Artificial Intelligence Today (22 June 2017)
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This was a top level presentation on some of the 30+ subcategories of Artificial Intelligence at the Hackaday LA June Meetup - Wheels, Wings, and Walkers. Sponsored by SupplyFrame Design Labs in Pasadena CA
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Artificial Intelligence Today (22 June 2017)
- 1. Sabri Sansoy CEO & Roboticist Artificial Intelligence presentation by Sabri Sansoy CEO & Roboticist Orchanic LLC
- 2. My background began as a rocket scientist.
- 5. This is a static test of a new Titan Solid Rocket Motor
- 12. Classified as a deflagration (fast burn) and not an explosion Damages were in the millions World’s largest crane at the time was destroyed.
- 14. some of our projects
- 15. Underwater Toxic Metal Detector Robot Boats use copper based coatings to prevent barnacle growth on their hulls. Over the course of many years the copper leaches out of the paints and into the marine environments. Marina Del Rey has one of the highest concentrations of copper which is toxic to most marine life.
- 16. BeachCombr - Trash Identifying Robot
- 17. Hyperspectral Imaging The idea is to look for hidden pollution in the sand like oils and other contaminants
- 18. Cloud Robotics
- 19. Medical Environment anesthesiology pollution detection Agriculture Automotive chemical dispensing creative advertising Fashion Current Vertical Areas of Business
- 20. Artificial Intelligence coined in 1955 a machine that can learn, reason, judge, predict, infer and initiate action
- 21. Machine Learning (Find Patterns) - Neural Networks - Deep Learning - Reinforcement Learning - Gradient Boost Machines - Support Vector Machines - Conformal Prediction Reasoning Robotics Computer Vision Internet of Things - Everything connected Natural Language Processing - Chatbots Philosophy Knowledge Engineering Rules Engines Logic Programming Multi Agent Systems Turing Tests …… and many more 30+ Subcategories of Artificial Intelligence
- 22. Machine Learning (Find Patterns) - Neural Networks - Deep Learning - Reinforcement Learning - Gradient Boost Machines - Support Vector Machines - Conformal Prediction Reasoning Robotics Computer Vision Internet of Things - Everything connected Natural Language Processing - Chatbots Philosophy Knowledge Engineering Rules Engines Logic Programming Multi Agent Systems Turing Tests …… and many more 30+ Subcategories of Artificial Intelligence
- 23. Developed in the 1940’s Think of them as “Giant Rocket Engines” - Andrew Ng, Chief Scientist, Baidu Neural Networks
- 24. Limited cup of rocket fuel, ie data Rocket engines sputter because of lack of fuel. Artificial Intelligence gets a bad wrap a few times referred to as AI Winters
- 25. 2006 - BIG DATA Explosion of data from Twitter, Facebook, Youtube, etc is making these “rocket engines” come alive. Amazing advances in cancer detection, speech recognition with background noise, etc
- 26. Big Data 2.5-quintillion bytes of data are being created every day 90% of the data in the world today has been created in the last two years alone
- 27. Machine Learning (Find Patterns) - Neural Networks - Deep Learning - Reinforcement Learning - Gradient Boost Machines - Support Vector Machines - Conformal Prediction Reasoning Robotics Computer Vision Internet of Things - Everything connected Natural Language Processing - Chatbots Philosophy Knowledge Engineering Rules Engines Logic Programming Multi Agent Systems Turing Tests …… and many more 30+ Subcategories of Artificial Intelligence
- 28. Deep Learning Used in Deutsch VW RRR Campaign which recognizes human vocalized car sounds.
- 29. Deep Learning - Developed by Geoff Hinton of Univ of Toronto & Google In 1959 David Hubel & Torsten Wiesel discovered “simple cells” and “complex cells” in cat visual system Software that emulates the Cat’s visual cortex system. The first layer of a cats eye recognizes edges of objects. The next layer recognizes what’s attached to that edge, is it a nose or an eyeball, etc The next layer recognizes whether the eyeball is attached to another cat or human…..
- 31. VW RRR Audio Recognition Image Recognition problem - Collected 1000s of audio samples of people making 3 types of car sounds, ie acceleration, deceleration & screeching! - Process converted audio wave files into frequency spectograms. - Train using supervised learning methodology, ie tell the Deep Learning engine that this image represents a human making a screeching car sound, etc.
