Women in AI Kickoff Event Agenda and Speakers
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The document summarizes a Women in AI meetup event held on May 22nd, 2017. It includes an agenda for the event with times for food, introductions, and featured speaker presentations. Two featured speakers are highlighted - Julie Choi, Head of Marketing at Intel's AI Products group, and Anahita Bhiwandiwalla, a Senior Software Engineer at Intel. Their presentations covered topics like how AI is changing different industries, the growth of AI compute cycles and machine learning, and Intel's new class of AI products designed for neural networks. The document also shares Anahita's perspective working with AI through examples of her past research on speaker recognition, language modeling, social network analysis, and healthcare analytics.
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Women in AI Kickoff Event Agenda and Speakers
- 1. Women in AI Kickoff - May 22nd, 2017
- 3. Nice to meet you Amara Keller AI Developer Advocate with Intel Nervana (AI Products) @MissAmaraKay
- 4. Agenda 6 - Grab food, meet someone new 6:15 - Intro, welcome ~6:30 - Featured Speakers! Julie Choi, Head of Marketing (AI Products, Intel) Anahita Bhiwandiwalla, Sr. Software Engineer (AI Products, Intel) Q&A and Mingling to Follow
- 5. Things to consider ● Hashtags to use: #WomenInAI #WIAI ● Please adhere to our Code of Conduct. ● Let me know if you are interested in speaking! ● We are hiring: nervanasys.com/careers
- 7. 2 background Nerd marketing Spelling bee winner Wife and mom Slow distance runner
- 8. 3 Aiischangingeverything Consumer Health Finance Retail Government Energy Transport Industrial Other Smart Assistants Chatbots Search Personalization Augmented Reality Robots Enhanced Diagnostics Drug Discovery Patient Care Research Sensory Aids Algorithmic Trading Fraud Detection Research Personal Finance Risk Mitigation Support Experience Marketing Merchandising Loyalty Supply Chain Security Defense Data Insights Safety & Security Resident Engagement Smarter Cities Oil & Gas Exploration Smart Grid Operational Improvement Conservation Autonomous Cars Automated Trucking Aerospace Shipping Search & Rescue Factory Automation Predictive Maintenance Precision Agriculture Field Automation Advertising Education Gaming Professional & IT Services Telco/Media Sports Source: Intel forecast examples Earlyadoption
- 9. 4 AIneedsdataBy 2020… The average internet user will generate ~1.5GBoftrafficperday Smart hospitals will generate over 3,000GBperday Self driving cars will be generating over 4,000GBperday…each All numbers are approximated http://www.cisco.com/c/en/us/solutions/service-provider/vni-network-traffic-forecast/infographic.html http://www.cisco.com/c/en/us/solutions/collateral/service-provider/global-cloud-index-gci/Cloud_Index_White_Paper.html https://datafloq.com/read/self-driving-cars-create-2-petabytes-data-annually/172 http://www.cisco.com/c/en/us/solutions/collateral/service-provider/global-cloud-index-gci/Cloud_Index_White_Paper.html http://www.cisco.com/c/en/us/solutions/collateral/service-provider/global-cloud-index-gci/Cloud_Index_White_Paper.html A connected plane will generate over 40,000GBperday A connected factory will generate over 1,000,000GBperday radar ~10-100KB persecond sonar ~10-100KB persecond gps ~50KB persecond lidar ~10-70MB persecond cameras ~20-40MB persecond Self driving cars will generate over 4,000GBperday…each
- 11. 6 Machine Learning Neural Networks Deep Learning AI Aicontinuestoevolve
- 12. 7 IntelNervana:AIProducts ACCELERATEAI by Design discoverApplied AI Research evolveHuman Intelligence
- 13. 8 New class of AI products designed for neural networks, architected to handle higher level matrix operations and non- linearities inherent to this problem space. Deep Learning & Beyond Next Level Silicon AIbydesign
- 14. 9 Healthcare: Tumor detection Automotive: Speech interfaces Positive: Negative: Industry: Agricultural Robotics Energy: Oil & Gas Positive: Negative: Genomics: Sequence analysisFinance: Time-series search engine Query: Results: AIapplied
- 15. 10 libraries Intel® MKL MKL-DNN Intel® MLSL toolkits Frameworks Intel® DAAL hardware Memory/Storage NetworkingCompute Intel Distribution Mlib BigDL Intel® Nervana™ Graph* Intel®Nervana™PORTFOLIO experiences Intel® Nervana™ DL Software & Cloud Computer Vision *Future Intel® DL Training & Deployment Intel® Computer Vision SDK Movidius Fathom Intel® GO™ Automotive SDK *
- 21. Recognizing Speakers? http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.232.6270&rep=rep1&type=pdf - All that math actual does something!!! - I can barely tell the difference between these two speakers - So much noise! Is anyone even speaking? - Each speaker has it’s own mathematical representation - The system improved it’s representation over time! - Accent/language independent - Who spoke when in a conversation? - This is actually useful THIS IS COOL! Rewind 8 years ago to Mumbai, India
- 22. Make new words in a Language I don’t know? http://www.cs.columbia.edu/~rasooli/papers/acl2014.pdf Rewind 5 years ago to New York - Generate new words! But I am clueless about Turkish, Tagalog, Pashto - Prefix/suffix can be modeled? - Keyword search, okay that I know - Predict new words you are likely to search for - Wait did the system learn the rules of the language before I could even try? THIS IS SUPER COOL
- 23. Predicting friends? https://event.cwi.nl/grades/2013/04-jain-slides.pdf Rewind 4 years ago to Oregon - Graphs are more than - Storage matters - Applying math concepts to derive insights – recommendations, filtering, influential nodes, drug similarity - Why is all this free? (READ - Open Source) HIRED!
- 24. Patient re-admittance - Your numbers tell your story! - Your numbers can also tell you what may not know, yet. - What can you do if you know you are at risk? - What can your doctor do? - What can your insurance do? OKAY I LOVE MY JOB! Last three years, Oregon
- 25. Are these drugs similar? Last three years, Oregon - Analyzing drug similarity - Saving lives – side effects, allergies! - Accessible healthcare - Helping doctors make decisions
- 26. http://technologyadvice.com/blog/healthcare/5-dicom-viewers/ http://dicom.nema.org/ Analytics on MRI/CT images - Assist in healthcare - Uncover hidden insights - Validate opinions - Leverage benefits of massive data to make smart models - Faster time to result OKAY I LOVE MY JOB ++! Last three years, Oregon
- 31. Thank you J