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TammyPowlas
Active Contributor
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Title: Empathy is a Must for Machine Learning, February Community Call
Abstract: Artificial Intelligence, Machine learning and Predictive Analytics are at a perfect storm and many companies leverage these technologies to transform their organization. These technologies existed for a decade, but they evolved rapidly - machine learning today is not like machine learning of the past. In these session, we will look into these technologies, understand what SAP is to offer and how SAP customers are using these technologies.

Call Recording: Part 1, Part 2

Hosted by: Chris Kernaghan



 

Speakers: Chandran Saravana, Senior Director, Advanced Analytics SAP

Markus Noga, Innovation Network



Figure 1: Source: SAP

Emotions are a big business

Growing market and how enable empathy in machine learning



Figure 2: Source: SAP

Start with empathy for the end user



Figure 3: Source: SAP

What is empathy?



Figure 4: Source: SAP

What are the markers?  Shown in Figure 4

How bring empathy to it - structured and unstructured data



Figure 5: Source: SAP

Why important now?  Computing power

Genome analysis - took days to do



Figure 6: Source: SAP

Early stages for empathy for machine learning



Figure 7: Source: SAP

Use cases for machine learning - teaching, simple math lessons, can be done by a robot



Figure 8: Source: SAP

Goals of empathetic machine learn

Respond intelligently to emotions



Figure 9: Source: SAP

Universal facial expressions

7 primary emotions and other secondary emotions



Figure 10: Source: SAP

4 knowledge approaches are shown in Figure 10



Figure 11: Source: SAP

Algorithms used



Figure 12: Source: SAP

Requires speed and agility



Figure 13: Source: SAP

Definition of digitization is shown in Figure 13



Figure 14: Source: SAP

Digital framework, machine learning is a part of it



Figure 15: Source: SAP

SAP Clea - making enterprise applications intelligence



Figure 16: Source: SAP

Trying to automate knowledge work

Take load off customer service so humans can handle complex situations



Figure 17: Source: SAP

Use cases across SAP



Figure 18: Source: SAP

Use cases



Figure 19: Source: SAP

Roadmap is subject to change



Figure 20: Source: SAP

Apps are for the business users

API's are for the developers

Training infrastructure is for data scientist

 

Questions

Q: Are there differences in training the empathic model versus normal statistical mode

A: Key element is data availability and images

Q: Taking open platforms into the context, how does sap ml pair with the data lakes and all platforms out there beyond vora?

A: Going natively on SAP Cloud Platform; will be natively connected on SAP Cloud Platform

Create machine learning platform partner program; increased openness

Q: Where is data held, privacy/data concerns..

A: data protection is serious; follow German privacy laws, which are strict; linked to SAP Cloud Platform roadmap

Q: How guard against biases?  Creating new ones?

A: Discussing with SuccessFactors colleagues and Business Beyond Bias campaigns and machine learning can contribute

Try to find calibrated data

Q: Are these models pretrained?

Or does the customer have to do their own training?

A: Some things are pre-trained, others are not

Q: Relationship between Clea and Leonardo?

A: Clea will help all SAP apps, including IoT