Conversational Banking Is a Competitive Necessity in a Remote-Everything World

  • “For financial institutions that have yet to adopt conversational banking, the potential user base already exists. Nearly two-in-five U.S. adults are now users of smart speakers, such as Amazon Alexa or Google Home.
  • In November 2020, eMarketer estimated that 128.0 million people in the US used a voice assistant – 44.2% of internet users and 38.5% of the total population.
  • The aggregate potential cost savings for banks from AI applications is estimated at $447 billion by 2023, according to Autonomous Next research. Notably, the front office (conversational banking) and middle office savings account for $416 billion of that total.”

https://www.finextra.com/blogposting/19995/conversational-banking-is-a-competitive-necessity-in-a-remote-everything-world

Baidu’s Stronger-Than-Expected Outlook Validates AI Push

  • “The internet giant has over the years sunk billions of dollars into areas from language learning to voice interaction and autonomous driving, betting on smart devices and vehicles of the future. Now, aided by years of investment and Beijing’s bid to build smart nationwide infrastructure, these efforts are finally paying off.
  • Sales last quarter rose 4.8%, the fastest pace in 2020, fueled by a 52% increase in its non-advertising businesses like AI cloud.”

https://www.google.com/amp/s/finance.yahoo.com/amphtml/news/baidu-revenue-beats-estimates-core-214048814.html

Forget coding, you can now solve your AI problems with Excel

  • “While I’ve been using Excel’s mathematical tools for years, I didn’t come to appreciate its use for learning and applying data science and machine learning until I picked up Learn Data Mining Through Excel: A Step-by-Step Approach for Understanding Machine Learning Methods by Hong Zhou.
  • There’s a chapter that delves into the meticulous creation of deep learning models. First, you’ll create a single layer artificial neural network with less than a dozen parameters. Then you’ll expand on the concept to create a deep learning model with hidden layers.
  • In the last chapter, you’ll create a rudimentary natural language processing (NLP) application, using Excel to create a sentiment analysis machine learning model. You’ll use formulas to create a “bag of words” model, preprocess and tokenize hotel reviews and classify them based on the density of positive and negative keywords.”

https://thenextweb.com/syndication/2021/01/16/forget-coding-you-can-now-solve-your-ai-problems-with-excel/?scid=lAWQQPRS8c&utm_content=socialchampbGaQ5eNNFl&utm_medium=social&utm_source=facebook.com&utm_campaign=socialchamp.io

How Traditional Banks can Stay Ahead of Fintech Firms with Conversational AI

  1. “Customers Want Quick Contactless Payment Methods
  2. Legacy Systems Costs Banks Huge Chunks of Money
  3. Offering Omnichannel Banking Services
  4. Conversational AI is a Key to Increase Revenue
  5. Conversational AI Adoption is a Survival Imperative for the Banks
  6. Banks can Avail Enterprise-Grade Security
  7. Conversational AI Helps Banks Adapt Quickly”

https://www.google.com/amp/s/readwrite.com/2020/12/11/how-traditional-banks-can-stay-ahead-of-fintech-firms-with-conversational-ai/amp/

Artificial intelligence app will use Alexa to enable people to talk to deceased relatives

Credit: Alamy
  • “Microsoft has applied for a ­patent for the app, which could operate through smart devices like Amazon Alexa or Google Nest.
  • It uses recordings of them to copy their style, diction, tone, voice and intent to make what they say appear to be genuine.
  • Details from their social media accounts and letters could be mixed in to add to the effect.”

https://www.google.com/amp/s/www.the-sun.com/lifestyle/tech/2101492/ai-alexa-talk-dead-relatives/amp/