Human Brain Vs. Neural Networks? Imagination or Science?

Neural networks are among the most advanced technologies that have caught every tech freak's attention. Neural networks are used in different fields and industries, including the stock market, social media, healthcare, defense, aerospace, etc. It has dramatically impacted all these fields, and now with the power of AI and neural networks, many tasks have become easier and efficient. 

On the other hand, the human brain is everywhere. Not a single industry is exempt from its range. It is the most significant factor that helped them survive.Although both of these complicated systems are similar in many ways, they have their functioning and ways of interpreting data and finding solutions. This blog post will explore the topic in-depth to help readers understand these two magnificent systems and see how they can utilize them perfectly.

How does the Brain Process Information?

The network of neurons in our brain continuously communicates with each other to process information. Apart from the neuron networks, the brain also uses sensory registers to receive and further process data.

When the brain receives information through the sensory register, it sends it to the thalamus, which uses our past experiences to analyze its importance. If the data is of no value, it filters it out and doesn't give signals to neuron networks to pass the information. This process is called sensory filtering.

Once the information reaches the human brain, it then sends it to different regions, depending on the type of information. The occipital lobe processes the information, including the colors, distance, patterns, etc. Then different brain regions work together to give that information they also use the individual's cognitive processes, including memory, attention, perception, and language. 

AI Neural Networks

AI neural networks work in a similar way to human neurons. However, they are different in some ways. AI experts have made neural networks very similar to the human brain as they know its power and capabilities. 

The AI neural networks are the combination of numerous interconnected neurons that are combined in a layered structure like the human brain. Each neuron has its unique function, and it only performs the task for which it is designed. 

When a neural network receives information, all the neurons start to interpret data. Once each neuron does its task, the neural networks combine the data and produce results accordingly. Neural networks assist computers in executing various tasks, including solving problems, analyzing pictures, recognizing faces and patterns, etc. 

The neural networks are divided into three main types of layers, including an input layer, various hidden layers, and an output layer. The input layers take the data from the outer world or commands, hidden layers process them, and the output layers show results to users or computers.

Comparison Between Human Brain and Neural Networks

The human brain and neural networks share a lot of common things. However, at the same time, they are different in many other ways.

Here are a few similarities between these two systems:

Similarities

Learn and Adapt Information

Both systems are designed to learn and adapt new information without hassle. The human brain can adjust its neuron connections based on new experiences and learnings. The same applies to neural networks, where the input data can help them learn and adapt to new information.

Distributed Representation

The human brains have different regions to store and process information; the data isn't stored in a single location. Each neuron in the brain has a different job, and it doesn't perform the duty that isn't assigned to it. Similarly, neural networks have a layered structure where each layer has a different function. Moreover, the multiple neurons in the hidden layers are also designed to process a single type of data. 

Multi-Tasking

The neural networks and human brains of both of these systems can perform various duties simultaneously. For example, humans can speak on a topic and control their hand movements at the same time. In the case of neural networks, they can also be trained to execute different duties simultaneously using different inputs.

Differences

Complexity

Human brains are more complicated than neural networks. They have more neuron networks, layers, functions, and duties they perform. On the other hand, neural networks are also very complicated but they are still less complicated than human brains.

Functionality

The human brain can perform unlimited tasks and have more emotions than neural networks. Moreover, human brains can also be trained within a few seconds to perform new tasks. In comparison, neural networks have a limited number of functions that are controlled by commands.

Generate New Ideas

Here is the most crucial difference between human brains and neural networks. Based on experiences and cognitive abilities, the brain can generate new ideas, concepts, and words. On the contrary, neural networks cannot do as they depend solely on the data provided by external sources.

Applications of the Human Brain

Decision Making

Decision-making is an application of the human brain that enables humans to learn what is better for them and what isn't. They process various data types and choose the most appropriate course of action. This is one of the most crucial abilities of brains that help human brains to survive in difficult situations.

Problem-Solving

Problem-solving is another great application of the human brain. The brains utilize memory and learning from past experiences to come up with results whenever they are in difficult situations. The problem-solving ability of the human brain has helped humans come up with different ideas to solve issues.

Creativity

The applications of the human brain are broader than neural networks. The human brain's biggest benefit is that it can generate new ideas and concepts. Inventions, innovations, and technology are all products of the human mind. 

Applications of Neural Networks

Analyze Images

The neural networks can analyze and interpret information presented in digital form. This visual processing ability enables them to explore every element shown in an image and respond accordingly. The reverse image search uses this technology to provide accurate data to users against their queries.

Speech Recognition

AI-powered speech recognition tools like text to speech are also developed to assist people. They are programmed to convert written words into audio by using different algorithms. The speech recognition tools created with the help of neural networks can enhance productivity and enable users to perform various functions.

Natural Language Processing

The tools like ChatGPT, Jasper, and AI Writer are used with the help of neural networks. The neural networks enable systems to create human-like content and responses against various types of inputs. These tools and systems have multiple benefits; they can create emails, write assignments, craft marketing copy, etc.