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Episode Summary: We receive a lot of interest from business leaders in the domain of data enrichment, and we've executed on a few campaigns for these businesses. At the same time, our audience seems particularly interested in the collection of data to train a bespoke machine learning algorithm for business, asking questions related to how to get started on data collection and from where that data could come.

After plenty of deliberation, web development and research, we’ve finally rebranded to Emerj Artificial Intelligence Research.
I’m glad I finally won’t get any more “so when are you rebranding?” emails.
It sure did take more effort and development work than I had expected (lots of new features / functionality to build out), but it was well worth it.
My goal with this article is to provide our users and readers with a full breakdown of what’s new, and what to expect moving forward. The article below is broken down into the following sections:

We have identified three areas in finance where companies are applying AI to solve real business problems: fintech, regtech, and suptech.

Several factors have contributed to the advancement of AI in the pharmaceutical industry. These factors include the increase in the size of and the greater variety of types of biomedical datasets, as a result of the increased usage of electronic health records.

The clinical trial is a foundational pillar of the pharmaceutical drug discovery process. Essentially, clinical trials are research studies which seek to determine if a medical treatment or device is safe and effective for humans. While the pharmaceutical drug industry has experienced some fluctuations it remains a profitable market. Global prescription drug expenditures are estimated to reach nearly $1.5 trillion by 2021 according to Quintiles IMS Holding.  

In our previous report, we covered the current use cases for AI in construction and building. As of now, numerous companies claim to assist building maintenance managers in aspects of their roles from optimizing energy usage in building to improving the comfort of building occupants.

Episode Summary: Over the last year, we've covered a lot of marketing applications, including a survey of the landscape of machine learning in marketing applications and which industries will be affected first. But marketing doesn't tell the whole story when it comes to B2B sales. At some point, we need to take these clicks and turn them into appointments, for example.

With the entrance of artificial intelligence and its capabilities of recognizing temperature, vibration, and other factors from sensors pre-built into machinery and vehicles, business leaders in heavy industry might be interested in the possible opportunities of predictive and preventative maintenance applications.

Before getting into this report, we have to inform readers that none of the companies discussed below claim to offer software that provides diagnostics, except Cognoa, which has FDA approval to call itself a diagnostic tool. We suspect this is because these companies are not legally allowed to do so. We usually don't refer to a dictionary to determine what constitutes a concept, preferring to create our own informed definitions, such as in our What is Machine Learning? piece, but Merriam Webster defines "diagnosis" as the following: "the art or act of identifying a disease from its signs and symptoms."

One highly sought after engineering role at major tech companies today is the natural language processing, or NLP, engineer.