Generative AI – On the Path to Artificial General Intelligence
Published on : Friday 04-08-2023
Dhiraj Sharma explores the concept of Generative AI and its role as a precursor to AGI.
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Artificial Intelligence (AI) has evolved significantly over the years, progressing from Artificial Narrow Intelligence (ANI) to Generative AI, which can be considered as an early step towards achieving Artificial General Intelligence (AGI). While ANI focuses on performing specific tasks with limited capabilities, Generative AI aims to generate new content, learn from it, and potentially pave the way for AGI, which encompasses human-like intelligence across various domains.
Understanding Artificial Narrow Intelligence (ANI)
Artificial Narrow Intelligence refers to AI systems that are designed for specific, repetitive tasks defined by human operators. These systems excel in performing well-defined tasks, such as image recognition, natural language processing, and speech recognition. ANI models undergo supervised or unsupervised learning, based largely on structured data to produce results within their designated domain. However, they lack the ability to solve problems beyond their predefined scope.
The Emergence of Generative AI
Generative AI represents a significant leap forward in the field of AI, as it focuses on generating new content rather than simply recognising patterns or performing predefined tasks. Generative models, such as Generative Adversarial Networks (GANs) and Variational AutoEncoders (VAEs), have gained prominence in this domain. These models can create new images, text, audio, and even whole new interactive experiences by learning from vast amounts of training data which is primarily unlabeled.
Generative AI combines deep learning techniques with probabilistic models to generate outputs that mimic the characteristics of the training data. This technology enables machines to go beyond the limitations of ANI and produce novel content based on patterns and relationships learned from the training data. Generative AI has found applications in various industry verticals, including technology services, BFSI, media and entertainment, advertising, and healthcare among others.
Generative AI as a step towards AGI
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While Generative AI represents a significant advancement in the field of AI, it is important to understand that it is not synonymous with AGI. AGI refers to the development of machines capable of defining tasks, pathways to task completion, and carrying out self-correction comparable to human cognition. Generative AI can be seen as an early step towards AGI as generative AI demonstrates the potential for machines to exhibit self-awareness, common sense, creativity, and ability to express emotions, which are crucial elements of AGI. However, AGI involves a much broader range of capabilities, including self-selected learning, near-human or even beyond-human generalisation capabilities across a variety of inputs, and massively parallel real-world data processing, which are yet to be achieved.
Generative AI marks a significant milestone in the progression towards achieving Artificial General Intelligence. By enabling machines to generate new content and learn from vast amounts of data, Generative AI showcases the potential for machines to exhibit creative thinking and adaptability. While AGI remains a long-term goal, Generative AI serves as an important building block in the evolution of AI systems. Continued research and advancements in Generative AI, coupled with advancements in other areas of AI, will contribute to the eventual development of AGI, leading us closer to a future where machines possess human-like or beyond-human intelligence across a multitude of domains.
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Dhiraj Sharma is Principal Analyst at NASSCOM.
Article Courtesy: NASSCOM Community – an open knowledge sharing platform for the Indian technology industry: https://community.nasscom.in/communities/digital-transformation/generative-ai-path-artificial-general-intelligence