Microsoft and Google move to expand machine learning operations

Microsoft and Google have announced plans to expand their machine learning capabilities, through acquisition and new research offices respectively.

Jamie Davies

June 17, 2016

3 Min Read
Microsoft and Google move to expand machine learning operations

Microsoft and Google have announced plans to expand their machine learning capabilities, through acquisition and new research offices respectively.

Building on the ‘Conversation-as-a-Platform’ proposition put forward by CEO Satya Nadella at Build 2016, the Microsoft team has announced plans to acquire Wand Labs. The purchase will add weight to the ‘Conversation-as-a-Platform’ strategy, as well as supporting innovation ambitions for Bing intelligence.

“Wand Labs’ technology and talent will strengthen our position in the emerging era of conversational intelligence, where we bring together the power of human language with advanced machine intelligence,” said David Ku, Corporate Vice President of the Information Platform Group on the company’s official blog. “It builds on and extends the power of the Bing, Microsoft Azure, Office 365 and Windows platforms to empower developers everywhere.”

More specifically, Wand Labs adds expertise in semantic ontologies, services mapping, third-party developer integration and conversational interfaces, to the Microsoft engineering team. The ambition of the overarching project is to make the customers experience more seamless by harnessing human language in an artificial environment.

Microsoft’s move into the world of artificial intelligence and machine learning has not been a smooth ride to date, though this has not seemed to hinder investment. Back in March, the company’s AI inspired Twitter account Tay went into melt-down mode, though the team pushed forward, updating its Cortana Intelligence Suite and releasing its Skype Bot Platform. Nadella has repeatedly highlighted artificial intelligence and machine learning is the future for the company, stating at Build 2016:

“As an industry, we are on the cusp of a new frontier that pairs the power of natural human language with advanced machine intelligence. At Microsoft, we call this Conversation-as-a-Platform, and it builds on and extends the power of the Microsoft Azure, Office 365 and Windows platforms to empower developers everywhere.”

Who is the leader in artificial intelligence and machine learning?

  • Google (44%, 30 Votes)

  • IBM (40%, 27 Votes)

  • Microsoft (13%, 9 Votes)

  • AWS (1%, 1 Votes)

  • HPE (1%, 1 Votes)

  • Salesforce (0%, 0 Votes)

Total Voters: 68

Google’s efforts in the machine learning world have also been pushed forward this week, as the team announced dedicated machine learning research based in the Zurich offices, on its blog. The team will focus on three areas specifically, machine intelligence, natural language processing & understanding, as well as machine perception.

Like Microsoft, Google has prioritized artificial intelligence and machine learning, though both companies will be playing catch-up with the likes of IBM and AWS, whose AI propositions have been in the market for some time. Back in April, Google CEO Sundar Pichai said in the company’s earnings call “overall, I do think in the long run, I think we will evolve in computing from a mobile first to an AI first world,” outlining the ambitions of the team.

Google itself already has a number of machine learning capabilities incorporated in its product portfolio, those these could be considered as relatively rudimentary. Translate, Photo Search and SmartReply for Inbox already contains aspects of machine learning, though the team are targeting more complex and accurate competencies.

Elsewhere, Twitter has announced on their blog advertisers will now be able to utilize emoji keyword targeting for Twitter Ads. This new feature uses emoji activity as a signal of a person’s mood or mind set, allowing advertisers to more effectively communicate marketing messages minimizing the potential for backlash of disgruntled twitter users. Although the blog does not state the use of machine learning competencies, it does leave the opportunity for future innovation in the area.

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