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Your brain is too small to manage your business


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Presentation that I delivered at "Accelerate AI, Europe 2018" in London on Sept 19, 2018. My focus is on socio-cultural perspective as well as proving information about various tools, vendors and partners available to help companies get started using AI.

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Your brain is too small to manage your business

  1. 1. Your brain is too small to manage your business Christopher Bishop chief reinvention officer improvising careers Accelerate AI, Europe 2018 September 19, 2018
  2. 2. • Historical perspective • Why AI now? • Who can help • How to get started
  3. 3. “AI is the new electricity. Just as electricity transformed industry after industry 100 years ago, I think AI will do the same.” Andrew Ng – Former Chief Scientist of Baidu Co-Chairman, Co-Founder of Coursera, Adjunct Professor at Stanford University
  4. 4. Using machines to solve problems for thousands of years
  5. 5. Charles Babbage The Difference Engine (1822)
  6. 6. 8
  7. 7. 9
  8. 8. 11
  9. 9. Why is AI adoption accelerating now? 13 Big Data Hardware Software
  10. 10. • 90% of world’s data created in last 2 years • 80% of it is unstructured • Annual rate of data creation=16.3ZB
  11. 11. IoT connected devices WW from 2015 to 2025 (in billions)
  12. 12. 16
  13. 13. AI to the rescue! Collect Analyze Act
  14. 14. Devin Wenig CEO, eBay 4 “If you don’t have an AI strategy, you are going to die in the world that’s coming.” SOURCE:
  15. 15. AI in the Enterprise Source: Teradata – Bringing Artificial Intelligence to the Enterprise – October 30, 2017
  16. 16. Top verticals impacted by AI and machine learning • Financial services – machines can manage vast quantities of data to manage portfolios • Healthcare – reading scans, analyzing journals, managing back-end processes • Retail – tracking inventory, managing supply chain • Manufacturing - sensors in machinery, vehicles, production plants predict repairs and maintenance 20
  17. 17. Who can help?
  18. 18. Tools and libraries
  19. 19. •Image/video classification - Amazon Rekognition •Speech recognition – Amazon Alexa •Natural language processing – Amazon Lex •Recommendation engines - MXNet AWS offers tools, training for major use cases
  20. 20. Google • Open-source machine learning library for research, production • APIs for beginners and experts to develop for desktop, mobile, web, and cloud
  21. 21. • Used by 100,000 data scientists at 12,600 organizations • Interfaces connect: • Leading open source deep learning tools with H2O • Framework combines H2O and Spark • Driverless AI - "AI to do AI"
  22. 22. Vendors and partners [NEXT SLIDE]
  23. 23. • Transform data into a powerful asset - NLG • Relevant, intuitive stories delivered at scale “A massive amount of time and effort has been spent in gathering data and no human can look at all of it. Narrative Science offers us opportunities to more efficiently sift through large amounts of data and bring out insights more quickly.” —Craig Muraskin, Managing Director of Innovation, Deloitte IMPACT • Journalism • Marketing • Communications
  24. 24. • World-class legal search engine • Combined with artificial intelligence-driven technology “Casetext has changed my approach to legal research. I used to wait for days and hours for answers using traditional legal research tools, but with Casetext, I can find my best, most on-point case in minutes and seconds.” Sasha Rao, Partner Maynard, Cooper & Gale LLP IMPACT • Legal research • Paralegals • Case preparation
  25. 25. • Conversational AI powering intelligent virtual assistants and enterprise chatbots IMPACT • Call center • Help desk • Customer support
  26. 26. • Provides cargo companies with data cleansing, demand forecasting • Predictive optimization based on data science and AI “Transmetrics finds solutions. They pragmatically clean data and make it usable – and on the way create unexpected benefits for our dispatchers and managers alike.“ Nils Wemhoener SVP Operations Overland, Kuehne + Nagel AG IMPACT • Logistics • Supply chain
  27. 27. UNICORN AI FOCUS Machine learning-based credit risk modeling Deep learning-based drug discovery Machine learning for predictive analysis of IoT data AI to predict and prevent cyber attacks Extracting information from electronic health records m Unicorns offering niche AI solutions
  28. 28. Data collection, cleaning, tagging
  29. 29. Transforming real world data into high quality training data Data cleaning and extraction, 2D and 3D image recognition, comparison, segmentation Data collecting, tagging; model scoring, validation Create training data for computer vision models
  30. 30. Curated datasets
  31. 31. Images, geospatial, sentiment, government, statistics Annotations, labels, bounding boxes, 1ks of categories Large list of public data sets for training Image Processing, Natural Language Processing, and Audio/Speech Processing Data for building computer vision models
  32. 32. • Pick a small project - prediction or analysis to benefit business • Explore four popular use cases based on where you have data: 1. Image/video classification 2. Speech recognition 3. Natural language processing 4. Recommendation engines • Identify vendor’s software to augment your capabilities • Make an existing application smarter or more autonomous • Build, deploy, evaluate, adjust How to get started
  33. 33. 40 “Over the next decade, AI won’t replace managers, but managers who use AI will replace those who don’t.” SOURCE: HBR – July 2017
  34. 34. From one small brain to another… THANKS! @chrisbishop