CyberAgent, Inc.

AI(artificial intelligence)

Dec 2015(originally Mar. 2015)Daisuke Minamide

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HAL 9000 -2001: A Space Odyssey-

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sophistication of AIbasic technology infrastructure

Deep Learning

Pattern Recognition

Statistical Analytics

computing power

open source

R&D institution

x

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category of AI

strong AI weak AI

goal: replace a human brain

duplicate a human brain in all purpose and let it perform any intelligence task that a human being can.

keyword: deep learning

goal: narrow and limited intelligence which takes over vertical tasks from a human brain.

mainly recognize a pattern from data a machine already experienced (big data).

a good example is Siri by Apple. keyword: machine learning

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research institution of AI

watson:a cognitive system which

won at quiz show, Jeopardy

project adam: image recognition

OAK4: warehouse robot

deepface: face recognition AI for tagging on picture

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Application of AI

automation(robotics)agent service (concierge)

security

auto drive(google)drone delivery(amazon)security robot(knightscope)

Siri (apple)google voice(google)

fraud detection(palantir)voice recognition(barclays)

prediction/problem solving entertainment

media

automatic writing(AP)Evernote Context(evernote)

deep blue:chess(IBM)Shogi(将棋) AI

Miku Hatsune AI project

business intelligence(Sentient)stock trading(Binatix)

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vc investment in AI

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DeepMind

deepmind

Headquarters: LondonDescription: Artificial intelligence companyFounders: Mustafa Suleyman, Shane Legg, Demis HassabisCategories: SoftwareWebsite: http://deepmind.com

Acquired by Google on Jan, 2014 by $500M

deepmind has created a neural network that learns how to play video games in a similar fashion to humans and neural network that may be able to access an external memory like a conventional Turing machine, resulting in a computer that appears to possibly mimic the short-term memory of the human brain

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AlchemyAPI

AlchemyAPI

Headquarters: Denver, CODescription: AlchemyAPI's web services for real-time text analysis and computer vision give you the intelligence needed to transform unstructured data.Founders: Elliot TurnerCategories: Text Analytics, Big Data Analytics, Big Data, Machine Learning, Artificial Intelligence, Developer APIs, Computer Vision, Natural Language Processing, Enterprise SoftwareWebsite: http://www.alchemyapi.com

Acquired by IBM on Mar, 2015

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Wit.ai

Wit.ai

Acquired by FB on Jan, 2015

Headquarters: Palo Alto, CADescription: Natural Language for the Internet of ThingsFounders: Laurent Landowski, Alex Lebrun, Willy BlandinInvestors: Ycombinator, SV angel, NEA, A16ZCategories: SoftwareWebsite: https://wit.ai

the Wit.ai product lets developers add a few lines of its code to instantly build in speech recognition and voice control. its platform will become the Stripe for voice command APIs

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Scaled Inference

Scaled Inference

a platform the company is building is pattern recognition, anomaly detection, prediction, and predictive ranking, which will be accessible by developers by way of a set of APIs.

Funding Received: $13.6 Million in 2 Rounds from 9 InvestorsMost Recent Funding: $8 Million Series A on October, 2014Headquarters: Palo Alto, CADescription: Scalable General AIFounders: Dmitry Lepikhin, Olcan SercinogluInvestor: Khosla, SVA, Data Collective, FelicisCategories: Software, Machine Learning, Artificial IntelligenceWebsite: https://scaledinference.com/

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Luka.ai

luka.ai

Funding Received: Undisclosed in 1 Round from 1 InvestorMost Recent Funding: Seed on December, 2014 / Undisclosed AmountHeadquarters: San Francisco, CADescription: a mobile app that gives restaurant recommendations in a chat interfaceFounders: Eugenia Kuyda, Philip DudchukCategories: Travel, Restaurants, LifestyleWebsite: https://luka.ai/

current YC batch company(2015w)

places and activities that matter.

Education

Movies

Restaurants

Fitness

Music

Exhibitions

Hotels

Travel

chat interface concierge service. right now restaurant only but will expand other verticals including on demand service.

download here *need us account

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13

Technology - Proprietary User Modeling Drives Personalization

• Interest Graphs describe a user by combining content understanding and user behavior

!

• Interest Graphs form the foundation of easy consumer personalization

!

• Proprietary Vidora technology developed by PhDs from Caltech and Berkeley

Vidora(portfolio)

Vidora, corp

Headquarters: San Francisco, CADescription: Intelligent Consumer Experience OptimizationFounders: Alex Holub, Philip West, Abhik MajumdarCategories: Mobile, Machine Learning, Big Data, AnalyticsWebsite: http://www.vidora.com

company offers a platform which developers can incorporate vidora’s machine learning system through the cloud. with user modeling capability, developer can optimize its website/any kinds of contents for individual user.

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Elon and Gates’ position about AI

“I am in the camp that is concerned about super intelligence,” Gates wrote. “First, the machines will do a lot of jobs for us and not be super intelligent. That should be positive if we manage it well. A few decades after that, though, the intelligence is strong enough to be a concern.”

”I agree with Elon Musk and some others on this and don’t understand why some people are not concerned.”

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“Dubito  ergo  cogito,  cogito  ergo  sum.”

(I  doubt  therefore  I  think,  I  think  therefore  I  am)

-­‐  Rene  Descar=es

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