Era of Artificial Intelligence Lecture 3 Pietro Leo
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This document summarizes a lecture by Pietro Leo on artificial intelligence. Some key points discussed include: - AI can help industries like agriculture, automotive, and healthcare. For agriculture, precision agriculture using AI is discussed. - For science, big data acts as a microscope for the 21st century, enabling analysis like wine DNA tracing. Mapping the microbiome can also help protect from harmful bacteria. - Digital twins of farms can help share insights and data to help farming. AI sensors may also detect foodborne pathogens at home. - In automotive, self-driving vehicles are discussed as well as predictive maintenance using cloud, AI and connected cars. Damage assessment systems can also help standardize
Era of Artificial Intelligence Lecture 3 Pietro Leo
- 1. @pieroleo The Era of Artificial Intelligence Lecture 3 Pietro Leo IBM Italy Executive Architect and thought leader for Artificial Intelligence Chief Scientist for IBM Italy Research & Business IBM Academy of Technology Leadership Member of ISO/SC42 Artificial Intelligence Standardization Committee www.pieroleo.com
- 2. @pieroleo Why do we need the help of Artificial Intelligence?
- 4. @pieroleo Investment in digital is a matter of survive for companies, after digitalization what’s next?
- 5. @pieroleo Source: McKinsey What’s next? For agriculture Precision Agriculture
- 7. @pieroleo For Science, Big Data is the microscope of the 21st century Wine DNA Tracing @pieroleo www.pieroleo.com
- 8. @pieroleo Source: Cornell University - Maize kernal infected with Aspergillus flavus, which produced aflatoxin.http://www.plantpath.cornell.edu/labs/milgroom/Research_aflatoxin.html And http://www.special-clean.com/special- clean/en/mold/mold-lexicon-1.php For science, Big Data is the microscope of the 21st century @pieroleo www.pieroleo.com
- 9. @pieroleo 9 Mapping the microbiome will protect us from bad bacteria. Microbiome Analysis
- 10. @pieroleo 10 Food safety inspectors around the world will gain a new superpower: the ability to understand how millions of microbes coexist within the food supply chain. These microbes—some healthy for human consumption, others not— are everywhere –in foods at farms, factories, and grocery stores. The ability to constantly and cheaply monitor the behaviors of microbes at every stage of the supply chain represents a huge leap in food safety. Microbiome Analysis
- 11. @pieroleo 11 Preliminary scientific evidences https://researcher.ibm.com/researcher/view_group.php?id=9635 By sequencing the genomes of the microbiome, or community of microbes, present in the food we eat, IBM researchers as well as partnering organizations like Mars, Inc., Bio-Rad, and Cornell University are turning the corner to a new and more predictive kind of food testing. This new regimen may allow inspectors to identify dangerous pathogens inhabiting food with better sensitivity well before they make anyone sick. This rapidly evolving field at the intersection of big data and microbiology is built upon the technology of next generation sequencing (NGS), which researchers are using to amass an unprecedented reference database of genomes through an IBM-led partnership called the Consortium for Sequencing the Food Supply Chain. Consortium for Sequencing the Food Supply Chain Preliminary scientific evidences
- 12. @pieroleo 12 #twinning: Farming's digital doubles will help feed a growing population using less resources Digital Farm
- 13. @pieroleo 13 Creating a digital twin or a “virtual model” of the world’s farms could help ready agriculture for new challenges by democratizing farm data, allowing those in agriculture to share insights, research, and materials, and communicate data on farmland and crop growth across the planet, and connect and cross-reference with the food supply chain. Digital Farm