- 32. Machine Learning (Find Patterns) - Neural Networks - Deep Learning - Reinforcement Learning - Gradient Boost Machines - Support Vector Machines - Conformal Prediction Reasoning Robotics Computer Vision Internet of Things - Everything connected Natural Language Processing - Chatbots Philosophy Knowledge Engineering Rules Engines Logic Programming Multi Agent Systems Turing Tests …… and many more 30+ Subcategories of Artificial Intelligence
- 33. ABDUCTIVE : taking your best shot What is the source of water?Reasoning
- 34. INDUCTIVE : conclusion merely likely Reasoning What is the source of water?
- 35. DEDUCTIVE : conclusion guaranteed Reasoning What is the source of water?
- 36. C. DEDUCTIVE : conclusion guaranteed Reasoning So what is Sherlock Holmes doing? B. INDUCTIVE : conclusion merely likely A. ABDUCTIVE : taking your best shot
- 37. C. DEDUCTIVE : conclusion guaranteed Reasoning So what is Sherlock Holmes doing? B. INDUCTIVE : conclusion merely likely A. ABDUCTIVE : taking your best shot
- 38. Machine Learning (Find Patterns) - Neural Networks - Deep Learning - Reinforcement Learning - Gradient Boost Machines - Support Vector Machines - Conformal Prediction Reasoning Robotics Computer Vision Internet of Things - Everything connected Natural Language Processing - Chatbots Philosophy Knowledge Engineering Rules Engines Logic Programming Multi Agent Systems Turing Tests …… and many more 30+ Subcategories of Artificial Intelligence
- 39. Czech playwright Karel Čapek introduced the word robot in 1920 in his play Rossum’s Universal Robots
- 40. Hollywood
- 41. Where is Rosie?
- 42. 1950's Whirlpools Miracle Kitchen of the Future Promo
- 46. Laundry Folding Robot Research @ UC Berkeley by Prof. Pieter Abbeel
- 47. Toys - Anki’s Cozmo
- 48. Commercial Savioke RELAY Starship Lowe’s LoweBot
- 49. Savioke Relay There’s one at LAX Residence Inn!
- 50. Flippy - a burger-grilling robot from Miso Robotics @ Caliburger in Pasadena
- 51. HANDEDNESS Would your robot be left handed or right handed? Why? If it doesn’t matter why did evolution make us one or the other? The idea of handedness in humans is tied to the use of one hemisphere of the brain over another, known as "lateralisation."
- 52. Lifespan Mayflies have the shortest lifespan of 24 hours Robot lifespan? Near infinite? Implications?
- 53. Emulating Feedback Loop found in Nature
- 55. Machine Learning (Find Patterns) - Neural Networks - Deep Learning - Reinforcement Learning - Gradient Boost Machines - Support Vector Machines - Conformal Prediction Reasoning Robotics Computer Vision Internet of Things - Everything connected Natural Language Processing - Chatbots Philosophy Knowledge Engineering Rules Engines Logic Programming Multi Agent Systems Turing Tests …… and many more 30+ Subcategories of Artificial Intelligence
- 56. Modelling Human Visual System in Software is Difficult The bar in the middle is only one color. But when placed on a gradient background your brain makes it appear to have a gradient itself
- 57. Mirror Self Recognition (MSR)
- 58. Machine Learning (Find Patterns) - Neural Networks - Deep Learning - Reinforcement Learning - Gradient Boost Machines - Support Vector Machines - Conformal Prediction Reasoning Robotics Computer Vision Internet of Things - Everything connected Natural Language Processing - Chatbots Philosophy Knowledge Engineering Rules Engines Logic Programming Multi Agent Systems Turing Tests …… and many more 30+ Subcategories of Artificial Intelligence
- 60. IBM Watson / Marchesa / Ogilvy Cognitive Dress
- 61. WATSON COGNITIVE DRESS iOT Technology Roadmap - 28 Mar 2016 Computer WIRELESS OPTIONS xBee / Zigbee WiFi Bluetooth Cellular/GSM Radio RF MicrocontrollerIBM Watson Components OPTIONS Mbed series Odroid XU4 RaspberryPi 3 Arduino Mega BeagleBoneBlack Intel Edison Particle Photon Particle Electron WIRED Ethernet CONTROL CENTER DRESS OPTIONS Servos Motors Muscle Wire Switches Sensors SmartFilm Power OPTIONS Voltage Amperage LiPo NOTES: 1. Design considerations - # of components to determine weight, heat, operation time & power constraints 2. Is the communication to the dress in one direction? Or will the dress send sensor data back to Watson for further cognitive training? 3. With each dress design iteration, a full matrix of an optimized hardware solution will be generated, detailing wireless protocol, microcontroller, battery size, etc.
