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Stockbrokerage might be viewed by investors as a traditionally human-based service allowing them to buy and sell equities. When looking at the shift in how stock brokerage is different today compared to the early 2000s, the largest change seems to be in software-based automation. Put simply, a lot of what was being done by humans (such as executing trades, giving advice to investors, discretionary trading) can now be done through software.

Speech recognition is technology that can recognize spoken words, which can then be converted to text. A subset of speech recognition is voice recognition, which is the technology for identifying a person based on their voice.

When contemplating a new venture into AI or machine learning, companies need to take on a number of important considerations that relate to talent, existing data, and limitations. One way executives can judge how successful or appropriate and AI project would be for their company is to examine use cases of businesses that have previously done something similar.

Telehealth (or Telemedicine) is a growing sector of the healthcare industry which has steadily gained traction and formed a profitable sector, according to Transparency Market Research. The market research firm projects that total US revenue will hit $19.5 billion in 2025 up from $6 billion in 2016.

In a study from Researchscape International, 74 percent of 300 marketers surveyed said personalization in this field has strongly helped their clients or companies in advancing customer relationships. It also found that 54 percent said their clients or companies experienced a 10 percent increase in sales, while 13 percent of marketers surveyed reported a more than 30 percent lift.

Back at the beginning of the year, I set out to get a feel for a city in the longitudinal center of the country, between two coastal tech hubs in San Francisco and NYC: Austin. I wanted to find out what made Austin an attractive AI and tech hub the way I had in Boston, Atlanta, Montreal, and Bangalore before it. It turns out the AI startup community in Austin is measurably different than those on the east and west coast, and it stood out to me in the way it was able to offer a quality of life that's rare for fresh-out-of-college talent on the coasts. 

This article is based on a panel discussion facilitated by Emerj (Techemergence) CEO Dan Faggella on the state of AI in the healthcare industry. The panelists were Just Biotherapeutics Chief Business Officer Carolina Garcia Rizo (representing healthcare startups) and Senior Manager for A.I./Machine Learning at Bayer Kevin Hua (representing big pharma). This session was part of the Applied Artificial Intelligence Conference by Bootstraps Labs held in San Francisco on April 12, 2018. The video of the panel is provided below:

Episode Summary: In this episode of the podcast, we interview AIG’s Chief Data Science Officer, Dr. Nishant Chandra, about natural language processing (NLP) for internal and team communication. Dr. Chandra talks about how NLP can help with sharing documents with specific team members whose roles warrant viewing those documents.

With an ongoing nurse shortage in the United States and other areas, startups and global companies have begun developing methods for handling time-consuming responsibilities traditionally held by nurses, ranging from daily operations to diagnosis.

In 2013, a McKinsey report noted that over 85 percent of Amazon sales revenue was generated from personalized recommendations. Since then, the use of personalized recommendations has grown. On average, today’s personalized recommendations account for 27-percent of retail site revenue, according to a recent Salesforce report.