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AI generations: from AI 1.0 to AI 4.0.

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Artificial Intelligence (AI) evolves through four generations: Information AI, Agentic AI, Physical AI, and speculative Conscious AI. Each stage is driven by advancements in algorithms, computing power, and data, shaping AI

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Robotics
  • Machine Learning
  • Philosophy of Technology

Background:

  • Artificial Intelligence (AI) has progressed through distinct developmental phases over approximately 70 years.
  • Key technological bottlenecks, including algorithmic innovation, computing power, and data availability, have driven AI's generational leaps.
  • Understanding AI's historical trajectory is crucial for navigating its future development and societal impact.

Purpose of the Study:

  • To propose a generational framework for Artificial Intelligence (AI) evolution: AI 1.0 (Information AI), AI 2.0 (Agentic AI), AI 3.0 (Physical AI), and AI 4.0 (Conscious AI).
  • To analyze the interplay of algorithms, computing power, and data in driving each AI generation.
  • To explore the ethical, regulatory, and philosophical implications of advancing AI autonomy.

Main Methods:

  • Historical analysis of AI development over seven decades.
  • Mapping technological bottlenecks and their impact on AI generational shifts.
  • Conceptualization of a four-generation AI model, including speculative AI 4.0.

Main Results:

  • AI 1.0 focused on pattern recognition and information processing (e.g., computer vision, NLP).
  • AI 2.0 emphasizes real-time decision-making in digital environments using reinforcement learning.
  • AI 3.0 integrates AI into the physical world via robotics and autonomous systems.
  • AI 4.0 envisions self-directed AI with goal-setting capabilities and potential machine consciousness.

Conclusions:

  • AI's progression is characterized by overlapping generations, each building upon the last.
  • Synergies among AI generations (1.0, 2.0, 3.0, 4.0) are critical for continued advancement.
  • Addressing the ethical and societal challenges of increasingly autonomous AI is paramount for responsible development and societal benefit.