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HOT TOPICS
- 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
Analytics
Thought Leaders in Artificial Intelligence: Mike Flannagan, SVP of Analytics, SAP (Part 6)
Sramana Mitra: In your estimate, how are we in getting to that kind of usability of being able to use AI in a highly-leveraged way without having rocket science capabilities in the individuals? Mike Flannagan: I think we’re doing a great job on the consumer side. Amazing work has been done to provide those sorts
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
Building an AI-Driven Sales Optimization Company: Vincent Yang, CEO of EverString (Part 5)
Vincent Yang: We use, what we call, topic modelling to analyze every single news. For example, is this company acquiring the other company? Is this news about conference sponsorship? How do we know how strong an implication is? We have no idea. That’s the point where we have to rely on machine learning. Machine learning
Building an AI-Driven Sales Optimization Company: Vincent Yang, CEO of EverString (Part 4)
Sramana Mitra: I’m going to start asking you very deep questions because I did a startup in the sales lead generation area back in 1997. It used NLP and the whole AI stream. It was a bit early. It was well before the Internet had completely established itself. I know a lot about this area