- 14. @pieroleo 14 Preliminary scientific evidences https://ibmpairs.mybluemix.net/ IBM PAIRS Geoscope IBM PAIRS GEOSCOPE is a platform, specifically designed for massive geospatial-temporal data (maps, satellite, weather, drone, IoT), query and analytics services. It frees up data scientists, developers from the cumbersome processes that dominate conventional geospatial-temporal data acquisition and preparation and provides search-friendly ready access to a rich, diverse, and growing catalog of historical and continuously updated geospatial- temporal information
- 15. @pieroleo 15 https://www.ibm.com/blogs/research/2018/09/smarter-farms-agriculture/ IBM Watson Decision Platform for Agriculture A platform that combines data, satellites, mobile phones and sensors with AI capabilities to collect and analyze unstructured, visual data about agricultural land use, from soil chemistry and water supplies, to crop diseases, equipment usage and availability, impending rainstorms, heat waves, and cold streaks - all to deliver on the promise of improved food quality and safety. • Yield History and Forecast for Corn • Disease & Pest Indicators for Corn • High Definition Normalized Difference Vegetation Index (HD-NDVI) for Crop Health Monitoring • High Definition Soil Moisture (HD-SM) Hello Tractor Preliminary scientific evidences
- 16. @pieroleo 16 Dinner plate detectives: AI sensors will detect foodborne pathogens at home. Dinner plate detectives
- 17. @pieroleo 17 https://www.ibm.com/blogs/research/2018/05/ai-authentication-verifier/ IBM Research is currently creating bacteria-detecting sensors that would be a next-generation extension of IBM’s Crypto Anchor Verifier. This optical device, which is currently being tested by businesses from drug stores to construction companies, uses AI and machine learning techniques to analyze microscopic features and “read” the wavelengths emitted by different substances and objects. After scanning a material, a verifier records its unique wavelength and microscopic details on the blockchain, comparing its fingerprint to that of other identical substances. Soon, we’ll be able to stop them in sub-seconds IBM's Next-generation Crypto Anchor Verifier Preliminary scientific evidences
- 18. @pieroleo AI-enabled value opportunity for Automotive Industry According to McKinsey2025 the potential incremental value that will accumulated by AI in Automotive industry will be USD 215 billions (+1.3% per year)
- 19. @pieroleo Self drive vehicle announcements
- 20. @pieroleo TESLA: Autopilot 1 billion of miles
- 21. @pieroleo Waymo 10 milions of miles
- 22. @pieroleo https://techcrunch.com/2018/05/24/uber-in-fatal-crash- detected-pedestrian-but-had-emergency-braking-disabled/ Uber in a fatal crash, Mar 18
- 23. @pieroleo
- 24. @pieroleo
- 25. @pieroleo Cloud + AI + Connected Car = Predictive Maintanance
- 26. @pieroleo
- 27. @pieroleo AI Ding sun bao 2.0: standardize Car Damage Assessment
- 28. @pieroleo Example of Use Case: Car Damage Assessment System from Ding sun bao
- 29. @pieroleo Example of Use Case: Car Damage Assessment System from Ding sun bao Estimated damage: slightly deformed left-rear fender Repair cost: 40$
- 30. @pieroleo 30 Body Mass Index (BMI) Mass (weight - Kg) / height (cm) x height (cm) 18.5 < NORMAL BMI < 24.99 Adolphe Quetelet, 1832
- 31. @pieroleo 31 Practice Pearls: • BMI - Body mass index is a strong and independent risk factor for being diagnosed with type 2 diabetes mellitus • Type 2 diabetes risk may be incrementally higher in those with a higher body mass index • Understanding the risk factors helps to shorten the time to diagnosis and treatment How precise could be a relative “simple” signal
- 32. @pieroleo 32 AI could help Medicine to reduce approximation (this is largely valid to all kind of industries....) The BMI - Body Mass Index is an approximation of our health status, it is inherently a proxy or a condensed information of a huge quantity physiological parameters Bottom line: it is not only a matter of how many data points you consider to take a decision, It is more a matter of how large is the data set you have that approximates the reality