- 63. IBM Watson Cognitive Dress
- 65. Some of today’s players in the fashion wearable space Julia Koerner https://www.juliakoerner.com/ Anouk Wipprecht http://www.anoukwipprecht.nl/ CuteCircuit http://cutecircuit.com/ Elektrocouture https://elektrocouture.com/
- 66. Machine Learning (Find Patterns) - Neural Networks - Deep Learning - Reinforcement Learning - Gradient Boost Machines - Support Vector Machines - Conformal Prediction Reasoning Robotics Computer Vision Internet of Things - Everything connected Natural Language Processing - Chatbots Philosophy Knowledge Engineering Rules Engines Logic Programming Multi Agent Systems Turing Tests …… and many more 30+ Subcategories of Artificial Intelligence
- 67. Natural Language Natural Language Processing - NLP - Voice to Text, Text to Voice, Translation Natural Language Understanding - NLU - Understand the context of whats being said Natural Language Dialog - NLD - AI generates natural sentences.
- 68. CHATBOTS “Todays chatbots are simple command and response systems” - Rob High, CTO of IBM Watson
- 69. CHATBOTS LOEBNER PRIZE - Annual competition Awards prizes considered by the judges to be the most human-like. - Controversy Promotes deceit vs true conversation - Mitsuku by Steve Worswick http://www.mitsuku.com/ 2013/2016 winner built on free pandorabots.com chat platform
- 70. Why Natural Language Understanding (NLU) is hard! What is “it” in each case? “The trophy doesn’t fit in your suitcase because it is too large” “The trophy doesn’t fit in your suitcase because it is too small.” - Yann LeCunn, Facebook Artificial Intelligence Research (FAIR)
- 71. LATEST IN AI
- 72. https://arxiv.org/pdf/1612.03242.pdf Generative Adversarial Networks Given a text description, an AI imagined these images of birds that don’t exist in real life..
- 73. These videos are not real; they are hallucinated by a generative video model.
- 74. Generative Adversarial Networks - Realtime video texture swapping
- 75. MIT AI system predicts when people will kiss, hug, or shake hands
- 77. POSSIBLE MAJOR DISRUPTOR IN DEEP LEARNING SPACE Bayesian Program Synthesis (BPS) Deals in Probabilities Company: Gamalon Funding: $12 mil from Darpa & Felicis Ventures Trains on few pieces of data (one shot) with same accuracy as Deep Learning Can train on one iPad vs many servers required for Deep Learning. 100 times more efficient than Google’s TensorFlow Cleaning enterprise unstructured data is their current business model.
- 78. Robots that can TASTE & SMELL. Computer learns to recognize sounds by watching video Quantum based, Machine Learning. qBit is a 1 & 0 …….at the same time! ← SPOOKY! Answer Set Programming Vatican weighing in on the religious aspects of A.I. On the horizon!
- 79. BLESSU-2 - Robot Priest
- 80. How to get started in Machine / Deep Learning! Deep Learning in the Browser http://cs.stanford.edu/people/karpathy/convnetjs/ Free Coursera Online Class https://www.coursera.org/learn/machine-learning Kaggle Competition https://www.kaggle.com/
- 81. Open Source Deep Learning Software Google Tensorflow https://www.tensorflow.org/ Facebook Deep-learning modules for Torch https://github.com/facebook/fbcunn
- 82. Cloud based AI Tools - all have free trials. IBM WATSON https://www.ibm.com/watson/ MICROSOFT https://www.microsoft.com/en-us/ai AMAZON https://aws.amazon.com/amazon-ai/ GOOGLE https://cloud.google.com/products/machine- learning/
- 83. Blogs OPENAI https://openai.com DEEPMIND https://deepmind.com/blog GOOGLE RESEARCH https://research.googleblog.com BERKELEY ARTIFICIAL INTELLIGENCE RESEARCH (BAIR) http://bair.berkeley.edu/blog/ FACEBOOK ARTIFICIAL INTELLIGENCE RESEARCH (FAIR) https://research.fb.com/category/facebook-ai-research-fair/
- 84. Organizations ASSOCIATION FOR THE ADVANCEMENT OF ARTIFICIAL INTELLIGENCE http://www.aaai.org/ ALLEN INSTITUTE OF ARTIFICIAL INTELLIGENCE http://allenai.org/ MACHINE INTELLIGENCE RESEARCH INSTITUTE https://intelligence.org/ FUTURE OF LIFE INSTITUTE https://futureoflife.org
- 85. Conferences NIPS 2017 https://nips.cc O’REILLY ARTIFICIAL INTELLIGENCE CONFERENCE https://conferences.oreilly.com/artificial-intelligence/ai-ny IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION( ICRA ) http://www.icra2017.org LIST OF MANY MORE CONFERENCES http://www.kdnuggets.com/meetings/
- 86. Competitions KAGGLE https://www.kaggle.com CROWDANALYTIX https://www.crowdanalytix.com DRIVEN DATA https://www.drivendata.org LIST OF MANY MORE COMPETITIONS http://www.kdnuggets.com/competitions
Notes de l'éditeur
- http://www.dailybreeze.com/environment-and-nature/20140914/boaters-la-county-brace-for-impact-of-marina-del-rey-cleanup-plan
- The central problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects. The field was founded on the claim that human intelligence "can be so precisely described that a machine can be made to simulate it."
