Currently, a driver involved in a car accident takes a picture of the damaged car and relays it to an insurer instantly for a quote.
A hotel guest checks in and issues voice commands to a designated in-room personal assistant to order a rental vehicle from a company selected by the guest. The vehicle is delivered outside the lobby about half an hour later.
What’s more, a hat retailer utilizes data analytics to configure its marketing formula, leading to 60% of recipients suddenly opening their messages, particularly in an email campaign.
All these are the real use cases that were presented during Dreamforce 2018 this week. They helped in highlighting a theme that took a large part of the conversation amongst 170,000 attendees.
Salesforce has been keenly pursuing artificial intelligence since rolling out Einstein two years back. Furthermore, the company may be making considerable progress in this challenging field.
Chances are high for Salesforce and any other company looking to create a lucrative business in the artificial intelligence space.
“What’s coming next is AI,” Ulrich Spiesshofer, president, and chief executive of global industrial solutions giant ABB Ltd. We need to be leading in AI use as an industry,” claimed during a conversation on Wednesday with Salesforce co-Chief Executive Officer Marc Benioff on a Dreamforce stage.
ABB, which recently announced a considerable in-house growth of Salesforce’s Einstein artificial intelligence technology, has created its business mainly on various functions of intelligent industrial robots.
The company made headlines last year by creating its own viral marketing stir, particularly when it made one of its robots performs an orchestra in Italy in the company of the well-known tenor Andrea Bocelli.
“We’re using AI combined with unique hardware to create a completely unique market,” said Spiesshofer to Benioff.
AI use cases exceed the entertainment value or robots performing a Verdi opera in front of a rapturous Italian audience. South African vehicle auction company, Auction Nation, relies on artificial intelligence to vend salvaged cars that have been sourced from leading insurers.
Through pictures of the damaged vehicles, Auction Nation implements Einstein Discovery and Einstein Vision to create an instant 3D model as well as compare the outcome with cars that had been sold previously for evaluation of those who may purchase them.
“This model isn’t perfect yet. But it’s like a baby’s brain. The model is becoming more and more intelligent,” said Chief Operating Officer Errol Levin during a Dreamforce presentation on Wednesday morning.
A Glimpse of the Future of AI
Salesforce purchased Silicon Valley-based artificial intelligence startup MetaMind. While studying at Stanford as a doctoral student, MetaMind’s CEO Richard Socher carried out extensive research in natural language processing (NLP), computer vision, and deep learning. Currently, Socher serves as Salesforce’s chief scientist. Recently, he provided conference attendees with a sneak peek behind what he considers as the future of AI.
In the computer vision field, Socher showed a set of images including one with a little girl holding an umbrella and another sitting on a bench.
The computer could identify the girl seated on the bench and the other one holding an umbrella successfully.
In another instance, a cat’s stripes were correctly identified. Socher said: “We’re seeing more of these visual capabilities actually making it into production.”
The main focus of Salesforce’s research team is currently on NLP. This is not a surprise considering Socher ’s academic background.
Bryan McCann is one of the members of Socher’s research team. He joined the company during the MetaMind acquisition. McCann was also a student at Stanford as well as a course assistant for an AI specialist Andrew Ng.
Recently, McCann presented the outcomes of NLP work, which showed considerable progress in the potential of computers understanding language context.
The aim of the research by Salesforce’s team was completing decaNLP, which is a new benchmark that calls for the need to perform 10 disparate natural language programming roles.
He also said that the NLP solution created by the company’s team can now execute all 10 tasks relatively well through developing a multitask language model.
McCann said: “we took 10 of the hardest tasks we could find in NLP, and we used the natural language decathlon to guide our decisions.”
The outcomes were intriguing. McCann displayed how the Salesforce model could feed the convoluted text, particularly that of an extensive corporate press release. McCann said: “This model is able to do a lot of different things. It’s how we can unify anything in NLP.”
How all this can be converted into business success for Salesforce. However, the company displays no sign of ceasing its exploration of the AI vehicle.
Socher said: “We see a future that is conversational, contextual and intuitive”. It’s also competitive. Salesforce provided a clear message that it plans to be a leading player.
Source SiliconAngle
