Stages of AI (ANI, AGI, ASI)
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- Overview
The modern project to create human-like artificial intelligence (AI) began after World War II, when it was discovered that electronic computers were not only number-crunching machines, but could also manipulate symbols. This can also be achieved without assuming that machine intelligence is the same as human intelligence.
Artificial intelligence (AI) has been named the most widely mentioned technology in recent times, according to a recent study by technology analyst Gartner. Most CIOs agree that AI has the greatest paradigm-shifting power. According to most predictions, AI should occupy the center stage of most human endeavors in the next few years.
But AI is far from a static technology with a fixed set of principles. In addition to providing the core value of mimicking human intelligence and reasoning to get work done faster, faster, and better, AI continues to evolve over time, becoming more capable and richer. This is called weak AI.
However, the goal pursued by many AI researchers is to develop AI that is in principle the same as human intelligence, called strong AI. Weak AIs are less ambitious than strong AIs and therefore less controversial. However, there are also important controversies associated with weak AI.
- Three Types (Stages) of AI - Based on Capabilities
There are various ways to create AI, depending on what we want to achieve with it and how we will measure its success. It ranges from extremely rare and complex systems, such as self-driving cars and robotics, to parts of our everyday lives, such as facial recognition, machine translation, and email categorization. The path you choose will depend on what your AI goals are and how well you understand the intricacies and feasibility of various approaches.
AI technologies are categorized according to their ability to mimic human traits, the techniques they use to do so, their real-world applications, and theory of mind. Using these characteristics as a reference, all AI systems — real and hypothetical — fall into one of three categories:
- Narrow artificial intelligence (ANI), with a narrow range of capabilities;
- Artificial General Intelligence (AGI) comparable to human capabilities; or
- Artificial Superintelligence (ASI), more capable than humans.
Today, we have three different variants of AI technology; ANI, AGI, and ASI. These are the three stages in which AI can evolve. We have only achieved narrow AI so far.
As machine learning capabilities continue to develop and scientists move closer to achieving AGI. Theories and speculation about the future of AI are circulating. ASI is a futuristic idea about the ability of artificial intelligence to replace human intelligence. For ASI to become a reality, computational programs must surpass human intelligence in all parameters and environments.
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- Artificial Narrow Intelligence (ANI)
In contrast to strong AI, which can learn to perform any task humans do, weak AI (or narrow AI) is limited to one or a few specific tasks. This is the kind of artificial intelligence we currently have. In fact, deep learning, named after the human brain (and often compared to it), has very limited capabilities and is nowhere near what a human child's brain can do. This is not a bad thing.
In fact, narrow AI can focus on specific tasks and do it better than humans. For example, feed a deep learning algorithm enough pictures of skin cancer and it will be better at spotting skin cancer than an experienced doctor. This does not mean that deep learning will replace doctors. You need intuition, abstract thinking, and more skills to decide what is best for your patients. But deep learning algorithms are sure to help doctors do their jobs better and faster, and care for more patients in less time. It will also reduce the time required to educate and train healthcare industry professionals.
- Artificial General Intelligence (AGI)
General AI (AGI) is only theoretical at this point. This is the AI that writers have made up for years in sci-fi stories. Ultimately, when we achieve AGI, machines will have consciousness and decision-making capabilities - full human cognitive abilities. These machines do not require human input to be programmed to function. For all intents and purposes, this will be a time when machines act, feel, respond and think like humans. We can say that a powerful AI has a mind of its own and is capable of doing whatever it wants to do like any human being. Unlike narrow AI, which classifies data and finds patterns, general AI uses clustering and association when processing data. AGI will also be self-aware. However, like a child, AI must learn through experience, improving knowledge and skills over time.
But while all of this talent is focused on finding a way to create a powerful AI that can compete with the human brain, we are missing a lot of opportunities and failing to address the threats posed by current weak AI technologies. Some commentators have argued that weak AI could become dangerous because of this "fragility" and fail in unpredictable ways. Weak AI could disrupt power grids, damage nuclear power plants, cause global economic problems, and mislead self-driving cars. In 2010, a weak AI trading algorithm caused a "flash crash" that caused a temporary but significant drop in the market.
- Artificial Super Intelligence (ASI)
ASI is a futuristic concept and idea of artificial intelligence replacing human intelligence capabilities. For ASI to become a reality, computational programs must surpass human intelligence in all parameters and environments. ASI will only become a reality when AI becomes smarter than humans.
ASI with a futuristic halo seems far removed from the future of human evolution, in the sense that this so-called perceptual AI variant shows the conceptual limits of AI technology and its promises that it won't deliver, at least in become a reality decades later.
If ASI becomes possible and becomes a reality, the role of humans in decision-making, the arts and humanities, and emotional understanding of all aspects of life could be at odds with the rise of machines.
