6. GOOGLE ASSISTANT
• Google Home & Google Allo
• Context-aware responses
• Leverages the other data Google knows about you
• Only available through Google apps so far "This is not a thing that's going to
figure itself out in 2016. It's going to
be a long journey."
– Mario Queiroz,VP Product, Google
7. AMAZON ECHO
• Fun cloud-based platform
• Excellent hardware for far-field voice recognition
• Excellent ASR and getting even better
• Extensible, and now appearing in non-Amazon products
• Very limited capability to have a conversation
• Requires connectivity
8. APPLE SIRI
• Siri coming to MacOS? Already on Apple
Watch,AppleTV, iPad
• Rumors of Echo-like device coming
• Breadth has grown, but capabilities seem stalled
[[Re-confirm after WWDC]]
9. FACEBOOK "M"
• 100% human-powered today
• Goal to be 100% machine-driven in 5 years
• Access to huge database of your interests and those of your friends
• Likely highly driven by selling ads
16. SRIVIRTUAL ASSISTANT ("VPA")
• Deeply conversational
• Well-suited as "Virtual Specialist"
• Custom speech recognition models
• Highly customizable ontologies
• Embedded in numerous platforms
• Can work without the cloud
17. MORE NATURAL
COMMUNICATION
FLOW
Transfer €200 to checking.
From which account?
How does my savings look?
Your savings balance is €2.200.
Should I continue the transfer?
Will there be any fees?
No, your savings account has
unlimited free transfers
OK, go ahead and transfer
the money.
Your €200 transfer from savings
to checking is complete.
20. ONTOLOGY AUTHORING
• Use W3C standards for data from semantic web
• Customizable tools for authoring
• Leverage myriad web APIs for data
• Move much of experience authoring from
engineers to interaction designers
22. SOCIAL INFLUENCES
• Opaque adaptable recommendations
• Leverage huge pool of data in social
networks
• Likely to dramatically improve over time
• Allow for high-value advertising if done well
24. Virtual Assistant Platform
PERSONALIZATION HUB
Present a better experience, personalized
to the user, based on:
• Who the user is
• What the user usually likes
• What state the user is in
• Where and when the interaction with
the user occurs
Context
aware
Emotion
detection
Preference
learning
Biometric
ID
Application