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“Make the real world computable.” |
| Founded: 2014, Tokyo, Japan
Category: Artificial Intelligence/ Robotics Primary office: Tokyo, Japan Core technical team:Tokyo, Japan Status: Private Employees: 251 to 500 Amount raised:USD $147.2million (7 rounds – July 2019) |
OVERVIEW
PERFORMANCE METRICS
ACHIEVEMENTS
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Sells
- Chainer Chainer™ – a core deep learning framework. First to adopt the define-by-run approach that allows developers to build complex neural networks in intuitive and flexible ways.
- CuPy CuPy™ – open-source matrix library accelerated with NVIDIA CUDA.
- Optuna™ – an open-source automatic hyperparameter optimization framework, automates the trial-and-error process of optimizing the hyperparameters. It automatically finds optimal hyperparameter values based on an optimization target
- Industrial and Personal Robots
- Bio & Healthcare – focuses on omics analysis, medical image analysis, and compound analysis using deep learning.
- Supercomputers – develops chips for artificial intelligence for companies like Google, Huawei Technologies, etc.
Channels
- Partners with Toyota (R&D based Human Support Robot (HSR) robotics platform), Intel (open source framework for deep learning), etc.
- Open source DevOps community
Competencies
- Artificial Intelligence – Machine learning, Deep learning
- Research & Development
- Data analytics, Edge-heavy computing, Distributed intelligence.
Distinct AI Features
Type
- Deep learning, Machine learning
AI use
- Robotics
- Joint research and development of object recognition technologies and vehicle information analysis, which are required for the development of autonomous driving and connected cars.
- Visual Inspection: proprietary deep learning model offering high accuracy and flexibility for building visual inspection systems.
- Sports Analytics develops play analytics and pose estimation algorithms for sports using deep learning technologies
AI useRate of return on customer’s investment to make AI work
Immediate:
- Novel and innovative products as well as solution and/or improvements to business processes.
Long term:
- Position to be leader in AI-driven solutions for the future
Databases
- Device and Tools-generated data
Quantum Computing
- N/A
Resources
Assets
- Diverse Industry robotic and AI solution projects
- R&D Collaboration with Toyota, Intel,
Processes
- Research, development & collaborations
- Open source development
Priorities
- Further diversify operations and explore new industries
- Increase Revenue
References
- Preferred Networks. https://preferred.jp/en/
- Bloomberg.2018. https://www.bloomberg.com/news/articles/2018-05-16/this-2-billion-ai-startup-aims-to-teach-factory-robots-to-think
- Crunchbase. 2020. https://www.crunchbase.com/organization/preferred-networks
- Yamada, A. 2020.Japan AI unicorn Preferred Networks seeks greener pastures. https://asia.nikkei.com/Business/Startups/Japan-AI-unicorn-Preferred-Networks-seeks-greener-pastures#:~:text=Preferred%20Networks%20was%20worth%20an,of%20%241%20billion%20or%20more.
Contributors
- Fatena El-Masri
- Yinka Olanrewaju-Olawepo