viralamo

Menu
  • Technology
  • Science
  • Money
  • Culturs
  • Trending
  • Video

Subscribe To Our Website To Receive The Last Stories

Join Us Now For Free
Home
Technology
Salesforce’s Einstein platform is now serving over 80 billion predictions per day
Technology

Salesforce’s Einstein platform is now serving over 80 billion predictions per day

25/11/2020

In September 2016, Salesforce launched Einstein, an AI platform to power predictions across all of the company’s cloud-hosted products. Just over four years after Einstein’s debut, Salesforce says the platform is now delivering more than 80 billion AI-powered predictions every day, up from 6.5 billion predictions in October 2019.

Forrester Research recently wrote that companies “have to rebuild their businesses, not for today, or even next year, but to prepare to compete in an AI-driven future.” Reflecting this changing landscape, IDC expects global spending on AI to more than double to $110 billion in 2024, up from $50 billion in 2020.

Salesforce asserts that Einstein is poised to drive a substantial portion of this growth. Einstein’s predictions can include internal and customer service answers for a given use case, like when to engage with a sales lead, how likely an invoice is to be paid, and which products to recommend to bolster sales. For instance, outdoor apparel and lifestyle brand Orvis taps Einstein to develop personalized conversations with its online shoppers. Internet Creations, a business technology and consulting firm, is using Einstein to forecast long- and short-term cash flow during the pandemic. And outdoor apparel retailer Icebreaker is leveraging Einstein to suggest products for new and existing target audiences.

Beyond the top-line prediction milestone announced today, Salesforce reports a 300% increase in Einstein Bot sessions since February of this year — a 680% year-over-year increase compared to 2019. That’s in addition to a 700% increase in predictions for agent assistance and service automation and a 300% increase in daily predictions for Einstein for Commerce in Q3 2020. As for Einstein for Marketing Cloud and Einstein for Sales, email and mobile personalization predictions were up 67% in Q3, and there was a 32% increase in converting prospects to buyers using Einstein Lead Scoring.

Salesforce also says Einstein Search is fielding more than 1.5 million natural language searches per month, which works out to 1.5 natural language searches every second. It’s also delivering more than 100 million tailored keyword searches per month.

The Einstein platform is the purview of Salesforce Research, a unit previously led by former Salesforce chief scientist Richard Socher. (Socher, who joined Salesforce through the company’s acquisition of MetaMind in 2016, left in July 2020.) To train its underlying algorithms, Salesforce Research’s hundreds of data scientists draw from sources that include the anonymized content in emails, calendar events, tweets, Chatter activity, and customer data. Salesforce says innovations in Einstein arise from scientific investigations into computer vision, natural language models, translation, and simulation.

Einstein’s voice services recently underwent a reorganization with Salesforce’s decision to shut down Einstein Voice Assistant and Voice Skills in favor of the newly released Salesforce Anywhere app. At the time, a company spokesperson told VentureBeat that voice capabilities remained “a priority” for Salesforce and that the products it’s discontinuing will inform the development of “reimagined” functionality focused on productivity and collaboration.

Source link

Share
Tweet
Pinterest
Linkedin
Stumble
Google+
Email
Prev Article
Next Article

Related Articles

2020 will be a big year for online childcare — here are 7 startups to watch
TechCrunch ist Teil von Verizon Media. Klicken Sie auf ‘Ich …

3 unicorn takeaways from the Casper and One Medical IPOs

Beat Saber is now an Oculus studio after Facebook acquisition
TechCrunch ist Teil von Verizon Media. Klicken Sie auf ‘Ich …

OctoML raises $15M to make optimizing ML models easier

Leave a Reply Cancel reply

Find us on Facebook

Related Posts

  • Lyft releases Flyte, a platform for maintaining AI workflows
    Lyft releases Flyte, a platform for maintaining …
    07/01/2020
  • The connected battlespace, part two: The fault in our (joint) stars
    The connected battlespace, part two: The fault …
    08/02/2021
  • MIT CSAIL’s radars map hidden features to help driverless cars navigate snowy terrain
    MIT CSAIL’s radars map hidden features to …
    24/02/2020
  • BMW develops AI-powered big data hub with AWS to boost manufacturing efficiency
    BMW develops AI-powered big data hub with …
    08/12/2020
  • Dangerous SHA-1 crypto function will die in SSH linking millions of computers
    Dangerous SHA-1 crypto function will die in …
    28/05/2020

Popular Posts

  • Verizon’s nationwide 5G will only be a “small” upgrade over 4G at first
    Verizon tells users to disable 5G to …
    01/03/2021 0
  • 10 Best Ancient Structures We Still Don’t …
    01/02/2021 0
  • Top 10 Blockchain Technologies – Listverse
    01/02/2021 0
  • 10 Best Theories That Explain The Bermuda …
    01/02/2021 0
  • Ars Technicast special edition, part 2: Open systems and the “joint force”
    Ars Technicast special edition, part 2: Open …
    01/02/2021 0

viralamo

Pages

  • Contact Us
  • Privacy Policy
Copyright © 2021 viralamo
Theme by MyThemeShop.com

Ad Blocker Detected

Our website is made possible by displaying online advertisements to our visitors. Please consider supporting us by disabling your ad blocker.

Refresh