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AI Landscape 2015
The document discusses the landscape of artificial intelligence and natural language processing, highlighting the rapid growth of data and technology in recent years. It emphasizes the importance of human-centered computing and outlines various industries impacted by AI advancements. The author shares personal experiences and lessons learned in developing technologies, advocating for innovative thinking and solutions.
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AI Landscape 2015
- 1. Artificial Intelligence LandscapeArtificialIntelligence Landscape 11th National Natural Language Processing Research Symposium, April 25, 2015 National University
- 2. About Me 2 Allan C.Tan, PMP, SCEA
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- 4. • 2.5 billioncontent items shared per day • 2.7 billion Likes per day • 300 million photos uploaded per day • 500+terabytes of new data every day (equivalent to 1,500,000,000 books) Company Orientation 4
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- 6. Bigger than aNation Company Orientation 6 Market Cap: $710B GDP: $679B GDP: $272B
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- 8. Personal Device Apple sold957,000 Apple Watches on the first day. Expected to sell 30M-40M units on the first year.
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- 10. Computing is nowmore human than ever
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- 14. Industry – CustomerExperience
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- 16. Industry – PublicSector
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- 21. Industry - Healthcare CompanyOrientation 21
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- 28. Imagine This! Based onmy findings, you should take the following medicines… According to R.A. 9201, you are not liable for …
- 29. Natural Language Processing CompanyOrientation 29 The bridge to translate between machines and human
- 30. My Real WorldExperience 30 Virtual Extraction Engine •Developed 2008-2009 •80+% accuracy is not acceptable •Consider other external factors Lessons Learned: •Present solution accordingly •High Cost of R&D
- 31. My Real WorldExperience 31
- 32. Goal 32 “The only wayto come up with something new—something world changing—is to think outside of the constraints everyone else has. You have to think outside of the artificial limits everyone else has already set.” - Steve Jobs
- 33. Thank You! Allan C.Tan, PMP, SCEA allan@ideyatech.com 33
Editor's Notes
- #5 80% of world’s data is generated in the last 2 years
- #6 The zettabyte is a multiple of the unit byte for digital information. The prefix zetta indicates multiplication by the seventh power of 1000 or 1021 in the International System of Units (SI). equal to a thousand exabytes or a billion terabytes
- #14 PredictionIO is an open-source Machine Learning server for developers and data scientists to build and deploy predictive applications in a fraction of the time. Skymind: Deep Learning for Industry. world’s first open-source, distributed, commercial-grade deep-learning framework: Deeplearning4j.org. We also built ND4J, a scientific computing library for the JVM. AlgorithMIA: We're building a community around state-of-the-art algorithm development. Users can create, share, and build on other algorithms and then instantly make them available as a web service.
- #17 500 million tweets, raised $130M usd Catch story and threats before public, journalist. Predicts twitter moods. Dataminr transforms the Twitter stream and other public datasets into actionable signals, discovering must-know information in real-time for clients in Finance, the Public Sector, News, Security and Crisis Management.
- #23 ALP can combine evidence from a variety of contexts to create a unified psychometric profile for each learner. As these profiles grow with each child, they’ll provide you with rich insight into not only your learners’ strengths and interests but also the efficacy of your own educational product. Because it was designed to incorporate data from a range of sources, ALP can support personalized learning in any domain and at any age level to provide the optimal learning experience for your users. These data are used to create an adaptive learning environment, generate personalized insights and activity suggestions for each learner and their parents, and update the learner’s psychometric profile to provide a meaningful picture of their learning journey.