- The central problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects. The field was founded on the claim that human intelligence "can be so precisely described that a machine can be made to simulate it."
- The central problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects. The field was founded on the claim that human intelligence "can be so precisely described that a machine can be made to simulate it."
- The central problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects. The field was founded on the claim that human intelligence "can be so precisely described that a machine can be made to simulate it."
- https://memeburn.com/2017/05/artificial-intelligence-data-analyst-job/
- The central problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects. The field was founded on the claim that human intelligence "can be so precisely described that a machine can be made to simulate it."
- http://lookwhatwedid.co/vwgolfrrr-awards/
- https://www.forbes.com/sites/peterhigh/2016/06/20/deep-learning-pioneer-geoff-hinton-helps-shape-googles-drive-to-put-ai-everywhere/#764d50fe693c
- https://www.slideshare.net/sawjd/big-data-day-la-2015-deep-learning-human-vocalized-animal-sounds-by-sabri-sansoy-of
- The central problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects. The field was founded on the claim that human intelligence "can be so precisely described that a machine can be made to simulate it."
- Inductive reasoning begins with observations that are specific and limited in scope, and proceeds to a generalized conclusion that is likely, but not certain, in light of accumulated evidence.
- Inductive reasoning begins with observations that are specific and limited in scope, and proceeds to a generalized conclusion that is likely, but not certain, in light of accumulated evidence.
- The central problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects. The field was founded on the claim that human intelligence "can be so precisely described that a machine can be made to simulate it."
- https://www.nytimes.com/2017/05/24/business/entrepreneurship-laundroid-self-folding-laundry-machine.html
- https://www.nytimes.com/2017/05/24/business/entrepreneurship-laundroid-self-folding-laundry-machine.html https://www.youtube.com/watch?v=5FGVgMsiv1s
- https://anki.com/en-us/cozmo
- https://newsroom.lowes.com/news-releases/lowesintroduceslowebot-thenextgenerationrobottoenhancethehomeimprovementshoppingexperienceinthebayarea-2/ https://www.starship.xyz/ http://www.savioke.com http://www.lowesinnovationlabs.com/lowebot/
- https://caliburger.com/pasadena
- First Contact might be with machine.
- The central problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects. The field was founded on the claim that human intelligence "can be so precisely described that a machine can be made to simulate it."
- https://en.wikipedia.org/wiki/Mirror_test
- The central problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects. The field was founded on the claim that human intelligence "can be so precisely described that a machine can be made to simulate it."
- the network of physical objects—devices, vehicles, buildings and other items —embedded with electronics, software, sensors, and network connectivity that enables these objects to collect and exchange data.
- https://chargetech.com/ 110volt chargeable power
- https://chargetech.com/ 110volt chargeable power
- The central problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects. The field was founded on the claim that human intelligence "can be so precisely described that a machine can be made to simulate it."
- https://techcrunch.com/2017/02/27/for-ibms-cto-for-watson-not-a-lot-of-value-in-replicating-the-human-mind-in-a-computer/
- http://www.loebner.net/Prizef/loebner-prize.html https://phys.org/news/2013-09-mitsuku-chatbot-good-loebner-prize.html
- http://fortune.com/2017/05/15/facebooks-chatbot-language-artificial-intelligence/
- http://web.mit.edu/vondrick/tinyvideo/
- http://web.mit.edu/vondrick/tinyvideo/
- http://www.techrepublic.com/article/mit-ai-system-predicts-when-people-will-kiss-hug-or-shake-hands/ http://carlvondrick.com/prediction.pdf
- http://web.mit.edu/vondrick/tinyvideo/ http://www.digitaltrends.com/computing/gamalon-machine-learning-bps-technology/
- https://www.theguardian.com/technology/2017/may/30/robot-priest-blessu-2-germany-reformation-exhibition