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‘Point, Click, Predict.’ myEinstein: Putting coders out of business?

New Salesforce AI platform promises to ‘empower’ developers

“Salesforce reimagined AI, bringing it out of the lab and into the hands of business users with Salesforce Einstein, which now generates more than 475 million predictions every day,” said John Ball, general manager and senior vice president, Salesforce Einstein

Sophisticated predictions, recommendations and insights are now within reach of anyone, well, within reach of a mouse. ‘Clicks, not code’ are all that’s required to operate myEinstein, the powerful machine learning platform launched by Salesforce at Dreamforce 2017, in downtown San Francisco’s Moscone Centre this week.

“Salesforce reimagined AI, bringing it out of the lab and into the hands of business users with Salesforce Einstein, which now generates more than 475 million predictions every day,” said John Ball, general manager and senior vice president, Salesforce Einstein.

“Today, we are further democratising AI by empowering admins and developers to transform every process and customer interaction to be more intelligent with myEinstein. No other company is arming customers with both pre-built AI apps for CRM and the ability to build and customise their own with just clicks.”

News of the myEinstein announcement spread quickly through the massive crowd of 170,000 plus attendees at Dreamforce 2017 and was met with equal levels of enthusiasm and scepticism.

Two new services in particular stand out: Einstein Prediction Builder allows customers to automatically create custom AI models that can predict outcomes for any field or object in Salesforce; while Einstein Bots can be trained to increase customer service workflows by automating tasks such as answering questions and retrieving information.

Heavy lifting

While the new AI products are being marketed as tools that can not only do the heavy lifting in terms of data mining, but also guide users in terms of strategy and choosing how to customize analysis/insight that might improve your bottom line, in reality the tech isn’t really capable of that level of valuable input just yet.

“You still need to have well-defined strategies set out - meaning people, not machines, will need to come up with good questions to ask of datasets,” explains Morgan Stewart, co-founder and chief executive of strategic email marketing agency, Trendline Interactive.

“A college professor once told me the key to good research is asking better questions than anyone else,” he states. “Once you have a good question the research part becomes almost formulaic. I don’t know that myEinstein is capable of formulating the most succinct questions yet.

“It can certainly help you get to the answers faster, which is great. But the heavy lifting is still needed on the data integration side. It can crunch the numbers once it has them but someone must first provide that data correctly, which is still a pretty laborious task. In specific cases, there are very practical applications but the expectations of AI generally are still unrealistic right now.”

Dreamforce 2017 took place from Sunday 5th November until Wednesday November 8th.

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