From the instant you woke up today to that first bite of your breakfast, your brain was already hard at work. The brain contains billions of interconnected units that process sight, smell, and thoughts. Artificial neural networks, which almost work similarly, are slowly and surely reshaping corporate and social life. These AI systems can perform tasks, capture images, understand languages, and identify patterns and anomalies.
They spearhead innovation and optimize numerous operations like fraud detection and demand forecasting. Here’s a look at several applications of this emerging tech in the corporate world and our social lives.
Customer Relationship Management
Using neural networks to assess customer data can be a game-changer for businesses. CRM data is a treasure trove of consumer insights, encompassing the consumers’ names, email, and online activity. They are useful in assessing such information and revealing patterns that may not be easily noticeable. Hence, you can easily predict which customers will likely buy your products and focus on these hot leads.
These networks boost conversion rates by assessing consumer behavior and recommending products or services that fit their tastes. You can accelerate the results by using Leadar to find marketing and sales experts to help with the rest of the funnel strategies. Combining professional experience with neural network analysis of your CRM data provides a 360-degree view of your high-value prospects.
Fraud Detection and Prevention
Fraudsters have become increasingly smarter over time to the point that they can wreak havoc within the blink of an eye. Banks and e-commerce businesses that handle thousands of transactions daily rely on highly interconnected tech. The systems operate in real time to swiftly process incoming transactions and help minimize fraud. These networks assess every transaction for patterns different from the norm, such as multiple failed login attempts, unusual IP addresses, or inconsistent purchasing behavior. In case of any abnormality, they block the transaction or request more personal identification details.
If you own a retail store or are a manufacturer, you must juggle between overproduction and underproduction. When you produce excess products, you’re stuck with a bloated inventory, and underproduction could mean lost revenues. However, with neural networks, you can accurately forecast the market demand. By analyzing historical sales information, seasonality, and other factors, you can optimize inventory management and ensure products are available when customers need them. Consumers expect your products to be available always; otherwise, they will turn to your competitors. Demand forecasting aids you to avoid stockouts and keeps your customers happy.
For any business to be successful, customer satisfaction is non-negotiable. Many consumers tend to express dissatisfaction on social platforms, and that’s where neural networks come in. Many monitoring tools utilize this technology to perform sentiment analysis on diverse platforms. They can assess texts and tell whether social media mentions about a brand or product are positive, negative, or neutral. When businesses understand their consumers’ sentiments, they can make more informed decisions, improve products and services, and ultimately achieve customer satisfaction.
Recommendation systems provide potential clients with personalized suggestions on suitable content or products. They collect consumer data, which neural networks use to create user profiles, and proceed to capture consumers’ behavior and preferences. They also assess items in the recommendation system and identify their attributes and correlations between users and items. Since neural networks are adept at pattern recognition, they can identify popular commodities. Subsequently, they can tell which products are bought together and will use this information to make recommendations.
Applications in Social Life
Here are five applications of neural networks in social life and how they can benefit you.
Social Media Experience
Social sites like Instagram store massive amounts of user data, including likes, shares, and comments. With such massive databases, neural networks help process and filter relevant information. They extract keywords, topics, and sentiments from posts and assess them to identify context and meaning. After getting this part right, they recommend content based on user behavior.
For instance, assume we have two users here, John and Jane, with similar interests. When John likes a post, Jane will see this post on the list of suggestions of posts she might like, thanks to neural networks.
VAs and Chatbots
If you regularly use voice assistants (VA) like Siri or Google Assistant, you may have noticed that they have improved over time. This improvement results from increased development and sophistication of neural networks, especially in understanding natural language. This innovation allows voice assistants and chatbots to comprehend and interpret natural language, slang, and regional accents. With such sophistication, users can interact with voice assistants and chatbots more naturally, making queries, requests, and conversations smoother and less frustrating.
The rise of social media has seen a surge in hate speech, cyberbullying, and other online vices. Hence, there has been a policy outcry to moderate these online spaces. Neural networks’ algorithms come in handy regarding detecting and filtering out inappropriate or harmful content. These robust spy technologies continuously check and flag content whenever users post it. This means that whenever you upload content, they must analyze it for any violations of content guidelines.
Many people join social media forums and groups for knowledge and entertainment. Sometimes, you meet people from diverse backgrounds who can only communicate in their native language. The neural networks leveraged by translation tools provide you with real-time language translation capabilities, breaking down language barriers and enabling cross-cultural exchanges.
Images and Objects Identification
Technology growth has made neural networks an integral part of our social life. These systems are exceptionally good at recognizing faces in diverse environments, including complex scenarios with varying lighting, angles, and facial expressions. Social media sites leverage this capability to detect and tag individuals in a photo. Automated tagging ensures everyone in the image can see and engage with the content.
As more people adopt neural networks in their businesses and social life, it’s evident that these almost brain-like marvels are more than just algorithms. This piece only scratches the surface because there’s so much more to explore in artificial intelligence than the time or space to write about it.