Technology is advancing far faster than we have the time to understand it and make everything clear for us. It is a known fact that we can largely benefit from this digital era, and if you utilize the best platforms along with the current software, you can easily take your business to the next level.
Deep learning is one of the latest advancements in technology, but it is also something that can be relatively difficult to understand, especially if you don’t have the needed knowledge and experience in that industry. If you’ve been wondering what it is, and if you want to understand it without having to go through difficult words, and confusing phrases, you’ve come to the right place. In this article, we are going to help you get acquainted with this process, and we will try to do it in the easiest way possible.
Continue reading if you want to learn more about this tech, understand it with simple words, and see how you can benefit from it.
The first thing we are going to talk about is what type of technology is this, and why do we want to implement it in our day-to-day lives.
By definition, this is a process where artificial intelligence is used to analyze data, and based on it, draw business-related conclusions. It uses representative examples, instead of the traditional task-specific ones, and it is usually semi-supervised, or unsupervised. The machine analyzes large quantities of data and based on that, it draws conclusions and sends a detailed report on predictions, errors, and probable outcomes.
Artificial intelligence acts like a human, and it is able to learn constantly if it is given access to data. Because of this, the machines need to be constantly online, so they can do their process uninterrupted. Unlike traditional machine learning, the DL can process far higher loads of data, but it needs more time to process and go through everything.
There are three main types of DL and include artificial neural networks (ANN), recurrent neural networks (RNN), and convolutional neural networks (CNN). It is said that these processes are changing the world as we know it, and they are making their impact in many different industries. They help not only process and understand data, but also make well-rounded decisions based on research and facts.
Know that there are many industries where this technology can be utilized, and some of them include autonomous vehicles, speech recognition, and even the aerial industry. They can be utilized pretty much everywhere, but since they are extremely complex and deep, they are rarely incorporated in smaller companies and businesses that don’t require the analysis of large volumes of data.
For more information about DL and neural networks, check the post: https://serokell.io/blog/deep-learning-and-neural-network-guide.
Now that you know more about the concept, let’s look at some of the good and bad things that could come from implementing it in your workspace.
Let’s first talk about the advantages of this process, and how affects not only individual companies, but also the overall economy. It is said that this technology had a great impact on the financial status of the world and that in 2017, this industry was worth almost 2.5 billion dollars, and the expectations are that it will reach almost 20 billion dollars by 2023. It is growing faster than any other industry, and the predictions are that this is extremely worth investing in and learning it.
The biggest positive side that comes from this machine learning is that you can create unique features depending on your needs as an owner. The analysis can also help you avoid issues, detect them, as well as learn from the past. Data researchers can implement this technology into many different aspects of their jobs, and create solutions for problems that could arise. This will help prevent serious mishaps, and it will just provide a better understanding of the whole process.
Another advantage that comes from deep learning is the analytical process. When we analyze data, we can create fact-based predictions, and we can easily make the right decision. Since the system supports unlabeled data, it can advance on its own, it can learn and it will help you advance in your field of business.
Now let’s talk about some of the disadvantages, or challenges that come with this practice, and how they may prove they are not as amazing as we currently perceive them.
The biggest problem that might arise is the fact that this technology needs a lot of data to be able to learn, and that data needs to be constantly updated. The problem with the quick analysis is that it may not be as accurate as we need it to be, and currently, the fast process may result in some errors.
Another problem that will arise from this practice is the need for special devices that will be able to support this process, and the resource-demanding technology is not going to be easy on everyone’s pocket. You may need to invest a lot if you want to implement the process in your work, and you need to be ready for constant updates on your hardware and software.
The last thing that many people see as a negative side is that there is no proof of how the machine got to the analytical conclusion. Yes, we will get all the data we need, we will get the results, and we will get the predictions, but there is no step-by-step process, and we will just need to believe the AI that it made the right conclusion. The lack of transparency is a big problem, and hopefully, as technology advances further, these problems will get smaller, and hopefully erased.
These are the things that you should know about deep learning technology, and even though there is still room for improvement, it is said that this process will continue making a huge impact on different technologies.
In case you think about implementing the DL technologies in your company, you need to make sure you are ready to invest in all the right devices, including hardware and software, and that you are willing to invest in your skills. It is always better to consult with an expert before you take any steps forward. Even though there are some drawbacks of this process, it is definitely something that has made a huge impact on our lives and will continue to do so.