- 33. @pieroleo Leveraging the Explosion of Data in Medicine An Impossible Task Without Analytics and New advanced Artificial Intelligence Computing Models 1000 FactsperDecision 10 100 1990 2000 2010 2020 Human Cognitive Capacity Electronic Health Records (Clinical Data) Internet of Things (Exogenous Data) The Human Genome (Genomic Data) Capturing the Value of Data: Big Changes Ahead Medical error—the third leading cause of death in the US Source: BMJ 2016; 353 doi: http://dx.doi.org/10.1136/bmj.i2139 (Published 03 May 2016) Cite this as: BMJ 2016;353:i2139
- 34. @pieroleo 34 Source: Bipartisan Policy Center, “F” as in Fat: How Obesity Threatens America’s Future (TFAH/RWJF, Aug. 2013)
- 35. @pieroleo 35 Image source: http://personalexcellence.co/blog/ideal-beauty/ Source: Bipartisan Policy Center, “F” as in Fat: How Obesity Threatens America’s Future (TFAH/RWJF, Aug. 2013) Human Digital Twins
- 36. @pieroleo 36 Image source: http://personalexcellence.co/blog/ideal-beauty/ City Lifestyle ZIPcode Costal vs Inland Marital status Generation Location Family Size Gender Income Level Competitors Age Loyalty & Card Activity Revenue Size Life Stages Eductation Legal status Sector Industry Subscriptions Date on Site Wish List Size of Network Check-ins App usage duration Number of Apps on Device Deposits/Withdrawals Device Usage Purchase History Following Followers Likes Number of Hashtags used History of Hashtags Search Strings entered Sequence of visits Time/Day log in Time spent on site Time spent on page Frequency of Search Videos Viewed Photos liked Sentiment Tone Euphemisms Hedonism Extroversion Face Recognition Openess Colloquialism Reasoning Strategies Language Modeling Dialog Intent Latent Semantic Analysis Phonemes Ontology Analysis Linguistics Image Tags Question Analysis Self-transcendent Affective Status DNA Proteome Microbiome Clinical/Biochemical Data Steps Nutrition Genetics Runs X-rays (CT scans) sound (ultrasound), magnetism (MRI), Radioactive (SPECT, PET) light (endoscopy, OCT) Environment Bio-Images Source: Bipartisan Policy Center, “F” as in Fat: How Obesity Threatens America’s Future (TFAH/RWJF, Aug. 2013) Human Digital Twins
- 37. @pieroleo 37 Source: http://www.bloomberg.com/video/meet-the-world-s-most-connected-man- Vs~LzkbkR7yhjza~7nji1g.html Meet the World's Most Connected Man
- 39. @pieroleo 6 Terabytes 60% Exogenous Factors 1.100 Terabytes 0.4 Terabytes 30% Genomics Factors 10% Clinical Factors IBM Watson Health // SOURCE: ©2015 J.M. McGinnis et al., “The Case for More Active Policy Attention to Health Promotion,” Health Affairs 21, no. 2 (2002):78–93 Data Generated per Life
- 40. @pieroleo Leveraging Exogenous Data for Chronic Care (Type 2 Diabetes; Primary & Secondary Prevention) 60% Exogenous Factors 30% Genomics Factors 10% Clinical Factors IBM Watson Health // SOURCE: ©2015 J.M. McGinnis et al., “The Case for More Active Policy Attention to Health Promotion,” Health Affairs 21, no. 2 (2002):78–93 Glucose Monitoring Calorie Intake Stress Levels Physical Activity Other vital signsSocial Interaction Affinity (retail) Sleep Pattern @pieroleo www.pieroleo.com
- 41. @pieroleo Source: http://datacoup..com Value of Data Pietro Leo's Second Income!
- 42. @pieroleo Source: http://fdna.com/blog/pmwc_duke/ Personalizing Medicine with Artificial Intelligence and Facial Analysis Presented by Omar Abdul-Rahman, MD, University of Nebraska Medical Center Precision Medicine World Conference (PMWC)| September 24-25, 2018 | Duke University
- 43. @pieroleo Thanks! Pietro Leo IBM Italy Executive Architect and thought leader for Artificial Intelligence Chief Scientist for IBM Italy Research & Business IBM Academy of Technology Leadership Member of ISO/SC42 Artificial Intelligence Standardization Committee www.pieroleo.com