Messengers, Bots and Personal Assistants

Messengers, Bots and Personal Assistants

Konstantin Savenkov, CEO Intento

Data Science Week, Moscow,2016

Top options for any Data Scientist in 2016

1.

2. do something else

Data Science Week, Moscow,2016

Three trends to track

1. The rise of Chat Bots

2. Personal Assistants

3. API / Micro-services

IntelligentApps

More stuffaccessibleto 3rd partysoftware

Data Science Week, Moscow,2016

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

Trend I: The rise of chat bots

Data Science Week, Moscow,2016

2014 2015 2016

(apps, not bots)

NDA

(apps, not bots)

Some scepticism:a lot of money invested low to none revenues low user adoption

Are chatbots any good?NOT when they are trying to implement GUI browsing via chat dialog

Data Science Week, Moscow,2016

YES when 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

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

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2011 2015 20162012 2013 2014

Trend III: API / Micro-services

Service Provider

WWW

3rd partyappAPI

• API Management market CAGR 22% (Forrester)• Google just bought Apigee for $625M

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Web sit

es

Web ap

ps

Native

apps

Chat b

ots

Person

al

assis

tants

IoT

Interface apps Intelligent apps

App Evolution

Robots

(enable to do smth.) (enable to avoid doing smth.)

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Dumb app Intelligent app

Menu Waiter

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Intelligent App

Terminal

NLP/NLU

Reasoning

Service platform

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Data Science Chalenges:

• Understand natural language

• Infer context

• Take decisions

• Cooperate

Terminals• Chat and assistant terminals

• Connector services • Microsoft Bot Framework • API.ai • message.io

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NLP/NLU

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• IBM Watson Language Services

• Microsoft Cognitive Services LUIS

• Google Natural Language API

• WIT.ai

• API.ai

• angel.ai

Reasoning

• Alexa Skill Kit: set of sample queries -> provided API

• Viv: Automatic synthesis of the intent fulfilment pipeline

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)

Data Science Week, Moscow,2016

http://venturebeat.com/2016/08/11/introducing-the-bots-landscape-170-companies-4-billion-in-funding-thousands-of-bots/

Chat bots vs. Assistants

Data Science Week, Moscow,2016

Chatbot paradigm: dumb terminals clever services

Personal Assistant paradigm:

clever terminals dumb services

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Q&A

Konstantin SavenkovCEO Intento

<[email protected]>

Data Science Week, Moscow,2016