Microsoft announced today that it has acquired Semantic Machines, a Berkeley-based startup that wants to solve one of the biggest challenges in conversational AI: making chatbots sound more human and less like, well, bots.
In a blog post, Microsoft AI & Research chief technology officer David Ku wrote that “with the acquisition of Semantic Machines, we will establish a conversational AI center of excellence in Berkeley to push forward the boundaries of what is possible in language interfaces.”
According to Crunchbase, Semantic Machines was founded in 2014 and raised about $20.9 million in funding from investors, including General Catalyst and Bain Capital Ventures.
In a 2016 profile, co-founder and chief scientist Dan Klein told TechCrunch that “today’s dialog technology is mostly orthogonal. You want a conversational system to be contextual so when you interpret a sentence things don’t stand in isolation.” By focusing on memory, Semantic Machines claims its AI can produce conversations that not only answer or predict questions more accurately, but also flow naturally, something that Siri, Google Assistant, Alexa, Microsoft’s own Cortana and other virtual assistants still struggle to accomplish.
Instead of building its own consumer products, Semantic Machines focused on enterprise customers. This means it will fit in well with Microsoft’s conversational AI-based products. These include Microsoft Cognitive Services and Azure Bot Service, which the company says are used by one million and 300,000 developers, respectively, and its virtual assistants Cortana and Xiaolce.
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