Neural networks are at the height of their glory. According to statistics, over the past few years, the use of artificial intelligence has grown by a record 270%. AI-enabled solutions are used to perform a variety of business tasks including sales forecasting, customer research, data validation and risk management. IT specialist Gennady Dmitrik talks about the business opportunities that new technology opens up.
Why use neural networks
Neural networks are information-processing models “inspired” by the way neurons work in the human brain. That is, neural networks imitate the brain structure and behavioral patterns. Artificial neural networks are part of machine learning; using algorithms, they are able to discover hidden patterns and correlations in raw data, cluster and classify them, and continuously learn and improve. They are also capable of making generalizations and conclusions, and revealing hidden correlations and patterns.
Neural networks perform complex business tasks no worse than a person, and their cost, even adjusted for possible errors, is very competitive. However, it is also clear that artificial intelligence and humans must operate hand in hand. A neural network is capable of processing large amounts of information and analyze it, while a person can adapt and edit the resulting product based on the business’s needs. Other things a neural network can do:
- identifying images;
- visualization;
- identifying sequences;
- filtering information;
- generating output in accordance with the specified criteria.
Scope of applications for AI
In fact, artificial intelligence has long penetrated society. Vehicles can actually move without a driver, not just automatically park, keep to a lane, or monitor traffic to prevent collisions; they can independently develop a route from point A to point B and complete the journey safely. All humanity needs to do is regulate responsibility at the legislative level for exceptional cases and introduce the technology widely.
When we get a phone call, we can’t immediately tell if we are speaking to a human or a perfectly trained neural model with a striking imitation of a human voice and natural-sounding tones. This already happens today when we call banks and ask questions verbally: the system can maintain a conversation and guide callers by asking clarifying questions.
Another application for this sort of system is using a smart answering assistant: the program can easily record a conversation, schedule a meeting in a calendar and transcribe a dialogue. Neural networks have a wide scope of applications in modern business settings, from finance to healthcare.
Relying on artificial intelligence is extremely relevant in marketing. AI can be used for segmenting clients, creating purchase models, identifying sequences and forecasting based on data and process automation. For example, mobile phones constantly listen to us and the language you speak or the language of your smart phone interface are not particularly important. Even anonymized ad identifiers do not affect data collection or processing. Experiments have shown that for different iOS devices, if you pick several phrases or international brands and pronounce them at intervals (to determine their effectiveness in proximity to devices), the outcome is always the same: in about 30 seconds, advertisers will reach the interested customer. On the one hand, privacy and security are at stake; on the other, it is an opportunity to promote goods to the most precise targeted audience using AI.
In banking, AI-powered systems can analyze credit assessment and loan applications, fraud and risks, bad loans and credit deterioration.
Neural networks can also play an enormous role in healthcare. Modern technology allows controlling not only daily activity but also analyze cancer cells. An IBM study claims that an AI model correctly predicted breast cancer in 87% of cases.
Verifying quality of a product by recognizing visual images and detecting flaws can help manufacturing businesses.
Moreover, trained neural network models can be coaches that can flag errors, issues and suggest solutions. The simplest example is style and grammar analysis of texts that suggests better wording, a service particularly relevant to professionals working with copy.
Less obvious opportunities of AI in business
Artificial intelligence helps with resolving many issues such as security, customer’s choice or human intention. There is software (eyeware) for 3D tracking of eyesight depth that helps record real interactions, user attention, intention, motives and interests.
Microsoft developed Seeing AI, an app based on AI and machine learning that serves as visual aid and helps people with visual impairments to navigate objects and texts. For example, by pointing a camera at a product, the user will learn the product description. This technology may help businesses make their customer base more inclusive.
Artificial intelligence is an important tool for human resource management companies. From the recruitment and onboarding process to HR management and training, neural networks help HR departments adapt to workers’ changing needs. AI also automates HR operations, screening thousands of resumes and reducing manual workload. One example of an AI-powered recruiter is pymetrics.
Even on modern smart phones, we already use numerous pre-trained neural networks without even realizing it. Spam messages in our inboxes are filtered on the go; other emails are scanned for events, schedules and tasks to be added to the calendar. There is also fast and convenient search for documents, presentations and most frequently used apps based on geolocation, time of day and launch frequency. AI recognizes faces, sorts photos by type and objects, and offers relevant photo memories. Obviously, neural networks have changed our lifestyle. The most important thing is to know how to adapt modern technology for business purposes in a smart way.