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Machine to Machine
Communication
in the AI Age
Konstantin Savenkov
Intento, Inc.
Data Science Weekend, Moscow, 2017
It’s not about SkyNet
It’s about business
and should be solved
Data Science Weekend, Moscow, 2017
New Digital Economy
MAIN FACTORS
cheaper information search
cheaper communication
MAIN OUTCOMES
more scale
digital transformation
more room in value chains
1995-…
Data Science Weekend, Moscow, 2017
New AI Economy
2016-…
MAIN FACTOR
cheaper decision making
MEANING
data collection, storage and processing
risk management
decision delegation,
implementation and monitoringData Science Weekend, Moscow, 2017
New AI Economy
2016-…
EFFICIENCY
for business built around decisions:
mortgage, insurance etc
AI TRANSFORMATION
business processes rebuilt around
decision-making automation
NEW MARKETS
more room in value chains
Data Science Weekend, Moscow, 2017
Decision-making in
XX
few trusted information sources
in-house analysts and experts
few trusted partners on pre-paid contracts
planning everything ahead
Data Science Weekend, Moscow, 2017
Decision-making in
XXIreal-time information discovery
outsourced analysts and experts
on-demand services with instant gratification
in situ decision making
COOPERATION
more
better
faster
cheaper
Data Science Weekend, Moscow, 2017
Would machines
cooperate like we
humans do, but
better?
Data Science Weekend, Moscow, 2017
?
Machine cooperation
TODAY
few hardwired integrations
no machine-readable documentation
custom pre-paid contracts and ToS
Data Science Weekend, Moscow, 2017
How many humans does it take
to make two programs talk?
Client App Service
Provider
Discover
API
Read
API docs
Write
integration
code
Maintain
integration
$394Bn
System Integration
Market*
$35Bn
Custom Software
Integration Market*
*2017 projection by Gartner Data Science Weekend, Moscow, 2017
How many humans does it take
to make two programs talk?
Client App Service
Provider
Discover
API
Read
API docs
Write
integration
code
Maintain
integration
+ legal + billing
Data Science Weekend, Moscow, 2017
Typical solutions
Custom integrations in private cloud
IPaaS (cloud integration for public services)
Crowdsourcing (service platforms)
are based on
manual directories
Unlikely to work for “50Bn connected devices by 2020”
Data Science Weekend, Moscow, 2017
Like it was in early web
Personal
bookmarks
Curated
directories
Automated
search
but…
Data Science Weekend, Moscow, 2017
APIs are not documents,
delivery means not
reading,
but interacting
HERE COMES AI!
Data Science Weekend, Moscow, 2017
Two interesting projects
Viv Labs, acquired by Samsung in 2016: synthesises
middleware code for third-party services integrated to
the platform
Microsoft/Cambridge DeepCoder: combines code
samples from other programs to reach its goal
Data Science Weekend, Moscow, 2017
Two interesting projects
Viv Labs, acquired by Samsung in 2016: synthesises
middleware code for third-party services integrated to
the platform
Microsoft/Cambridge DeepCoder: combines code
samples from other programs to reach its goal
Intento: API Integration Platform, powered by
“artificial engineers”
THREE!
Data Science Weekend, Moscow, 2017
INTENT
Client
software
translate
CONTEXT
text
to
Intento Service Platform accepts requests with an intent and its context, routes
them to the appropriate API, receives the answer and translates it back to the
intent domain.
Service
providers
Microsoft Cognitive
Services
IBM Watson
Google Cloud Services
…
Indie providers
System
of Intents
Routing &
Integration
Billing
Data Science Weekend, Moscow, 2017
Focused on AI Services
machine translation
image recognition
voice synthesis
OCR
et ceteraWHY?
multiple providers per intent
arms race between service providers
context-based relevance
(currenly)
What it has to do with
Machine to Machine
Communication?
powered by “artificial engineers”, not manual
ideally, any new public service is integrated to the
platform in a matter of seconds, much like Google
does to websites
“standard library” of intents may be used as a lingua
franca for “I need to to do…” between machines
Please, Oh Please!
