ARTIFICIAL INTELLIGENCE AT BOSCH

Transcription

1 ARTIFICIAL INTELLIGENCE AT BOSCH HOW BIG DATA IMPROVES QUALITY AND EFFICIENCY MAY 18 TH, DR. LOTHAR BAUM BOSCH CENTER FOR ARTIFICIAL INTELLIGENCE

2 Two Major Drivers 1. Hyper-exponential growth of available data 2. Algorithmic break-throughs and exponential growth of available compute power error rate [%] typical human error rate GoGlobe, 2016 Every two days, we re now collecting as much data as mankind has collected until the end of last century! Eric Schmidt, 2010 (former Google CEO) today time [year] Deep neural networks ( deep learning ) today out-perform humans in key cognition tasks Exponential increase in machine learning research, publications, and break-through research results 2

3 Mining the Value in Big Data billion GB stored digitally in 2017 Amount of stored data (log scale) analog storage 2007 digital storage t The Three V s of Big Data: Volume Velocity Variety 1mil. records ( 50GB) Data size Big Data current processing capabilities Data volume at Bosch >> 100 million GB in 2016 Home appliances: >14 GB/year Automotive diagnostics: > GB/year Connected vehicles: > GB/year Smart grids, finance solutions: >5 000 GB/year 10MB/sec Analysis rate Automotive field data: > GB/year 3 source: Intrinsic Advantage, Inc; 2016 Big Data Definition : data beyond current processing capabilities: > 1 mil. records, analysis rate > 10MB/sec Video surveillance and retail analytics: > GB/year (listing not meant to be complete)

4 Break-Throughs in Training Deep Neural Networks ILSVRC: ImageNet Large-Scale Visual Recognition Competition Classification of 1000 different objects score board leaders: 8/2014 Google, 1/2015 Baidu, 2/2015 Microsoft examples: anemone fish mask Error Rate [%] blue: classical computer vision algorithms Key Enablers: Increased compute power (GPUs) Availability of large data sets for training Algorithm advancements purple: Deep Learning red: Humans 4

5 Machine Learning a Core Element of AI Artificial Intelligence Machine Learning (technology clusters and typical applications) (Deep) Neural Networks Deduction, Reasoning Perception Tasks Cognitive Assistants Robotics Knowledge Representation Decision Support Probabilistic Inference Reinforcement Learning Self-Calibrating Factory Self-learning Controls Action Planning 5

6 Example: Scrap Reduction and Quality Prediction End-of-Line Testing Warehouse kpa pressure related quality claim pressure & pressure control related claims quality claim mm 6

7 Example: Scrap Reduction and Quality Prediction Big Data can get messy! 23 databases 3'000'000 parts shipped p.a. kpa >70 part types >30 different test layouts >17 billion measurements over 10 years Use Case performance metrics: may scrap 3 good parts for one correctly identified bad part TB model : FB model = 1:3 100 relevant claims p.a. Tricky algorithmic problem! pressure related quality claim mm Reduced generation of scrap improves efficiency and resource utilization Quality prediction reduces low-mileage failures and warranty claims 7

8 Example: Analysis of ESP Field Data Finding the business case can be a challenge! Field data reveals actual usage of ESP pump BMW E60 (5-Series) data data collected since '000 vehicles Every Brake Event with odometer reading, speed, braking pressure, braking duration, and many more features Allows to optimize pump specifications higher manufacturing efficiency adding new ESP features without having to update pump specs Allows to reduce testing effort 8 CR/PJ-AI-KPC CE-DM May 2017

9 Example: Community-Based Parking vehicle data hmi data OEM X backend vehicle data parking services Bosch backend vehicle data hmi data OEM Y backend vehicle data parking services Community-based parking services AI system provides predictive and real-time occupancy of parking spaces Eliminates long searches for parking spaces -> save fuel and time, reduces emissions Productivity increase for OEMs: shared data set increases prediction accuracy and driver satisfaction 9

10 Bosch Center for Artificial Intelligence Bosch combines deep expertise in engineering, manufacturing and IoT with cutting-edge AI know-how. Bosch Center for Artificial Intelligence centralizes and expands on decades of machine learning, computer vision, and language expertise at Bosch. Currently ~100 experts located in Bangalore, Stuttgart, and Palo Alto; $300 mio investment over 5 years. Our mission is to build best-in-class artificial intelligence knowledge at Bosch, across all products and maturity stages. We strive to enable design and implementation of smart, connected and learning products. 10

11 THANK YOU! Dr. Lothar Baum Bosch Center for Artificial Intelligence BCAI AI Enablement Robert Bosch Campus Renningen lothar.baum@de.bosch.com