high-performance computing to specialized data have stimulated each generational leap. It further highlights the ongoing synergies among AI 1.0, 2.0, 3.0, and 4.0, and explores the ethical, regulatory, and philosophical challenges that arise when artificial systems approach (or aspire to) human-like autonomy. Ultimately, understanding these evolutions and their interdependencies is pivotal for guiding future research, crafting responsible governance, and ensuring that AI’s transformative potential benefits society.https://www.frontiersin.org/articles/10.3389/frai.2025.1585629/fullartificial intelligence evolutionmachine learningreinforcement learninglarge language modelsAI ethics and governance |
| spellingShingle | Jiahao Wu Hengxu You Jing Du AI generations: from AI 1.0 to AI 4.0 Frontiers in Artificial Intelligence artificial intelligence evolution machine learning reinforcement learning large language models AI ethics and governance |
| title | AI generations: from AI 1.0 to AI 4.0 |
| title_full | AI generations: from AI 1.0 to AI 4.0 |
| title_fullStr | AI generations: from AI 1.0 to AI 4.0 |
| title_full_unstemmed | AI generations: from AI 1.0 to AI 4.0 |
| title_short | AI generations: from AI 1.0 to AI 4.0 |
| title_sort | ai generations from ai 1 0 to ai 4 0 |
| topic | artificial intelligence evolution machine learning reinforcement learning large language models AI ethics and governance |
| url | https://www.frontiersin.org/articles/10.3389/frai.2025.1585629/full |
| work_keys_str_mv | AT jiahaowu aigenerationsfromai10toai40 AT hengxuyou aigenerationsfromai10toai40 AT jingdu aigenerationsfromai10toai40 |