Called Cloud AutoML, the set of services gives businesses automated AI building tools. They can then create machine learning-infused services without a detailed understanding of the underlying tech. Cloud AutoML consumes data supplied by the business to automatically generate a machine learning model. This is then optimised to suit the dataset and begin producing further results. The initial release of the platform will include one service, Cloud AutoML Vision.
Google is boosting its AI-as-a-service offerings this week, most notably with the alpha release of a new Contact Center AI solution. Contact Center AI is built around its Dialogflow development suite for conversational agents, which was launched last fall and already in wide use. Dialogflow Enterprise Edition now has the ability to build AI-powered virtual agents for contact centers, a Phone Gateway for taking calls without infrastructure, Knowledge Connectors for understanding unstructured data like FAQs and Sentiment Analysis. In Contact Center AI, a Virtual Agent first answers the call and handles it if possible. If not, it passes the call to a human representative, who is helped by an Agent Assist system that continues to monitor the call and provide supporting info as needed.
Google on Monday announced it's integrating Cloud AuotML into Kaggle, its platform for data scientists. Cloud AutoML, which Google unveiled in 2018, automates the creation of machine learning models. The software makes it possible to build custom machine learning models without any specialized machine learning knowledge. Integrating AutoML into the Kaggle platform advances its mission to "empower our community of data scientists by providing them with the skills and tools they need to lead in their field," Google wrote in a blog post. Kaggle, which was acquired by Google in March 2017, specializes in Jupyter notebooks used by data scientists.