Microsoft's new service automatically builds AI models

While announcing the new Azure AI platform service, Microsoft also revealed it is launching a $50m humanitarian AI initiative

25Sep

Microsoft has introduced a number of new workplace AI services through its Azure Machine Learning platform. These services include new, faster ways to train AI systems, custom Cortana voice apps for business and a service which automatically generates AI and ML models.

The AI model generator will be capable of automatically picking the most appropriate algorithm for the user's needs and will also be able to optimize the model without assistance from a data scientist.

This move by Microsoft has put them in direct competition with Google's AutoML and Nvidia's upcoming semiautonomous Project Maglev.

Tech giants are preparing for a completely AI-integrated future where their platforms are the 'go-to' place for developers, so are focused on creating solutions to empower them.


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The upgraded service offers users a myriad of automated AI options depending on the model the user wants to create and how advanced they are at data science. Users can explore a number of application programming interfaces such as vision, speech, language, knowledge and search. The can also decide which of the platform's AI tools, AI frameworks or AI-related infrastructure is necessary to aid them in the open platform.

In conjunction with the announcement, Microsoft also revealed the launch of the AI for Earth, a five year, $50m initiative with the aim of facilitating the creation of new AI to tackle planet-wide issues such as biodiversity, conservation and climate change. So far, more than 100 grants have been awarded by the initiative to developers from all around the world.

In a blog post, Brad Smith, Microsoft's president said: "We believe that technology, like AI combined with cloud technology, can be a game changer, helping save more lives, alleviate suffering and restore human dignity by changing the way frontline relief organizations anticipate, predict, and better target response efforts."

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