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Messengers, Bots and Personal Assistants

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My talk on the Bot and Assistant ecosystem at Data Science Week 2016.

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Messengers, Bots and Personal Assistants

  1. 1. Messengers, Bots and Personal Assistants Konstantin Savenkov, CEO Intento Data Science Week, Moscow,2016
  2. 2. Top options for any Data Scientist in 2016 1. 2. do something else Data Science Week, Moscow,2016
  3. 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. 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. 5. 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
  6. 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. 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. 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 Data Science Week, Moscow,2016
  9. 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.) Data Science Week, Moscow,2016
  10. 10. Dumb app Intelligent app Menu Waiter Data Science Week, Moscow,2016
  11. 11. Intelligent App Terminal NLP/NLU Reasoning Service platform Data Science Week, Moscow,2016 Data Science Chalenges: • Understand natural language • Infer context • Take decisions • Cooperate
  12. 12. Terminals • Chat and assistant terminals • Connector services • Microsoft Bot Framework • API.ai • message.io Data Science Week, Moscow,2016
  13. 13. NLP/NLU Data Science Week, Moscow,2016 • IBM Watson Language Services • Microsoft Cognitive Services LUIS • Google Natural Language API • WIT.ai • API.ai • angel.ai
  14. 14. Reasoning • Alexa Skill Kit: set of sample queries -> provided API • Viv: Automatic synthesis of the intent fulfilment pipeline
  15. 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) Data Science Week, Moscow,2016
  16. 16. http://venturebeat.com/2016/08/11/introducing-the-bots-landscape-170-companies-4-billion-in-funding-thousands-of-bots/
  17. 17. Chat bots vs. Assistants Data Science Week, Moscow,2016 Chatbot paradigm: dumb terminals clever services Personal Assistant paradigm: clever terminals dumb services • • • •• • • • • •
  18. 18. Q&A Konstantin Savenkov CEO Intento <ks@inten.to> Data Science Week, Moscow,2016

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