This document discusses trends in messengers, bots, and personal assistants. It outlines three key trends: 1) The rise of chat bots as people spend more time in messaging apps. However, chat bots have had low revenue and adoption so far. 2) The rise of personal assistants as a way for companies to control user behavior and be close to users. 3) The growth of APIs and micro-services as interfaces for applications, with the API management market growing at a 22% CAGR. The document argues that intelligent applications will utilize natural language processing, reasoning, and web services to understand users and assist them.

1. Messengers, Bots and
Personal Assistants
Konstantin Savenkov,
CEO Intento
Data Science Week, Moscow,2016

2. Top options for any Data
Scientist in 2016
1.
2. do something else
Data Science Week, Moscow,2016

3. Three trends to track
1. The rise of Chat Bots
2. Personal Assistants
3. API / Micro-services
Intelligent
Apps
More stuff
accessible
to 3rd party
software
Data Science Week, Moscow,2016

4. Trend I: The rise of chat bots
• 2015: More people in messengers than in
social networks, more time spent in
messengers on mobile than in web and
social networks combined.
• Businesses: follow the audience, need tools
• Messengers: want to earn money without
hurting the audience
• Chat bots: an attempt to turn a messenger
into a smartphone / browser etc
?
Data Science Week, Moscow,2016

5. Trend I: The rise of chat bots
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2014 2015 2016
(apps,
not bots)
NDA
(apps,
not bots)
Some scepticism:
a lot of money invested
low to none revenues
low user adoption

6. Are chatbots any good?
NOTwhen they are trying to
implement GUI browsing via chat dialog
Data Science Week, Moscow,2016
YESwhen they can operate based on a limited
input, just like we humans
100
011011001
101001001001000
110010100001
10110
•GUI-over-Chat is no better than PPP-over-Voice
•e.g. replace existing services with chat interfaces: concierge,
receptionist, waiter, psychoterapist, customer support, assistant
etc

7. manual
Trend II: Personal Assistants
• Another way to be as close to users as possible,
and to control his consumer behaviour
• The next best option after a hardware-locked app
ecosystem, which may be obsolete soon enough
Data Science Week, Moscow,2016
2011 2015 20162012 2013 2014

8. Trend III: API / Micro-services
Service
Provider
WWW
3rd party
app
API
• API Management market CAGR 22% (Forrester)
• Google just bought Apigee for $625M
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9. W
eb
sites
W
eb
apps
N
ative
apps
C
hatbots
Personal
assistants
IoT
Interface apps Intelligent apps
App Evolution
Robots
(enable to do smth.) (enable to avoid doing smth.)
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10. Dumb app Intelligent app
Menu Waiter
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11. Intelligent App
Terminal
NLP/NLU
Reasoning
Service platform
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Data Science Chalenges:
• Understand natural
language
• Infer context
• Take decisions
• Cooperate

12. Terminals
• Chat and assistant terminals
• Connector services
• Microsoft Bot Framework
• API.ai
• message.io
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13. NLP/NLU
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• IBM Watson Language Services
• Microsoft Cognitive Services LUIS
• Google Natural Language API
• WIT.ai
• API.ai
• angel.ai

14. Reasoning
• Alexa Skill Kit: set of sample
queries -> provided API
• Viv: Automatic synthesis of the
intent fulfilment pipeline

15. Service Platforms
• Manual: Google Now / Assistant
• Crowdsourced: Amazon Alexa Skill Kit, Apple
Siri Kit, Viv + a lot in verticals (hotels, taxi etc)
• Automatic: Intento (coming soon)
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16. http://venturebeat.com/2016/08/11/introducing-the-bots-landscape-170-companies-4-billion-in-funding-thousands-of-bots/

17. Chat bots vs. Assistants
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Chatbot paradigm:
dumb terminals
clever services
Personal Assistant
paradigm:
clever terminals
dumb services
•
• •
••
• •
•
• •

18. Q&A
Konstantin Savenkov
CEO Intento
<ks@inten.to>
Data Science Week, Moscow,2016