4 Potential Applications Of Neural Networks To Your Business

August 19, 2022
Photo by Alina Grubnyak on Unsplash

Recent market research indicates that the neural network market will grow tenfold within the present decade. From a value of USD$14.35 billion two years ago, market experts predict it’ll breach the USD$150-billion mark by 2030. They point to the increase in IT spending by many businesses due to the COVID pandemic as the primary factor for this upward trend.

But there’s no need to wait that long to see such growth. Neural networks are widespread across multiple industries, with technologies like speech-to-text transcribers to deep learning modules for artificial intelligence (AI). To have a working neural network, developers arrange sequential data and always maintain information about the order—and they’re getting better at it.

No matter the size or nature, businesses today should consider investing in neural networks or technologies that use them. The possibilities are endless with them, and here are several ways they can be a boon to doing business.

1. Financial Decision-Making

Before the advent of big data, knowing where the economy would go was a hit or miss. Investors had to rely on the information on hand to make decisions, lacking the foresight that technological marvels today can achieve. Analysts during the Great Depression of the 1930s expected deflation across the board but not at the scale it actually happened.

With neural networks and their ability to learn from past and present data, financial applications can mitigate the effects of bad decisions, if not steer clear of them. Although forecasts made by neural networks are by no means guaranteed, the information is crucial in letting investors and business owners know what and what not to do.

One program in this context is a decision manager. It runs a neural network that examines new transactions and discerns which ones are good or bad for the business. Some variations include features like fraud detection and forecasting to some degree.

2. Personalized Shopping Experience

Arguably the most extensive use of neural networks goes to retail, where they help consumers find and get what they want or need. Fire up any shopping app on your phone; the home page will likely show recommended products based on your recent search.

This feature was unimaginable before neural network technology, let alone personalization in retail, became mainstream. Businesses had little to no idea about their consumers’ wants and needs because gathering and processing data was limited. To compensate, they had to ramp up their marketing efforts.

With neural networks, marketing in retail has become much less cumbersome. For instance, deep learning has improved computer vision by extracting and managing vast amounts of unstructured data. Given the thousands, if not millions, of listings for a single type of product, neural networks can narrow down options just by presenting an image or video.

3. Advanced Cybersecurity

Cybersecurity has been a hot topic in the business sphere for years and continues to be this year. The latest statistics indicate that well-equipped attackers can breach nine of ten corporate cybersecurity infrastructures. Worse, it often feels like the attackers are one step ahead of cybersecurity tech, with attacks growing in sophistication through the years.

Experts believe neural networks may play a significant role in thwarting future data breaches and other attacks. In the U.S., many tech startups are developing deep learning models to stop attacks in less than a second. They also train these models to discern false positives, which can be just as dangerous as actual ones.

That said, it’s important to note that technology only forms a third of the complete cybersecurity picture. A business’s workforce must remain vigilant for any attempts or breaches in progress. Additionally, a business must have a recovery plan for when it suffers from such attacks.

4. Healthcare Advancements

If the pandemic has taught the world one thing, the current healthcare system requires a much-needed upgrade. For example, contactless consultations warrant the development of telehealth and increased transparency by healthcare practitioners and experts.

Neural networks are in a prime position to develop programs and systems that can give accurate diagnoses and information on treatments and the hospitals or clinics that provide them. One way to apply neural networks entails a two-stage system where the AI reviews test results twice and forwards the data to the attending doctor if everything checks out.

Conclusion

These applications only scratch the surface of neural networks’ boundless potential. Imagine this technology helping the economy steer clear of another devastating stock market crash or finding a cure for a previously incurable disease. Regardless of the obstacles, neural networks are likely to be the future of business.

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