Salesforce's 'TransmogrifAI' helps enterprises build big AI systems based on oceans of data.

Mitch Wagner, Executive Editor, Light Reading

August 16, 2018

3 Min Read
Salesforce Open-Sourcing Machine Learning Software Behind Its 'Einstein' AI

Salesforce is opening sourcing TransmogrifAI, key software behind Einstein, the AI that's strategic to the company's future in sales, customer services and more.

TransmogrifAI helps build machine learning systems at enterprise scale. While consumer AI generally learns from a small number of well-understood use cases and datasets, enterprise scale AI requires a broad diversity of data and use cases, which makes building enterprise AI systems harder, according to a post Thursday on the Salesforce Engineering blog by Shubha Nabar, senior director of data science at Salesforce Einstein. A broad range of data is required to predict enterprise events such as customer churn, sales forecasts and lead conversions.

Enterprises also need to protect data, and not share it with other organizations or competitors, she says.

TransmoigrifAI helps automate the process of parsing through that ocean of data to generate machine learning models while also protecting the data confidentiality, Nabar says.

Figure 1:

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"The dictionary defines Transmogrification as the process of transforming, often in a surprising or magical manner, which is what TransmogrifAI does for Salesforce  --  enabling data science teams to transform customer data into meaningful, actionable predictions," she writes. (She does not mention that the comic Calvin & Hobbes made the transmogrifier famous.)

Earlier today, Google (Nasdaq: GOOG) introduced its own tools to simplify building AI at enterprise scale. In Google's case, it's giving developers a head start in deploying AI for specific uses, starting with recruitment, contact center and recommendations. (See Google Applies AI to Recruitment, Call Centers & Recommendations .)

And yesterday, Salesforce rival Oracle Corp. (Nasdaq: ORCL) open sourced one of its own machine learning tools, GraphPipe, which concentrates on deployment, performance and delivering standardized APIs. (See Oracle Open Sources GraphPipe for 'Dead Simple' Machine Learning Deployment.)

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About the Author(s)

Mitch Wagner

Executive Editor, Light Reading

San Diego-based Mitch Wagner is many things. As well as being "our guy" on the West Coast (of the US, not Scotland, or anywhere else with indifferent meteorological conditions), he's a husband (to his wife), dissatisfied Democrat, American (so he could be President some day), nonobservant Jew, and science fiction fan. Not necessarily in that order.

He's also one half of a special duo, along with Minnie, who is the co-habitor of the West Coast Bureau and Light Reading's primary chewer of sticks, though she is not the only one on the team who regularly munches on bark.

Wagner, whose previous positions include Editor-in-Chief at Internet Evolution and Executive Editor at InformationWeek, will be responsible for tracking and reporting on developments in Silicon Valley and other US West Coast hotspots of communications technology innovation.

Beats: Software-defined networking (SDN), network functions virtualization (NFV), IP networking, and colored foods (such as 'green rice').

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