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The Artificial Intelligence Conference - New York, NY 2018

Video Description

Artificial Intelligence (AI) New York 2018 provided conference attendees with an unsurpassed opportunity to learn about the latest breakthroughs in AI. Laser focused on AI business development, the conference offered presentations by many of the world's top AI practitioners, including industry leaders such as Xerox PARC CEO Tolga Kurtoglu, Intuit CDO Ashok, IBM AI VP Al Dario Gil, and more. If there was just one take away from AI-New York 2018, it's this: AI will have an enormous impact on your business—don’t get left behind.

This video compilation gives you unfettered access to each of the conference's sessions, keynotes, and tutorials. Highlights include:

  • Keynote speeches from AI visionaries like Peter Norvig (Google), Julie Shin Choi (Intel AI), and Thomas Reardon (CTRL-Labs).
  • The AI Business Summit—tutorials and executive briefings specifically designed for executives, business leaders, and strategists.
  • Sessions on how to implement AI, including the Ashwin Vijayakumar (Intel) tutorial on the Movidius Neural Compute Stick and Danielle Dean's (Microsoft) talk on building AI applications backed by a Kubernetes cluster.
  • Sessions on the models and methods of AI, including Zoubin Ghahramani's (Uber) deep dive into probabilistic machine learning; Ameet Talwalkar's (Determined AI) exploration of scalable deep learning; Taniya Mishra (Affectiva) on AI emotion detection software; and Gerard de Melo (Rutgers University) on deep sentiment analysis techniques.
  • Sessions on AI in the enterprise.
  • Sessions covering the impact of AI on business and society.
  • Sessions on the ways people interact with AI, including talks on incorporating AI into cyberthreat detection; AI-powered customer service agents; and the uses of cognitive IoT in eldercare.

With more than 100 hours of material to review at your own pace, the AI New York 2018 video compilation is a phenomenal value for anyone who wants to join the AI future.

