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Database driven neural networks
Cybertec uses modern neural networks in combination with modern database technology. Combining artificial intelligence with PostgreSQL allows us to provide applications for totally new use cases.
Sample of a neural network
Use cases
- Artificial intelligence can be used for many different purposes:
- Fraud detection and prevention
- Optimization of processes
- Analysis of time series (e.g. financial data, …)
- Scientific models (simulations of climate, etc.)
- Pattern detection
- Data mining
- Industrial applications
- Game development
To work properly neural networks need data. PostgreSQL is an ideal database product to interact with neural networks. As PostgreSQL is highly extensible it is possible to integrate artificial intelligence with superior database technology.
Technical information
How neural networks work
Neural networks simulate the processes of human brains. In contrast to traditional approaches to build simulation models neural networks are able to detect complex interactions themselves. This means that the model itself decides which input is relevant and which parts of the data are not relevant. This makes it a lot easier to simulate complex interactions.
Neural networks can be optimized for special use cases. To get proper results the artificial neural network has to be trained with historic data. During this training process the network learns based on the data and used this knowledge for predicting the future.