Today we are here to give you some information regarding artificial neural networks. Today, the artificial neural network is an integrated part of our personal and work life. Right now, artificial neural networks are still young. But already they are one of the most impressive technologies. It indicates that they have a bright future in the next few decades.
Now, most of the users want to know about the future of the artificial neural network. So, here we will explain everything you want to know about artificial neural networks.
Present Performance of Artificial Neural Network
The artificial neural network is becoming advance exponentially. We can only see a brighter future with augmented reality, machine learning, artificial intelligence, and big data. Back in 1943, Warren McCulloch and W.
Pitts enlightened the first candle of ANN. Since then, their successors have developed artificial neural networks a lot. They are combining ANN with other technologies to make it more useful. Let’s discuss some of the practical uses of ANN.
These are the classic example of an artificial neural network. Chatbots are widely used in customer support to give answers. All major organizations are using chatbots for customer support. Before the use of chatbots, companies had to hire a room full of people for this job.
Now, the entire process is automated, provides complete customer satisfaction without human intervention. All the major brands are using chatbots in their social media and customer help page.
2. Virtual Assistance
Virtual assistances like Siri, Google Assistance, and Cortana can mimic human conversation to perform a task. They can perform simple tasks like cab booking, setting reminders, weather updates, and playing music.
3. Other Uses of Neural Network
Artificial neural networks are used in online retail to predict demand. ANN, combined with machine learning, predicts future demand from past purchases and checking.
Navigation services use an ANN to provide the easiest route to the users. ANN also uses GPS technology is effective to suggest the safest and time-saving route.
Application of artificial neural network includes the prediction of an upcoming earthquake. Based on the existing seismogram reading and soil study, the ANN makes predictions.
Key Strengths of Neural Network
There are some key strengths of artificial neural network that makes it the most favourite choice. Some of those are as follows:
1. Performance on Problems with Many Variables
The task is easy to perform when a machine is getting a limited number of inputs with strict rules. A perfect example of this is the calculator. The rules of mathematics are the same every time. You will get your answer when you input the numbers. But tasks like speech patterns identification or illness diagnosis requires much more variables.
The machine needs to understand so many things. The machine should understand what they are looking for and how it is different from the noise. They should also determine the way to influence the noise. ANNs are undoubtedly perfect in this task, even better than humans.
2. Feature Engineering
ANN perform incredibly to figure out the correct features to describe a problem. This is feature engineering. Let’s understand this with an example. ‘GO’ is a game where you can move; however, you want to.
There is no clear way to determine a move is ‘good’ or ‘bad’. As there are endless possibilities, the machine has to learn endless things too. When you want to teach a machine to play this like Google, ANN is an obvious choice.
Artificial neural networks can make them flexible. So, users can use them to solve almost all the problems. AI experts are using artificial neural networks to solve production issues and to improve air traffic patterns for smoother flights.
Future of Artificial Neural Network
AI experts and data scientists have realized the true potential of artificial neural networks. This is the reason why all of the major companies are spending their fund on ANN. Also, ANN, along with machine learning, are capable of solving almost all complex problems. Let’s look at the future of artificial neural networks.
Along with so many positive outcomes, ANN has some drawbacks too. But there are rays of hope. AI experts have claimed that the collaboration of ANN with other technologies can solve this. But here is an issue.
Compensatory technology has to work the same as an artificial neural network. AI engineers are working on it to find a way to make them work together. We can expect some advanced technology in the upcoming years.
2. Sheer Complexity
Artificial neural networks are already capable of handling complex problems. As we have mentioned earlier, it’s still in a premature stage. So we are expecting more development in terms of power and complexity.
Engineers are working on the design to process more data at a faster speed. There is a maximum limit of data processing, but we haven’t reached that limit. So, we are going to see a massive jump in speed and quantity of data processing.
3. New Application
Besides the vertical advancement, i.e., faster and more data processing, ANN can expand horizontally. Users can apply the ANN in more diverse applications.
Right now, industries from almost all the fields are using this technology. AI experts have also claimed a massive hike in this number. Industries will use ANN to develop new products and target a new audience.
4. Health Sector
Use of artificial neural networks in the healthcare sector is still in trial. Experts in this field have claimed that artificial intelligence can be used to diagnose diseases.
ECG reading, the suggestion of treatment is the other capabilities of ANN. Even some of the experts have suggested that artificial intelligence can discover new drugs too. However, all of these are still a matter of research.
So, we have explained all the present activities with future possibilities of ANN. We can already see the enlightened opportunities of ANN in the mirror of the future. This is the time to jump in the field of artificial neural networks.