Table of Contents

  1. Keynotes
    1. Rapid AI Experimentation and Innovation on Amazon Web Services (Sponsored by Amazon Web Services) - Dan Romuald Mbanga (Amazon Web Services) 00:06:54
    2. Intel AI for the enterprise ecosystem - Fiaz Mohamed (Intel AI Products Group) 00:07:55
    3. Using machine learning, the IoT, drones, and networking to reduce world hunger (sponsored by Microsoft) - Jennifer Marsman (Microsoft) 00:10:09
    4. Bringing AI into the wild (sponsored by SAS) - Mary Beth Ainsworth (SAS) 00:05:14
    5. Understanding automation - Ben Lorica (O'Reilly Media), Roger Chen (Computable Labs) 00:07:41
    6. The frontiers of machine learning and AI - Zoubin Ghahramani (Uber | University of Cambridge) 00:15:34
    7. Autonomy and human-AI interaction - Manuela Veloso (Carnegie Mellon University) 00:15:15
    8. Fireside chat with Peter Norvig and Kavya Kopparapu - Peter Norvig (Google), Kavya Kopparapu (GirlsComputingLeague) 00:12:52
    9. Increasing Business Results Through AI in the Entertainment Industry - Fiaz Mohamed (Intel AI Products Group) and Justin Herz (Warner Bros.) 00:09:19
    10. WTT: What the Tensor? (Sponsored by Google Cloud) - Ron Bodkin (Google) 00:06:37
    11. The Physics of AI (Sponsored by IBM Watson) - Dario Gil (IBM) 00:11:43
    12. Using Machine Learning in Workload Automation (Sponsored by Digitate) - Abhijit Deshpande (Digitate) 00:06:32
    13. Neural Interfaces: Connecting Humans and Artificial Intelligence - Thomas Reardon (CTRL-Labs) 00:15:06
    14. Serving Billions of Personalized News Feeds with AI - Meihong Wang (Facebook) 00:12:11
    15. Hybrid Bio-Opto-Electronics for AI - George Church (Harvard University) 00:14:27
    16. AI4ALL: AI will change the World, but who will change AI? - Olga Russakovsky (Princeton University) 00:14:19
  2. Implementing AI
    1. Building conversational AI in-house in the Fortune 500 - Alan Nichol (Rasa) 00:42:56
    2. How artificial intelligence helps advance day-to-day quality and maintenance decisions - Jacob Graham (Intel) 00:30:37
    3. Gamifying strategy: Enterprise AI use cases on agent-based simulation and learning - Anand Rao (PwC) 00:42:05
    4. From answering questions to questioning answers: Challenges of large-scale QnA systems - Mridu Narang (Microsoft) 00:40:08
    5. Do-it-yourself artificial intelligence - Alasdair Allan (Babilim Light Industries) 00:38:26
    6. Automatic financial econometrics with AI - Ambika Sukla (Morgan Stanley) 00:38:47
    7. The long and winding road to AI: Lessons from implementing cognitive AI - Rupert Steffner (WUNDER) 00:39:25
    8. Containers and the intelligent application revolution - William Benton (Red Hat) 00:39:51
    9. Deep reinforcement learning’s killer app: Intelligent control in real-world systems - Mark Hammond (Bonsai) 00:31:01
    10. Using machine learning to enhance activity-based intelligence - Jamie Irza (Raytheon) 00:31:22
    11. Online and active learning for recommender systems - Jorge Silva (SAS) 00:41:01
    12. Distributed DNN training: Infrastructure, challenges, and lessons learned - Kaarthik Sivashanmugam (Microsoft), Wee Hyong Tok (Microsoft) 00:40:24
    13. Machine learning meets DevOps: Paying down the high-interest credit card - Sameer Wadkar (Comcast NBCUniversal), Nabeel Sarwar (Comcast NBCUniversal) 00:40:45
    14. Revolutionizing aviation with AI - Carolina Sanchez Hernandez (NATS) 00:32:52
    15. A reliable and robust classification pipeline for protein crystallization imaging - Christopher Watkins (CSIRO) 00:40:32
    16. An open extensible AI platform implementing four use cases for the enterprise - Murali Kaundinya (Independent) 00:27:06
    17. Caching big data for machine learning platform at Uber - Zhenxiao Luo (Uber) 00:41:55
    18. Racial bias in facial recognition software - Stephanie Kim (Algorithmia) 00:38:24
    19. Using Cognitive Toolkit (CNTK) and TensorFlow with Kubernetes clusters - Danielle Dean (Microsoft), Wee Hyong Tok (Microsoft) 00:41:54
    20. Neural interfaces: Connecting humans and artificial intelligence - Thomas Reardon (CTRL-Labs) 00:42:42
    21. Scaling up deep learning-based superresolution models more efficiently using the cloud - Xiaoyong Zhu (Microsoft) 00:41:50
    22. Classifying images in Spark - Yulia Tell (Intel), Maurice Nsabimana (World Bank Development Data Group) 00:37:54
  3. Sponsored
    1. AI and quantum computing for business (sponsored by IBM) - Dario Gil (IBM) 00:37:53
    2. How AI produces high-impact business outcomes in the finance, manufacturing, travel, transportation, and pharmaceutical industries (sponsored by Teradata) - Chad Meley (Teradata) 00:40:13
    3. Don't get stung by extreme data (or honey bees) (sponsored by Kinetica) - Jonathan Greenberg (Kinetica) 00:34:18
    4. Improving wildlife conservation with artificial intelligence (sponsored by SAS) - Mary Beth Ainsworth (SAS) 00:33:16
