Thought Leaders in Artificial Intelligence: Shantanu Nigam, CEO of Jvion (Part 2)

Shantanu Nigam: Most of our nurses are in the profession because they care about the patient. When you have a probabilistic system, by design, it will have one patient slip through it and will not be 100% accurate. When the nurses care about the patients so much and they see that one patient slips through,

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Thought Leaders in Artificial Intelligence: Shantanu Nigam, CEO of Jvion (Part 1)

Jvion applies AI to avoidable healthcare problems in patients inside and outside hospitals. Read on for more on a very interesting application. Sramana Mitra: Let’s start by introducing our audience to yourself as well as Jvion.

Thought Leaders in Artificial Intelligence, Sanjoe Tom Jose, CEO of Talview (Part 3)

Sramana Mitra: When you start modeling some of your customer scenarios, what kind of metrics are you discovering? Sanjoe Tom Jose: A key metric that we built around is time-to-hire. Time is critical. Just to give you an example, some of the organizations have hundreds of thousands of people on their payroll.

Thought Leaders in Artificial Intelligence, Sanjoe Tom Jose, CEO of Talview (Part 2)

Sramana Mitra: Let’s double-click down on a number of things. Where in the workflow are you really adding value with artificial intelligence? You may have read my interview with Ashu Garg from Eightfold, which is also an HR tech AI solution. Where is your value-add and how? Sanjoe Tom Jose: Our focus is on helping

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Thought Leaders in Artificial Intelligence, Sanjoe Tom Jose, CEO of Talview (Part 1)

We’ve been covering AI in the HR tech space. You may have read our Eightfold AI story. Talview is another application in the same space. Sanjoe also points to possible white spaces you can look into. Sramana Mitra: Let’s start by having you introduce yourself and Talview to our audience. Sanjoe Tom Jose: I’m one

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Thought Leaders in Artificial Intelligence: Florian Quarre, Chief Revenue Officer, Exponential AI (Part 3)

Florian Quarre: The final use case is automated decision making. We’ve gone through defining the data meaning and dictionaries. We’ve gone through digitizing data. The last stage is executing on the data and start making decisions. One of the use cases that we help enable is making decisions on whether a claim should be paid

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Thought Leaders in Artificial Intelligence: Florian Quarre, Chief Revenue Officer, Exponential AI (Part 2)

Florian Quarre: We do have affinity to healthcare, finance, and retail primarily because we try to mix together the techno-functional aspects. On the functional side, quite a few of us either have past experience in healthcare, finance, or retail. That allows us to understand the problem. It’s easy for us to relate to the problems

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Thought Leaders in Artificial Intelligence: Florian Quarre, Chief Revenue Officer, Exponential AI (Part 1)

In this segment of TLAI, we discuss use cases in life sciences, healthcare, and retail. Sramana Mitra: Let’s start by introducing our audience to yourself as well as to Exponential Machines. Florian Quarre: I operate primarily in the field of healthcare technology. I have quite recently joined Exponential AI. Exponential AI is an AI platform

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