- Replacing cashiers at a fast food restaurant with a self-service kiosk system.
- Reducing multi-language communication friction in a company through automatic language translation.
- Replacing traditional cash registers at a retail shop with credit card payment terminals.
- Simplifying accountancy by using business rules to create an automated system.
Answer – Option (B) Reducing multi-language communication friction in a company through automatic language translation.
Reducing multi-language communication friction in a company through automatic language translation is the correct answer to “What is an example of value created through the use of deep learning?”
This is because neural machine translation systems can effortlessly and easily translate speech or text from one language to another which will help big corporations to incorporate members from different linguistic backgrounds without the need to worry about language barrier.
This in turn will give better change at collaborations as well as improve overall workload efficiency within the company. Also, consumer-based corporations can work with local businesses to expand and improve their image in their community.
Deep Learning And Its Uses
To further understand the answer let’s take a brief look at “Deep Learning”. Deep Learning is a sub-field of machine learning which is an Artificial Intelligence that helps computer systems to understand and use languages.
The translation is all about converting words and sentences from primary language to secondary language. Computer programs are taught to learn languages using Deep Learning and then translate it to another language using the same AI model.
This not only makes translation quicker but also helps the AI model to comprehend and improve all the mistakes made in previous translations, resulting in more accurate results. This will help businesses and corporates in multiple ways, some of which are as follows.
First and foremost, better cooperation and teamwork. With “Deep Learning” AI models members from different backgrounds can contribute by sharing their own ideas, understanding other team members, and working together on same projects.
Another notable benefit is the efficiency which means marketing team can understand local teams much faster and the communication carried out will be more accurate. Big corporations with multiple regional centers can understand and get more work done in less time.
One thing that not many people talk about is cost efficiency with deep learning. Human-based translation work takes time as well as lots of money however, AI translation models are a one-time investment which is a very good counterpart.
With the rise of the digital workforce, having a reliable tool to help with real-time translation can be extremely useful in every sector such as human resource department, employee training, consumer relation sections, and others.
Lastly, Deep learning AI models can provide data analysis from different languages much more feasible. This is especially helpful when your business or corporation has to engage in foreign events or connect with international consumers.
However, deep learning is not a flawless approach and it does come with several challenges. One of which is the need to install hyper computer system capable of running billions of computations along with a lot of data storage.
This makes it less approachable for small businesses or companies which are relatively new in the market. Another difficulty is with security and privacy that come with third-party deep learning AI models.
Conclusion
You might be wondering “What is an example of value created through the use of deep learning?” The correct answer to this is “using automated language translation to reduce multi-language interaction friction in the workplace” and there are many reasons for it. If you want to learn them all, refer to the answer above.