    5. Computational creativity: Making music with AI technologies (sponsored by Microsoft) - Erika Menezes (Microsoft), Serina Kaye (Microsoft) 00:36:18
    6. People, process, and platforms deliver AI (sponsored by Deloitte Analytics) - Brian Ray (Deloitte) 00:40:26
  4. AI Business Summit
    1. AI and the future of work - Faizan Buzdar (Box) 00:33:37
    2. Executive Briefing: Building an AI-first enterprise culture - Kathryn Hume (integrate.ai) 00:39:24
    3. How Comcast uses AI to reinvent the customer experience - Jan Neumann (Comcast), Dominique Izbicki (Comcast) 00:48:11
    4. AI building blocks: Speech technologies - Omar Tawakol (Voicera) 00:48:46
    5. Using artificial intelligence to enhance the digital experience - Ron Bodkin (Google) 00:41:59
    6. The vital role of failure in machine learning - Scott Weller (SessionM) 00:39:30
    7. Conversational AI: What we’ve learned from millions of AI conversations with thousands of customers - Dr. Sid J. Reddy (Conversica) 00:53:22
    8. Executive Briefing: Lean AI product development (and common pitfalls) - Shane Lewin (Microsoft) 00:41:30
  5. Models and Methods
    1. Building winning AI technology: The anatomy of a champion - Steve J Rennie (Fusemachines) 00:38:48
    2. Deep sentiment analysis across language boundaries - Gerard de Melo (Rutgers University) 00:38:30
    3. High-throughput single-shot multibox object detection on edge devices using FPGAs - Srinivasa Karlapalem (Intel) 00:38:06
    4. Long-term time series forecasting with recurrent neural networks - Mustafa Kabul (SAS) 00:50:03
    5. How DoorDash leverages AI in its world-class on-demand logistics engine - Raghav Ramesh (DoorDash) 00:30:48
    6. Avoiding biased algorithms: Lessons from the hiring space - Lindsey Zuloaga (HireVue) 00:40:12
    7. The quest for a new visual search beyond language - Mike Ranzinger (Shutterstock) 00:39:40
    8. Building a healthcare decision support system for ICD10/HCC coding through deep learning - Manas Ranjan Kar (Episource) 00:35:18
    9. Humanizing technology: Emotion detection from face and voice - Taniya Mishra (Affectiva) 00:40:36
    10. MLPerf: machine learning in academics - David Patterson (UC Berkeley), Greg Diamos, Sharan Narang (Baidu), Cliff Young, Peter Mattson (Google), Peter Bailis (Stanford University), Gu-Yeon Wei (Harvard University) 00:48:09
    11. An end-to-end video analytics solution for surveillance and securing high-value assets - Harsh Kumar (Intel) 00:38:04
    12. Recurrent neural networks for recommendations and personalization - Nick Pentreath (IBM) 00:41:20
    13. Combining well-established statistical techniques with modern machine learning algorithms - Funda Gunes (SAS) 00:39:50
    14. Determining normal (and abnormal) using deep learning - John Hebeler (Lockheed Martin) 00:33:51
    15. Adversarial ML: Practical attacks and defenses against graph-based clustering - Yacin Nadji (Georgia Institute of Technology) 00:42:37
    16. Scalable deep learning - Ameet Talwalkar (Determined AI) 00:38:15
  6. Impact of AI on Business and Society
    1. AI in personal finance: More than just chatbots - Brian Pearce (Wells Fargo) 00:39:21
    2. AI and the future of customer service: Meet Expensify’s new AI-assistant, Concierge - David Barrett (Expensify ) 00:40:09
    3. Executive Briefing: The conversational business—Use cases and best practices for chatbots in financial services and media - Susan Etlinger (Altimeter Group) 00:39:33
    4. Deep learning and AI is making clinical neuroimaging faster, safer, and smarter - Enhao Gong (Stanford University | Subtle Medical), Greg Zaharchuk (Stanford University) 00:41:34
    5. Executive Briefing: Making reliable and trustworthy AI systems a reality - Tolga Kurtoglu (PARC) 00:32:55
    6. Making business Bayesian: From uncertainty to action - Richard Tibbetts (Empirical Systems) 00:37:58
    7. AI: A force for good - Jake Porway (DataKind) 00:41:20
    8. When machines have ideas - Ben Vigoda (Gamalon) 00:42:15
    9. Executive Briefing: A new taxonomy of machine learning - Rachel Silver (MapR Technologies) 00:39:03
    10. AI for the public sector: Benefitting citizens through cognitive solutions - Sumeet Vij (Booz Allen Hamilton) 00:45:58
    11. Democracy, human rights, and the rule of law by design for artificial intelligence - Paul Nemitz (European Commission) 00:54:01
  7. AI in the Enterprise
    1. Best practices for machine learning in the enterprise - Robbie Allen (InfiniaML) 00:36:56
    2. Executive Briefing: Why AI needs human-centered design - James Guszcza (Deloitte Consulting) 00:44:22
    3. Deploying deep learning in the cloud - Alex Jaimes (DigitalOcean | Acesio) 00:53:36
    4. Three examples of computer vision in action - Ophir Tanz (GumGum) 00:37:52
    5. Executive Briefing: Building a learning organization is AI's hat trick - Jana Eggers (Nara Logics) 00:39:13
    6. Democratizing deep reinforcement learning - Danny Lange (Unity Technologies) 00:41:38
    7. Things nobody told you about building conversational UIs - Ofer Ronen (Chatbase) 00:41:39
