Cloud AI building blocks - Sight, Language and Conversation
Cloud AI building blocks – Sight, Language and Conversation
Cocado has personalised customer interactions by using AI to filter mails for urgent cases that require more immediate attention while box, the software that provides free storage space uses Google Cloud AI to enahnce it’s image recognition technology help its customers who need to identify objects in photos and pictures in their online files.
Google has the Cloud AI building blocks which helps developers get into speed with sight, language and conversation tools.
One such example is Google Translate which basically takes in a string of Unicode characters, detects the language and translate it into the target language. The query can be sent as a query string and the result is return as a JSON response to the call. This solution is scalable and it is used in “Clas of Kings” which requires language translation for the global gaming community. VICE, a media company use Google Translate which helps translates 18 languages in real time for writers. This greatly speeds up the editorial content in various language. It could be integrated with speech api to do real time language translators.
An example of Google Translate which can convert websites on the fly. In this case, this web page in English is translated into Chinese on the fly. Click this link to translate.
In Vision, it an recognise faces and is able to a meta data returned in JSON which can be indexed in a database. e.g. if the picture of the person is a professional based on his outfit. It can detect if the person’s mood, is the person happy or violent. Such a system may be used for surveillance.
Likewise, if you have a library of videos, an application can be developed to identify the objects within the videos. This is possible as videos are just multiple frames in motion. Thus, videos can be easily search for a bicycle, a cat within the video. The meta data can then be used as an index for searches or future use.
Google also provide Cloud AutoML which makes it easier for developer to do machine learning for any problem by providing data sets. The higher the model size the higher the accuracy.
Disney uses Cloud AutoML technology to build vision models to annotate their products with Disney characters, product categories and colours. These data are index and used in their search engine and product recommendations on shopDisney.