From science-fiction movies to reality, artificial intelligence (AI) has evolved. Scientists have been trying for decades to discover ways to incorporate intelligence in industries, leading to the development of machine learning and deep learning algorithms that enable machines to learn from their experiences.
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Now, since machine learning algorithms (ML) have become more mature and understanding of their applicability has increased, scientists are keen on incorporating intelligence in robotics.
Intelligence in Robots
Although there are many restrictions of artificial intelligence across various sectors, intelligence and automation have a significant impact and applications in robotics. Intelligence in robots is defined as the capability of a robot to learn from its experience, make reasonable decisions as per the conditions, and have the ability to reason.
Artificial intelligence is used in robots to make them intelligent so that they learn from their experience and improve their decision-making ability. Intelligent robots are programmed with machine learning algorithms that help them carry out the intended task optimally.
The ultimate goal of AI is to make robots with human-like intelligence. Although scientists are nowhere near achieving this milestone, they have made remarkable progress.
Classification of Artificial Intelligence
Artificial intelligence is divided into artificial narrow intelligence, artificial general intelligence, and artificial superintelligence. Artificial narrow intelligence is the level of AI that scientists have already achieved, and artificial general intelligence and superintelligence are what they hope to achieve.
Artificial general intelligence aims to meet human capabilities, while artificial superintelligence aims to surpass human capabilities. This article will focus on artificial general intelligence, its significance, progress, and applications.
Many research and industrial constraints have been surpassed with the discovery of deep learning and machine learning algorithms. The existing machine learning algorithms have enabled scientists to develop many systems that can interact with humans and the surrounding environment, such as self-driving cars.
The real challenge of AI has always been to understand how natural intelligence (NI) works. Now, since fast and efficient computers exist, the working principle of natural intelligence is a large focus.
What is Artificial General Intelligence?
Artificial General Intelligence (AGI) aims to complete tasks that a human can achieve. While humans are likely to be able to do a broader range of duties than technologies equipped with AGI, these systems may accomplish them more efficiently.
Currently, AGI does not exist from a technological standpoint.
A British computer scientist, Stuart Russel, has stated that there are many breakthroughs that must happen before reaching the level of AGI. According to him, the key difference between humans and machines is their ability to understand the content of the language and express it. Humans are capable of doing it while machines are not yet. If machines reach this level of understanding, they would be able to read and understand everything the humanity has ever written.
Although scientists have not reached the level of AGI, robots like Sophia, whose neural networks can be upgraded, indicate an AGI-robot future.
Requirements of AGI
There are a wide number of characteristics that AGI systems must incorporate to function. Since the main aim of AGI is to reach human intelligence and emotional levels, certain characteristics must be incorperated. These include the ability to effectively use and represent metacognitive knowledge, learn from different opportunities, and utilize method-specific knowledge efficiently.
Future of Artificial General Intelligence
Numerous challenges associated with AGI limit its establishment, such as modeling the human brain - it is difficult to model all the interconnections of millions of neurons.
While widespread AGI in robotics is likely to take decades to accomplish, achievements in the field of AI are helping to shorten this timeframe. Sectors like medicine, the manufacturing industry and climate change analysis have already benefitted from artificial intelligence techniques; with increased implementation, a rise in interest and breakthrough developments are sure to follow.
Continue reading: Artificial Intelligence Enhanced Atomic Force Microscopy
References and Further Reading
Ferguson, M. (2021) What is “Artificial General Intelligence”? Available at: https://towardsdatascience.com/what-is-artificial-general-intelligence-4b2a4ab31180.
Heath, N. (2018) What is artificial general intelligence? Available at: https://www.zdnet.com/article/what-is-artificial-general-intelligence/.
Heaven, W. D. (2020) Artificial general intelligence: Are we close, and does it even make sense to try? Available at:
https://www.technologyreview.com/2020/10/15/1010461/artificial-general-intelligence-robots-ai-agi-deepmind-google-openai/.
Ranjitha, S (2021) What is Artificial General Intelligence? Available at: https://www.mygreatlearning.com/blog/artificial-general-intelligence/.
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