    8. Build deep learning-powered big data solutions with BigDL - Sergey Ermolin (Intel) 00:37:16
    9. Session by Meihong Wang - Meihong Wang (Facebook) 00:42:39
  8. Interacting with AI
    1. Innovations in explainable AI in the context of real-world business applications - Scott Zoldi (FICO) 00:39:38
    2. Predicting the stock market using LSTMs - Aurélien Géron (Kiwisoft) 00:47:00
    3. The cognitive IoT and eldercare - David C Martin (IBM Watson) 00:44:28
    4. Artificial intelligence strategy: Delivering deep learning - Chris Benson (Honeywell) 00:39:45
    5. Fooling neural networks in the physical world - Andrew Ilyas (Massachusetts Institute of Technology), Logan Engstrom (Massachusetts Institute of Technology), Anish Athalye (Massachusetts Institute of Technology) 00:43:28
    6. TensorFlow Lite: How to accelerate your Android and iOS app with AI - Kaz Sato (Google) 00:36:56
    7. Collaborative machine intelligence: Accelerating human knowledge - Emily Pavlini (Diffeo), Max Kleiman-Weiner (Diffeo) 00:41:00
    8. Deep dive into probabilistic machine learning - Zoubin Ghahramani (Uber | University of Cambridge) 00:41:19
    9. Model evaluation in the land of deep learning - Pramit Choudhary (DataScience.com) 00:36:51
    10. From here to "Her": Evolving chatbot interactions to meet the relational needs of humans - Ian Beaver (Next IT - Verint), Cynthia Freeman (Next IT) 00:41:45
  9. Tutorials
    1. Design thinking for AI - Chris Butler (Philosophie) - Part 1 00:45:35
    2. Design thinking for AI - Chris Butler (Philosophie) - Part 2 00:11:13
    3. Design thinking for AI - Chris Butler (Philosophie) - Part 3 00:43:19
    4. Design thinking for AI - Chris Butler (Philosophie) - Part 4 00:28:00
    5. Accelerate deep neural networks at the edge with the Intel Movidius Neural Compute Stick - Ashwin Vijayakumar (Intel) - Part 1 00:44:18
    6. Accelerate deep neural networks at the edge with the Intel Movidius Neural Compute Stick - Ashwin Vijayakumar (Intel) - Part 2 00:21:38
    7. Accelerate deep neural networks at the edge with the Intel Movidius Neural Compute Stick - Ashwin Vijayakumar (Intel) - Part 3 00:22:57
    8. Accelerate deep neural networks at the edge with the Intel Movidius Neural Compute Stick - Ashwin Vijayakumar (Intel) - Part 4 00:19:23
    9. PyTorch: A flexible approach for computer vision models - Mo Patel (Independent), Neejole Patel (Virginia Tech) - Part 1 00:41:47
    10. PyTorch: A flexible approach for computer vision models - Mo Patel (Independent), Neejole Patel (Virginia Tech) - Part 2 00:40:45
    11. PyTorch: A flexible approach for computer vision models - Mo Patel (Independent), Neejole Patel (Virginia Tech) - Part 3 00:43:16
    12. PyTorch: A flexible approach for computer vision models - Mo Patel (Independent), Neejole Patel (Virginia Tech) - Part 4 00:41:02
    13. Customer-centered AI: A radical strategy - Radhika Dutt (Radical Product), Geordie Kaytes (Fresh Tilled Soil), Nidhi Aggarwal (Radical Product) - Part 1 00:50:03
    14. Customer-centered AI: A radical strategy - Radhika Dutt (Radical Product), Geordie Kaytes (Fresh Tilled Soil), Nidhi Aggarwal (Radical Product) - Part 2 00:35:05
    15. Deploy MXNet and TensorFlow deep learning models with AWS Lambda, Google Cloud Functions, and Azure Functions - Greg Werner (3Blades) - Part 1 00:42:30
    16. Deploy MXNet and TensorFlow deep learning models with AWS Lambda, Google Cloud Functions, and Azure Functions - Greg Werner (3Blades) - Part 2 00:26:37
    17. Deploy MXNet and TensorFlow deep learning models with AWS Lambda, Google Cloud Functions, and Azure Functions - Greg Werner (3Blades) - Part 3 00:44:41
    18. Deploy MXNet and TensorFlow deep learning models with AWS Lambda, Google Cloud Functions, and Azure Functions - Greg Werner (3Blades) - Part 4 00:42:18
    19. word2vec and friends - Bruno Gonçalves (New York University) - Part 1 00:41:40
    20. word2vec and friends - Bruno Gonçalves (New York University) - Part 2 00:33:57
    21. word2vec and friends - Bruno Gonçalves (New York University) - Part 3 00:45:04
    22. word2vec and friends - Bruno Gonçalves (New York University) - Part 4 00:43:31
    23. Bringing AI into the enterprise - Kristian Hammond (Narrative Science) - Part 1 00:48:37
    24. Bringing AI into the enterprise - Kristian Hammond (Narrative Science) - Part 2 00:38:19
    25. Bringing AI into the enterprise - Kristian Hammond (Narrative Science) - Part 3 00:46:48
    26. Bringing AI into the enterprise - Kristian Hammond (Narrative Science) - Part 4 00:37:40
    27. Bringing AI into the enterprise - Kristian Hammond (Narrative Science) - Part 5 00:49:08
    28. Bringing AI into the enterprise - Kristian Hammond (Narrative Science) - Part 6 00:28:12
    29. Bringing AI into the enterprise - Kristian Hammond (Narrative Science) - Part 7 00:41:32
    30. Bringing AI into the enterprise - Kristian Hammond (Narrative Science) - Part 8 00:44:20