If you are interested in either
using the Intento Platform or
submitting your APIs, fill out
the form at
https://inten.to/api-platform
Q&A
Konstantin Savenkov
CEO Intento
<ks@inten.to>
Data Science Weekend, Moscow, 2017

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Machine to Machine Communication in the AI Age

  • 1. Machine to Machine Communication in the AI Age Konstantin Savenkov Intento, Inc. Data Science Weekend, Moscow, 2017
  • 2. It’s not about SkyNet It’s about business and should be solved Data Science Weekend, Moscow, 2017
  • 3. New Digital Economy MAIN FACTORS cheaper information search cheaper communication MAIN OUTCOMES more scale digital transformation more room in value chains 1995-… Data Science Weekend, Moscow, 2017
  • 4. New AI Economy 2016-… MAIN FACTOR cheaper decision making MEANING data collection, storage and processing risk management decision delegation, implementation and monitoringData Science Weekend, Moscow, 2017
  • 5. New AI Economy 2016-… EFFICIENCY for business built around decisions: mortgage, insurance etc AI TRANSFORMATION business processes rebuilt around decision-making automation NEW MARKETS more room in value chains Data Science Weekend, Moscow, 2017
  • 6. Decision-making in XX few trusted information sources in-house analysts and experts few trusted partners on pre-paid contracts planning everything ahead Data Science Weekend, Moscow, 2017
  • 7. Decision-making in XXIreal-time information discovery outsourced analysts and experts on-demand services with instant gratification in situ decision making COOPERATION more better faster cheaper Data Science Weekend, Moscow, 2017
  • 8. Would machines cooperate like we humans do, but better? Data Science Weekend, Moscow, 2017 ?
  • 9. Machine cooperation TODAY few hardwired integrations no machine-readable documentation custom pre-paid contracts and ToS Data Science Weekend, Moscow, 2017
  • 10. How many humans does it take to make two programs talk? Client App Service Provider Discover API Read API docs Write integration code Maintain integration $394Bn System Integration Market* $35Bn Custom Software Integration Market* *2017 projection by Gartner Data Science Weekend, Moscow, 2017
  • 11. How many humans does it take to make two programs talk? Client App Service Provider Discover API Read API docs Write integration code Maintain integration + legal + billing Data Science Weekend, Moscow, 2017
  • 12. Typical solutions Custom integrations in private cloud IPaaS (cloud integration for public services) Crowdsourcing (service platforms) are based on manual directories Unlikely to work for “50Bn connected devices by 2020” Data Science Weekend, Moscow, 2017
  • 13. Like it was in early web Personal bookmarks Curated directories Automated search but… Data Science Weekend, Moscow, 2017
  • 14. APIs are not documents, delivery means not reading, but interacting HERE COMES AI! Data Science Weekend, Moscow, 2017
  • 15. Two interesting projects Viv Labs, acquired by Samsung in 2016: synthesises middleware code for third-party services integrated to the platform Microsoft/Cambridge DeepCoder: combines code samples from other programs to reach its goal Data Science Weekend, Moscow, 2017
  • 16. Two interesting projects Viv Labs, acquired by Samsung in 2016: synthesises middleware code for third-party services integrated to the platform Microsoft/Cambridge DeepCoder: combines code samples from other programs to reach its goal Intento: API Integration Platform, powered by “artificial engineers” THREE! Data Science Weekend, Moscow, 2017
  • 17. INTENT Client software translate CONTEXT text to Intento Service Platform accepts requests with an intent and its context, routes them to the appropriate API, receives the answer and translates it back to the intent domain. Service providers Microsoft Cognitive Services IBM Watson Google Cloud Services … Indie providers System of Intents Routing & Integration Billing Data Science Weekend, Moscow, 2017
  • 18. Focused on AI Services machine translation image recognition voice synthesis OCR et ceteraWHY? multiple providers per intent arms race between service providers context-based relevance (currenly)
  • 19. What it has to do with Machine to Machine Communication? powered by “artificial engineers”, not manual ideally, any new public service is integrated to the platform in a matter of seconds, much like Google does to websites “standard library” of intents may be used as a lingua franca for “I need to to do…” between machines
  • 20. Please, Oh Please! If you are interested in either using the Intento Platform or submitting your APIs, fill out the form at https://inten.to/api-platform