Now that just about everybody has some understanding of how machine and deep learning technologies will drive the next wave of intelligent enterprise applications, the race to be the first to tap into those capabilities is on.
Salesforce today unfurled a spring 2017 release of its Einstein service that adds Einstein Vision application programming interfaces (API) to be able to train Einstein to recognize photos, in addition to support for unstructured data types alongside structured Salesforce data.
Earlier this week, Salesforce revealed a partnership with IBM under which Einstein and the IBM Watson platform for infusing cognitive computing capabilities will be integrated in the future.
The latest release of Einstein primarily makes good on promises Salesforce already made, including integration with a broad range of Salesforce cloud services spanning analytics, e-commerce, community and marketing. The next release of Einstein, due out this summer, will add deeper analytics within each Salesforce cloud service as well as support for additional integrated workflow capabilities.https://o1.qnsr.com/log/p.gif?;n=203;c=204663295;s=11915;x=7936;f=201904081034270;u=j;z=TIMESTAMP;a=20410779;e=i
Salesforce CEO Marc Benioff says via all those services, Salesforce is already driving rapid adoption of AI in the enterprise.
“This year, we’ll soon have a billion users of Einstein,” says Benioff. “We’re really excited about finally getting Einstein into the hands of our customers.”
Salesforce also touted the early formation of an ecosystems surrounding Einstein, with 15 third-party startup vendors now working on applications that invoke Einstein.
In general, the relationship with IBM signals how rapidly machine learning and deep learning technologies, which have their roots in neural networks, are evolving. Together, Salesforce and IBM should be able to leverage each other’s machine and deep learning research to maintain an edge over rivals pursuing similar strategies.
That capability should also prove critical for enterprise IT organizations that are likely to wind up with scenarios where integration between various forms of AI across an extended set of business processes will be a fundamental requirement.