While dealing with AI, we come across two concepts — generative AI and Artificial General Intelligence (AGI). Both the concepts are revolutionary enough to transform the world, but both are different.
Generative AI is used to generate content. It is akin to a parrot repeating the human language. It understands the complex patterns of language and predicts the next word so as to create content. It does not understand language like a parrot. While dealing with images, it predicts the next stroke.
A poet draws on his emotional reservoir to compose a poem. Generative AI depends on its vast database. Its writing is more mechanical than emotive. Generative AI is good at commercial work, economics and summarization. It fails to grasp complex human experiences and cannot perform those tasks for which it has not been trained.
AGI is a big theoretical leap. Here a machine goes beyond tasks. It understands and initiates cognitive abilities of a human being. It can innovate and adapt. AGI can make a machine drive a car or do a medical diagnosis. Here the human tasks are replicated by understanding the context.
AGI still remains chimerical. It does not exist right now. There is a lot of speculation about it. Some experts see AGI looming large over our shoulders. Some think is a distant dream.
There are insurmountable technical hurdles in achieving AGI. There are issues of context and generalization. AGI has to be intuitive. It should grasp how different pieces of information relate to each other. It is not just processing power that you need. You also need artificial cognition. There should be connection of different disparate ideas and experiences.
Human beings have sensory perception. They interact with the physical world. AGI will have to perceive environment. There should be recognition of things in the environment. The whole thing builds a context.
Even with little information and data, AGI must adapt to different situations. It is called transfer learning.
Current models just regurgitate information learnt. They do not go beyond their programming. There is a limitation to the capability of generative AI models.
Generative AI has no real understanding but depends on algorithms and statistics. By contrast, AGI will have to develop understanding of the world around it.
Generative AI is applied to raise productivity and generate content. AGI, as and when realized, will transform the world by autonomously working for tasks. AGI would be able to reason, learn and understand complex concepts just like humans.
Super AI refers to AI that surpasses human intelligence. It will solve complex problems beyond human capabilities. It would learn and adapt at a rate faster than human intelligence. It is still a hypothetical concept. It is the ultimate goal of AI research.
GPT-4 does not possess self-awareness or introspection abilities, which are essential components of AGI. AGI deals with consciousness and sentience. AGI is able to learn new skills and knowledge on its own just like a human (without explicit programming).
GPT-5 is likely to go as close to AGI as we have ever been. OpenAI has been showcasing demos of GPT-5 to some enterprise customers.
AGI could revolutionize many industries and solve complex problems in medicine, climate change and exploration.