Artificial General Intelligence: When will we Really Achieve it?

AI researchers are eager to leverage artificial general intelligence in the future

The world is changing at a fast pace and almost the entire credit goes to artificial intelligence. AI has penetrated our professional and personal lives in such a way that it becomes inherent for us to need more innovative and automated solutions for our daily activities. Advanced technologies like AI and machine learning have their own disadvantages and banes, including the potential for bias, exploitation, and such other misuses, nonetheless, it has opened unprecedented ways of approaching every facet of business and our daily lives. Researchers and scientists are relentlessly striving to mitigate all technological constraints and innovate new branches of artificial intelligence to seamlessly automate processes.

One such innovative branch of AI is artificial general intelligence (AGI). The primary functions of artificial general intelligence are to make artificial systems fully capable, train them to experience, adjust to new things, and perform human-like tasks efficiently. AGI offers more accuracy in imitating human tasks than any other technology. These systems can even perform tasks with greater efficiency than humans when the particular tasks are assigned to them beforehand. To simply put, AGI is a machine with general intelligence much like a human being, to solve any problem.

The Present State of Artificial General Intelligence

Currently, the industry possesses the tools to create AI systems that display remarkable levels of understanding. Some existing programs show much resemblance to human-level reasoning, performance, and control on specific tasks. Integrating AGI into advanced tech systems will enable them to combine human-like flexibility, and reasoning with computational advantages, such as near-instant recall and split second-number crunching.

Furthermore, using this intelligence to control robots that are at least as dextrous and mobile as a person would result in a new breed of machines that can perform any task. Over time, these intelligence would be able to take over almost every role performed by humans. Certain experts believe that such rapid advancements in AGI could have two extreme conditions. Either it could make humans cheaper than machines, or, enable them to become more efficient with such advanced AI systems alongside them. But it is for sure that the advent of such systems could make human labour obsolete.

Artificial general intelligence also aids in several real-world industrial use cases. Scientists from large tech organisations are contributing to tackling climate change while developing what is required to build AGI for weather prediction and plasma control for fusion, which is a single source of clean and sustainable energy. Also, these models can help meteorologists provide forecast and aid decision-making for emergency services, energy management, and activation of flood warning systems, enabling better preparation and responses for extreme weather conditions. AGI systems can make more intelligent systems for advanced decision-making.

The Challenges faced by AGI in Real-World Scenarios 

While AGI may not have been realised so far, it does promise a world full of possibilities. But currently, the technology is facing several roadblocks.

Besides responding to the effects of climate change, it is also crucial to sort out the resources from which these data are generated by scientists and researchers. The lack of a working protocol with such advanced artificial intelligence or machine learning networking is critical. This deficiency coerces systems to work as standalone models in a closed environment. Also, the communication gaps come in the way of seamless data sharing and the inter-learning of machine learning models. Organisational executives are now in the dark to integrate AI with their business operations to drive specific results. The lack of direction followed by the fact that only a limited number of people possess the required skills to handle AGI machines makes the deployment of such systems quite costly.

Moreover, without expert collaboration. AI researchers cannot make significant progress in real-world domains. Identifying the right paths in this field requires accurate and meaningful partnerships across all disciplines. This will help develop a common scientific approach to use and navigate AI during society's most urgent needs.