Contents
- What is a neural network?
- How do neural networks work?
- Where are neural networks used?
- Neural networks in marketing
- How to query neural networks?
What is a neural network?
A neural network is a software that uses a mathematical model to process data, mimicking the neural connections of the human brain. The main characteristic of neural networks is their ability to make decisions based on past experiences. Unlike traditional programs that follow pre-defined algorithms, neural networks can "create" algorithms on their own. They identify features, relationships, and hidden patterns that may be inaccessible to developers.
Thanks to unique information processing methods, neural networks can work with unstructured data of various formats, finding complex nonlinear relationships, analyzing errors, and improving their algorithms. This makes them particularly useful in situations where it is necessary to analyze numerous similar cases to find the most effective solution.
How do neural networks work?
The structure of a neural network consists of artificial "neurons" or nodes, each of which performs specific computations. These nodes are interconnected through "synapses," which represent channels for transmitting information. Each synapse has a weight that reflects the importance of the neuron's output for the overall result of the network. At the beginning of training, the weights are distributed randomly, but as training progresses, if a path leads to the correct solution, the weight increases, resembling the process of strengthening neural connections in the human brain.
A simple neural network consists of three layers: input, hidden, and output. The input layer receives external information in various formats, the hidden layer processes the data, and the output layer generates the final response, which can be presented in any format—from numbers to images.
Where are neural networks used?
Neural networks are applied in various fields, performing tasks that were previously only solvable by humans. Some of the main areas of their application include:
- Recognition of medical images and analysis of research results.
- Assessment of borrowers' creditworthiness and market trend forecasting.
- Automation of manufacturing processes and quality control.
- Facial recognition and assistance in locating criminals.
- Generation of content recommendations in social networks and online stores.
- Translation and voiceovers for videos in real-time.
- Analysis of job applicants' resumes.
- Transformation of people's ages in videos and creation of unique media content.
Neural networks in marketing
There are many examples of neural networks being used in marketing and advertising. Companies utilize them for:
- Conducting market research and analysis.
- Automating the purchase of digital advertising through specialized platforms.
- Optimizing media planning and reducing advertising costs.
- Analyzing and planning promotional activities, including inventory control and campaign planning.
- Generating personalized recommendations for customers.
How to query neural networks?
Neural networks can also be used to create content, including text materials and graphics. For example, modern neural networks like ChatGPT and Stable Diffusion allow for the generation of texts, logos, and videos based on textual descriptions. However, it is important to formulate queries clearly to achieve the best results.
Despite significant advancements in artificial intelligence, neural networks cannot fully replace humans. They are a powerful tool that can simplify and expedite task execution, but optimal results require human-machine interaction.