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Enterprise Chatbots: Taking a Hybrid Approach to Machine Learning
Björn Gülsdorff, Head of Business Development
@Bjoern_CV @creativevirtual
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Gartner Predicts
Source: Gartner, 2016
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Existing VAs – how to add ML?
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The challengeof
Enterprise Chatbots
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Recap of the Challenges
Integration
Customisation – Domain Knowledge
Compliance (Legal, Security, …)
And ROI Timeline Budget
And Predictability
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Self-Learning - Pitfalls
Machine Learning is Not flexible• Architecture
• Algorithm
• Special cases
Black Box –By design
Garbage in –Garbage out
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And: A noisy Panda is a Gibbon
Panda (57%) „Noise“ Gibbon (99%)
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What‘s missing?
Let‘s think!
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If your agents were quicker
readers…
Would you let them
read chats or would you train them?
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If your agents were multi-taskers…
Should they watch other agents or would you train them?
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Accept Human Knowledge!
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How it worksUnsupervised pre-learning of generic language model
System actions with integration (Classes) defined by humans
Machine Learning against examples
Scenarios defined in flow editor
Examples for classification defined by humans or collected from agent actions
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Hybrid2 Approach
1. Creation of Content• Unsupervised Pre-Learning
• Human curated content
• Supervised Learning
2. Improvement• Alternates from user
interactions
• Feedback from agents
• Retrain
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Finds & Benefits
Small receptive fields
Robust against parameter variations
Only few examples needed
Great results!
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Semantic
StatisticalSurveys
FeedbackLoops
HumanCuration
A hybrid approach of human curation of content and self-learning minimizes the risk in creation, allows the system to continually improve while also giving control over the reliability of virtual agent responses.
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Companies needtoday
Combination of virtual & real
Knowledge management & feedback loop
Complementary technology
Learning capabilities
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Get in Touch with Me
By email:
On Twitter:
@creativevirtual
On the web:
www.creativevirtual.com