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- The Accelerator Conundrum
- The Startup Velocity Question
- Platform as a Service
- Man and Superman
- Web 3.0 = (4C + P + VS)
- The Future: End of Capitalism
- Capitalism 2.0
Thought Leaders in Artificial Intelligence: Mike Flannagan, SVP of Analytics, SAP (Part 5)
Sramana Mitra: Unintended bias has been very intentional in the past. Mike Flannagan: That’s the thing. If you look at the way compensation is generally determined, it’s based on salary history. If you consider the fact that, historically, there was an intended bias, it’s based on a history. If we want to remove that inherent bias,
Thought Leaders in Artificial Intelligence: Mike Flannagan, SVP of Analytics, SAP (Part 4)
Sramana Mitra: In that scenario, if SAP strikes a deal with Spotify and develops that intelligence and then sells it to a variety of retailers, and the retailers help enhance that model, and then if you go back and sell that enhanced model to every single retailer, that becomes a very questionable scenario. Mike Flannagan:
Thought Leaders in Artificial Intelligence: Mike Flannagan, SVP of Analytics, SAP (Part 3)
Sramana Mitra: The Netflix example is not a right example, because Netflix is not a vendor that sells AI software to other people. I think this question is only reasonable when you take into account a vendor who sells any domain-specific AI software to a whole lot of different customers who could be competitors. Netflix
Thought Leaders in Artificial Intelligence: Mike Flannagan, SVP of Analytics, SAP (Part 2)
Sramana Mitra: The job titles become critical because all the search engines and the AI on that side operate on the basis of keywords. Using the right keyword vastly enhances the findability of certain things. Mike Flannagan: Absolutely. Say for example I tell you, “I want you to go find me a data scientist.” You’d
Thought Leaders in Artificial Intelligence: Mike Flannagan, SVP of Analytics, SAP (Part 1)
This is a superb conversation about the trends and directions in which AI is evolving, especially in business applications. Sramana Mitra: Let’s start by introducing our audience to SAP’s artificial intelligence activities. What trends are you seeing? What trends are you leading? Mike Flannagan: The most significant thing that we’re seeing is that people don’t
Thought Leaders in Artificial Intelligence: Diaz Nesamoney, Founder and CEO of Jivox (Part 6)
Sramana Mitra: We do content-based marketing largely. Everybody that we encounter finds us through our content. We essentially run a media property and all the ancillary distribution of our media work. We put in as much finesse as possible into that work. Diaz Nesamoney: If you think about personalization, it’s essentially content-driven. We’re just saying,
Thought Leaders in Artificial Intelligence: Diaz Nesamoney, Founder and CEO of Jivox (Part 5)
Sramana Mitra: Can you walk us through some use cases? You talked about Claritin and the allergy season as one set of identifiers around which you are personalizing. What are some other examples? Diaz Nesamoney: The hotels, for example, are looking at multiple such data points. The loyalty program says a lot about you. They
Thought Leaders in Artificial Intelligence: Diaz Nesamoney, Founder and CEO of Jivox (Part 4)
Sramana Mitra: Talk to us a little bit about all these different data sources. What are the strengths and weaknesses? What level of depth can you find? Diaz Nesamoney: The differences and, arguably, the challenges with data is two-fold. One is some data is essentially not very accurate because it’s based on projections or modeling.
