How AI Revolutionizes Robotics and Automotive Industries

Shohei Hido Chief Research Officer

Preferred Networks, Inc.

l  Founded: March 2014

l  Headquarter: Tokyo, Japan

l  Subsidiary: San Mateo, California

l  Company size: 30 engineers & researchers

l  Investors: NTT (Oct. 2014), FANUC (Sep. 2015), Toyota (Dec. 2015)

Company profile: Preferred Networks, Inc. (PFN)

Deep Learning (AI technologies)

Industrial IoT

AutomotiveHumanoid Robot

Preferred Networks’ positioning in AI: Industrial IoT

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Consumer Industrial

Cloud

Device

PhotoGameText

Speech

Infrastructure

Factory Robot

Automotive

Healthcare

Smart City

Industry4.0

Industrial IoT �

Google

DeepMindFacebook

Microsoft

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How AI revolutionizes Industrial IoT: Manufacturing and AI companies joining forces l  AI-based intelligence is the key success factor in many industries l  Manufacturers reach to AI technologies for help l  PFN is partnering with the world-leading companies in each industry

–  Toyota

–  FANUC

–  NTT

–  Panasonic

–  NVIDIA

–  Cisco

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Cloud

Local network

Unsupported vehicle

detection

Optical NW

detection

Mobile NW

Traffic infrastructure

Automotive: Intelligent Connected-car Platform

l  Providing different intelligence applications on cars and across infrastructure l  Architecture using road infrastructure and network devices as a Fog layer

5 Intelligent vehicle Intelligent vehicle

Intelligent vehicle

Edge

Fog

Cloud

Automotive Demo: Toyota Self-learning Cars @ CES’16

6 Movie: https://www.youtube.com/watch?v=7A9UwxvgcV0

Silver cars autonomously learned how to avoid obstacles and cars, including manually controlled red car.

Presented at the Toyota booth in the main venue of CES this year

Robotics: Optimized Factory Machines & Zero Downtime l  Integrated intelligence platform from factory level to edge machines level l  AI can help further improve the utility and efficiency of factories

Robotics demo: Intelligent bin-picking robots @ International Robot Exhibition ’15

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Predict success possibility for each candidate point with 3D sensors

8 hours training reaches 90% success rate, the same accuracy with human-guided case

Movie: https://www.youtube.com/watch?v=ydh_AdWZflA

l  Robot tries to pick up cylinders as fast and as accurate as possible l  Deep learning automatically learns which picking point is most likely to

succeed.

Deep IntelligenceTM in-Motion (DIMo): Horizontal AI platform across industries

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Automotive

Fog devices Cloud Edge devices

SensorBee™: Intelligent Streaming ETL for IoT

Manufacturing Medical/healthcare

Oth

ers

will

be

adde

d

Self-driving

ADAS/Map

Connected car

Robot behavior optimization

Factory automation

Predictive maintenance

Diagnosis

Drug discovery

Personalized medicine

Machine learning Deep Learning Statistics

Computer vision

Detect/Track/Recognize

Reinforcement learning

Distributed/Curriculum

Time-series RNN /

Representation

Sensor fusion

Multi-modal

Feedback/Action …

Libr

arie

s

DIM

o

Summary l  Artificial Intelligence increasingly creating tremendous opportunities

not only for consumer products/services but also in industrial applications

l  PFN is collaborating with Toyota, FANUC, and others to integrate

deep learning capabilities into automotive and robotics systems

l  PFN is looking for partnership in Europe –  Joint R&D or OEM collaborations w/ solid business plan

l  PFN is looking for top talent (https://www.preferred-networks.jp/job) –  Researchers: Machine Learning, Robotics, Computer Vision, Bio-healthcare

–  Engineers: Distributed Systems, Embedded Device, Data Analytics

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