Intelligent tagging and decision making serve for interpreting the user's request. For example, the user may ask: 'What do I watch tonight?'. The technology will tag the top-rated movies and suggest you a few according to your interests.
Image recognition is a very useful upcoming feature that will help the blind people, travelers as well as daily chores of any people.
The noises from cars, electrical appliances, other people talking near you make the user's voice unclear. This technology will reduce or eliminate the background noise that prevents a correct voice recognition.
This is a very important option from the point of view of security. Thanks to this feature, the voice assistant may identify who is talking and whether it is necessary to respond.
With this mechanism, the client side of the applications will resize the voice data and send it to the server in a succinct format. It will provide a fast application performance without annoying delays.
Voice interface is what the user hears and sees in return to his or her request. For the voice part, you will need to pick up the voice itself, set the rate of speech, the manner of speaking, etc. For the visual part, you will have to decide on the visual representation that a user is going to see on the screen.
If we are able to feed enough data to our AI, this can be a Farmer’s true friend! What to plant, when to plant, what about seed, fertilizer, paste control?
if we feed existing/historical farming data from Govt. organizations, educational institutions, NGOs etc. Based on our model, AI will analyze data and learn the time & process of farming perfectly.
Our AI can be used to analyze incoming calls, AI will learn how & what to response. After initial learning period, AI can communicate & suggest solutions to users directly.
THEiA will take input & save data to analyze them, to learn and evolve. Then the Analyze, Learning & Evolving process starts. And this is also how response/solution will be delivered to users.