Human Brain Has Edge Over Artificial Intelligence - Web Inter Secure

 The combat of artificial intelligence with humans started the same day when it defeated a human in a chess game. The combat took the people into shock when the Wachowski brothers created the Matrix series. However, such things are not going to happen soon. AI has shown the power to enhance its capacity-building measures to bring improvisation at every stage. With the overall volume of datasets, AI changes its model from time to time to give better predictions and forecasts about any events or actions. Thus, AI is highly sophisticated in terms of manipulations and somewhere makes it stand apart from humans. But, the recent study about AI and humans has revealed unique information on human memory and how it is superior to the artificial intelligence models and algorithms. Let’s dig out more information on this issue and understand the factors that led to this conclusion. 

Latest Development

Published in the journal named, Physical Review Letters, the novel research stated that the brain has a better strategy to store data, facts, and information. Hence, the brain is more efficient than artificial intelligence algorithms. The scientists and researchers from SISSA (Scuola Internazionale Superiore di Studi Avanzati) and Kavli Institute for Systems Neuroscience & Centre for Neural Computation collaborated to conduct this research. In the study, there are observations that the brain has a different approach to remember facts and information. This approach is quite different from the methodology adopted by AI algorithms. The human brain tries to retrieve these data that might not be identical to the original input. The brain does it by silencing the activities of barely active neurons. Opposite to this, AI somewhere uses the retrieval of data sets and reverse engineering techniques.

Retaining Data

There is a network of neurons that helps the human to store all information in the brain. This neural network is also present in the artificial intelligence that has got a virtual digital memory to keep the same information, but, differently. AI uses its complex and lengthy algorithms that uses iterative tuning and optimization of neural network. However, the brain has more straightforward methods, i.e., reading the status of two active neurons and their connection simultaneously. So, in comparison to the AI model and algorithm, the brain permits significantly less storage to retain the same amount of memory that AI needs. Hence, the research provides insights about biological arrangement and assemblage of self-organized learning procedures and methods in a nutshell. This study shows the brain’s efficiency and the complexity of neural implausible training algorithms that let the AI model lag behind.

Inferences from Study

One can extract many inferences from this study. Firstly, it shows that there is a requirement for more efficient models at the machine learning level. It will help to store more information in less storage space. Thus, the information density in digital storage can increase to a great extent. Secondly, there is a long journey that AI has to travel to beat humans in memory. Games like chess are some dedicated horizons around which AI got more space and enhanced skills to defeat humans. Recently, DeepMind has developed more artificial intelligence models where it devised the strategy to learn the game without even knowing the rules. Hence, there is a need in terms of improvisation and enhancing the training models to other domains where it lags.

Conclusion

The study has revealed facts that are not trivial and holds enormous importance. It shows that human is a better figure even in recent times, and if artificial intelligence wants to defeat humans, it has to go far to adopt more advanced techniques and methodologies. Artificial intelligence will attain many small achievements with more advancement to get an edge over the human brain. At present, it has dedicated and targeted delivery and niche in some domains where it is performing with great pace. The model development and its collaboration with digital storage will build better strategies and approaches to retain the data, retrieve the same more efficiently, and perform better actions. So, both the factors (discussed as inferences) are in co-relation.

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