Automated data ingestion
AI systems deal with huge amounts of data from multiple concurrent sources. Data ingestion is the process of extracting unstructured data from these sources to prepare them for machine learning. It is a time-intensive process if done manually. AI software automates this process, freeing up resources and ensuring ML models have the most recent and applicable data.
2. Adaptive-reactive
A key feature of an AI platform is its ability to adapt to the environment with the help of machine learning. It observes its own results and tries to learn how to correct or improve its performance to provide better results. AI software reacts to the changing inputs and conditions. It monitors its inputs, and when certain conditions apply, it looks for the best-suited procedures, rules, or computations and makes a decision.
3. Forward-looking
In addition to adaptive-reactive capabilities, AI software considers multiple scenarios and searches for an effective way to reach its goal. It projects multiple steps into the future and makes calculations to choose the best scenario.
4. Concurrent
AI software is capable of handling multiple users or applications interacting with it simultaneously. It uses advanced technology such as distributed systems and parallel approaches so it can ingest data efficiently, adapt and react quickly to a changing environment, or choose the best path from multiple possible scenarios.