Microsoft acquires AI startup Bonsai to fuel AI capabilities

Based in Berkeley, California, Bonsai was founded in 2014 and has around 42 employees.

Microsoft acquires AI startup Bonsai to fuel AI capabilities

San Francisco: Microsoft has announced that it has signed an agreement to acquire Bonsai, an artificial intelligence (AI) startup based in San Francisco, to boost its AI and machine learning capabilities.

In its official blog, Microsoft said, "Today we are excited to take another major step forward in our vision to make it easier for developers and subject matter experts to build the “brains”— machine learning modelfor autonomous systems of all kinds with the signing of an agreement to acquire Bonsai."

"The company is building a general-purpose, deep reinforcement learning platform especially suited for enterprises leveraging industrial control systems such as robotics, energy, HVAC, manufacturing and autonomous systems in general. This includes unique machine-teaching innovations, automated model generation and management, a host of APIs and SDKs for simulator integration, as well as pre-built support for leading simulations all packaged in one end-to-end platform," the blog said.

Bonsai's platform combined with rich simulation tools and reinforcement learning work in Microsoft Research will compose with its Azure Machine Learning running on the Azure Cloud with GPUs and Brainwave, it added.

Based in Berkeley, California, Bonsai was founded in 2014 and has around 42 employees.

Bonsai said on its official website that it is building "the world's first deep reinforcement learning platform that empowers enterprises to build intelligence into real-world systems."

It claims to have a team that "brings deep experience in machine learning and developer tools from the likes of Microsoft, Uber, Google and Apple."

Bonsai CEO Mark Hammond worked for Microsoft as an engineer in the late 1990s and early 2000s.

Microsoft bought another two small AI startup companies, SwiftKey and Maluuba, in 2016 and early 2017.

With IANS Inputs

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