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Machine learning sol'n for SMEs at par with Watson

Posted: 01 Oct 2015     Print Version  Bookmark and Share

Keywords:Dato  machine learning  IBM  Watson  neural network 

Dato Inc., a machine-learning software company, has announced that it is branching out to mid-sized and small-enterprises with GUI toolkits and online training to implement machine learning. Founded in 2012, the company has in just three-years skyrocketed into the major corporations by offering them IBM Watson calibre learning capabilities at a fraction of the price and in a bundled package that can be embedded inside existing applications, Dato stated.

"We supply machine learning capabilities to everyone, from picking rooms for Hotel Tonight to picking Pandora songs for music listeners," stated Carlos Guestrin, CEO of Dato and Amazon Professor of Machine Learning in Computer Science & Engineering at the University of Washington.

Dato not only supports multiscreen advertising campaigns across multiple platforms, but also routinely deals with web distributed content for banks, financial institutions, oil exploration and all types of online platforms, from Paypal to StumbleOn to Zillow, using both archival data, real-time streams or both simultaneously.

Dato machine learning

Dato uses a four step strategy to add machine learning capabilities to your application. (Source: Dato, used with permission)

"We can learn from archives or learn from scratch in 'trending' mode while combining traditional neural network type 'deep learning' with our own proprietary real-time learning algorithms," Guestrin noted.

Dato claims its success comes from three ingredients, which are built into its turnkey toolkits, namely, both bottom-up learning and high-level "springboard" learning that simultaneously drills down until the two meet. Secondly, automatically identifying noise, recurring- and outlier-data that confuses plain-Jane algorithms, resulting in very robust learning. And thirdly, nearly infinite scalability in all dimensions: data size, number of available cores and number of graphics-processor units available for acceleration.

Dato's graphical tools

Dato's graphical tools allow easy definition of the machine learning capabilities users want to add (left), then allows them to use its prediction engine on premises to validate it doing what you want (middle), and finally (right) allows you to deploy to a distributed platform like Amazon Web Services, Hadoop, or Apache Spark. (Source: Dato, used with permission)


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