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Accelerating Machine Learning Adoption in the Automotive Industry

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Accelerating Machine Learning Adoption in the Automotive Industry

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Accelerating Machine Learning Adoption in the Automotive Industry

  1. 1. BigML, Inc Accelerating ML Adoption in the Automotive Industry October 2019 Atakan Cetinsoy VP - Predictive Applications, BigML 1
  2. 2. BigML, Inc Machine Learning in a Nutshell 2 Applied ML is primarily about finding patterns in business data, that can be used to make useful business predictions PREDICTIVE MODELS 2
  3. 3. BigML, Inc Automotive Industry Use Case Examples 33 Predictive Maintenance: Will this machine component fail? Forecasting: How much of each vehicle model will we sell next quarter? Supplier Risk: What will be the delivery performance per supplier? Marketing: Which customers show affinity for shared mobility? Finance: Is this transaction fraudulent? Operations: Which manufacturing configurations are optimal to use?
  4. 4. BigML, Inc Programming with Machine Learning • Ultimately, Machine Learning is all about transforming data into models that can be used to automate decision making. 44 ID COUNTRY CITY DAYS SINCE LAST PURCHASE PAGE VIEWS LTV PURCHASE TODAY? xyz US SEA 5 22 1448 Yes abc US PBI 8 9 2330 No def US CLT 20 2 22296 Yes nnx US MIA 4 19 32342 Yes sbd US ANC 1 21 1144 Yes fjm US MSP 5 8 1589 No cft US MSP 6 7 1299 No amt US CLT 14 2 1250 Yes AA US DFW 1 13 1464 No vgg US ATL 3 15 17471 Yes PREDICTIONS BUSINESS DATA ML PLATFORM
  5. 5. BigML, Inc Democratizing Machine Learning — Why Now? 5 Maturity of ML Techniques Cost of Computation Abundance of Data Speed of Computation Easier Tools
  6. 6. BigML, Inc The Economics of Machine Learning • As the unit cost of predictions go down, many facets of decision making will be automated via cheap predictions. • This means redesigning tasks with fewer human predictions, but more human judgment. 6 The Machine Learning Revolution Cheap Predictions + Fast (i.e., milliseconds) + Better: Quantifiable/Near Human-level Error Rates =>
  7. 7. BigML, Inc Early Adopters — Google 7 • "Machine learning is a core, transformative way by which we’re re-thinking how we’re doing everything. We are thoughtfully applying it across all our products, be it search, ads, YouTube, or Play. And we're in early days, but you will see us — in a systematic way — apply machine learning in all these areas." — Sundar Pichai, CEO
  8. 8. BigML, Inc Machine Learning tools are extremely complex Machine Learning is intrinsically complicated 8 Most businesses FAIL at Machine Learning :( is going to revolutionize every industry and every organization BUT... Machine Learning
  9. 9. BigML, Inc9 Machine Learning Challenges
  10. 10. BigML, Inc Hiring Microwave Engineers 10 SOURCE: https://hackernoon.com/why-businesses-fail-at-machine-learning-fbff41c4d5db
  11. 11. BigML, Inc Building a Machine Learning Product 11 Reality https://medium.com/thelaunchpad/the-ml-surprise-f54706361a6c Expectation 10.50 0.25 0.75 SOURCE: https://medium.com/thelaunchpad/the-ml-surprise-f54706361a6c
  12. 12. BigML, Inc ML — Current State in the Automotive Industry 12 • Modest gains of AI/ML deployed at scale in 2018 among OEMs, suppliers, dealers from 7% to 10% in one year. SOURCE: Forbes • Companies applying more measured approach in selecting use cases and projects. • “Scale champions” (3+ at scale projects) better at •Up or re-skilling workforce •AI/ML governance process •Yet 80% still mention AI/ML as a strategic initiative.
  13. 13. BigML, Inc Automotive Vision 2030 13 • Slow (2%) growth in the traditional vehicle sales and related aftermarket services. • Automotive industry revenue to increase by $1.5T (30%) thanks to new business models such as shared mobility and connectivity services. • 10% of cars sold in 2030 will be shared vehicles adding to special purpose fleets and mobility-as-a-service solutions popular in dense urban areas. • Various flavors of EVs will make up to 50% of vehicles! • New competing ecosystems with more diverse players will emerge to deliver a much more integrated customer experience. SOURCE: McKinsey Global Institute • Integrated software and data-driven insights as the connective tissue.
  14. 14. BigML, Inc ML for Automotive — Unfulfilled Potential 14 • Application of Machine Learning can boost pre-tax profits of the industry by 5% conservatively…and up to 16%. • ML has a key role to play in the future of the automotive industry. • Productivity • Operational Efficiency • Customer Satisfaction • Quality IMPROVE • Direct Costs • Customer Churn • Time to Market • Downtime REDUCE SOURCE: Capgemini
  15. 15. BigML, Inc15 Machine Learning: Take II
  16. 16. BigML, Inc Machine Learning Accessibility Revolution 16 SOURCE: https://hbr.org/2019/06/when-ai-becomes-an-everyday-technology “ After years of hype around mysterious neural networks and the PhD researchers who design them, we’re entering an age in which just about anyone can leverage the power of intelligent algorithms to solve the problems that matter to them. Ironically, although breakthroughs get the headlines, it’s accessibility that really changes the world. That’s why, after such an eventful decade, a lack of hype around machine learning may be the most exciting development yet.” — Andrew Moore, Google
  17. 17. BigML, Inc Tale of Two Innovation Approaches 17 AutoML / Standard Workflows • ML-literate Analysts, Developers, Subject Matter Experts, and Decentralized Data Science Staff MLaaS Platform Executive Mandates Acqu-hire Talent Strategic Initiatives Bespoke Systems • Centralized Data Science Staff and IT-led Operationalization on Specialized Computing Platforms and Open Source Tools TOP DOWN / CENTRALIZED BOTTOM UP / GRASSROOTS API-based Deployment Parallel Experiments Coexisting… …for continuous learning! GovernanceShared
  18. 18. BigML, Inc There’s More… 18 • Please visit us at the Thirdware booth to •see a live demo of the BigML MLaaS platform and/or •discuss your specific use case of interest.
  19. 19. BigML, Inc19 FIN
  20. 20. BigML, Inc Key to the Vault — ML Workflows & Automation 2020 Instances Data New Instance Prediction Confidence % ML Algorithm LEARNING OR TRAINING Evaluation Predictive Model SCORING OR PREDICTING • Standardization of the end-to-end process instills consistency, reliability, and collaboration.

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