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Listen "The Next AI Evolution: From Text Generation to Reflective, Self-Improving AI"
Episode Synopsis
Medium Article: https://medium.com/p/c7170ef22460/edit
This article discusses the evolution of AI from simple text generators to more advanced, self-improving systems. It identifies three phases: the era of text generators (2023-2024), the rise of Agentic AI (2024-2025) with thinking tokens and multi-agent systems, and the future of Neuro-Agentic AI (2026+), which emphasizes reflective intelligence and continuous learning. The piece argues that AI's future lies in modular, domain-specific agents that can reason, remember, and refine their decision-making processes. It contrasts current limitations of models like ChatGPT with the potential of future AI systems that act as strategic advisors, offering examples across law, science, and business. The author encourages organizations to invest in memory-driven and self-improving AI or risk being left behind.
This article discusses the evolution of AI from simple text generators to more advanced, self-improving systems. It identifies three phases: the era of text generators (2023-2024), the rise of Agentic AI (2024-2025) with thinking tokens and multi-agent systems, and the future of Neuro-Agentic AI (2026+), which emphasizes reflective intelligence and continuous learning. The piece argues that AI's future lies in modular, domain-specific agents that can reason, remember, and refine their decision-making processes. It contrasts current limitations of models like ChatGPT with the potential of future AI systems that act as strategic advisors, offering examples across law, science, and business. The author encourages organizations to invest in memory-driven and self-improving AI or risk being left behind.
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