Current problems which are caused by AI and how it can be solved by Effect.AI
To start with, the use of artificial intelligence is gaining momentum and becomes more popular and widespread nowadays. This kind of intelligence is considered to be shown by machines and is called as the study of intelligent agents. An intelligent agent is a device which recognizes its environment and is able to take such actions which in the future will maximize its chance of success while gaining some goals. However, artificial intelligence has also a lot of problems and challenges which are connected with researching and developing AI technology. Consequently, AI research and development suffer from various difficulties while performing. But Effect.AI can give the solution to all of them.
The first problem is data processing. The applications which use artificial intelligence sometimes do such tasks which require anyway human feedback. It can be, for example, the tasks when you should process unstructured data or find patterns for providing necessary output. But intelligent applications can only deal with large datasets which also must have different annotations. The other problem lies in performing diverging tasks. The challenge here is that for creating a complex algorithm you need to have connection and interaction with some parts of the world which are situated outside the certain domain. And the last problem is related to computational costs. It is an extremely expensive task to develop and train AI systems because it demands a universal technical infrastructure which can process huge amounts of data. So, what Effect.AI can offer to resolve these problems?
First of all, being based on blockchain technology Effect.AI ensures a direct contact between supply and demand. Moreover, the high level of collaboration and data sharing between agents is provided. Thanks to the process of sharing costs AI becomes more affordable. So, the main advantages of Effect.AI are:
- accessibility (a direct link between supply and demand);
- accuracy (it is easy for individual applications to find each other either for buying or selling information);
- performance (the opportunity of enriching existing datasets using different methods);
- interoperability (the combination of several AI algorithms is successful because it gives powerful capabilities and emergent intelligence).
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