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Open techai 20180429 v1
This document discusses IBM's OpenTechAI initiative and the state of open source AI projects on GitHub. It provides statistics on the most popular open source AI projects on GitHub, including the number of code stars and forks. TensorFlow, Keras, and Sci-kit Learn are among the most popular. The document also shows that IBM's own open source AI projects like INTU and FfDL have fewer stars and forks compared to projects from other large companies. It outlines steps for individuals to get involved in OpenTechAI like getting a GitHub account, learning through reading, replicating, and reporting on projects. Finally, it presents a potential framework for benchmarking and measuring progress in artificial intelligence.
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Open techai 20180429 v1
- 1. OpenTechAI Jim Spohrer (IBM) http://slideshare.net/spohrer/opentechai_20180429_v1 4/29/2018IBM #OpenTechAI 1 FfDL – MAX – ART – INTU – COG – IBM – DBG – WATSON – CODAIT - RESEARCH – POWERAI – COGNITIVE – GITHUB – LEADERBOARDS - KAGGLE
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- 6. OpenTechAI on GitHub(April 29, 2018) Code Stars (K) Forks (K) Google TensorFlow 97 62 Keras-team Keras 28 10 Sci-kit Sci-kit 27 13 BVLC Caffe 23 14 PyTorch PyTorch 14 3 Apache MXNet 13 5 Caffe2 Caffe2 7 1 Baidu PaddlePaddle 6 1 Google Tensor2Tensor 3 0.8 Tencent ANGEL 3 0.8 4/29/2018 IBM #OpenTechAI 6
- 7. OpenTechAI on GitHub(April 29, 2018) Code Stars (K) Forks (K) Tencent NCNN 3 0.8 Google Kubeflow 3 0.3 Microsoft ONNX 3 0.3 Google TensorBoard 1 0.3 Apache SystemML 0.6 0.2 IBM (watson-intu) INTU (10 Repositories) 0.1 0.07 IBM FfDL 0.1 0.04 IBM ART 0.1 0.03 IBM MAX 0.005 0.017 LFDL AT&T Acumos (35 Repositories) 0.01 0 4/29/2018 IBM #OpenTechAI 7
- 8. Step Comment GitHub Getan account and read the guide Learn 3 R's - Read, Redo, Report Read (Medium/arXiv), Redo (GitHub), Report (Jupyter Notebook) Kaggle Compete in a Kaggle competition Leaderboards Compete to advance AI progress Design New Challenges build an AI system that can take and pass any online course, then switch to tutor-mode and help you pass Open Source Guide Establish open source culture in your organization 4/29/2018 IBM #OpenTechAI 8
- 9. Leaderboards Framework AI Progresson Open Leaderboards - Benchmark Roadmap Perceive World Develop Cognition Build Relationships Fill Roles Pattern recognition Video understanding Memory Reasoning Social interactions Fluent conversation Assistant & Collaborator Coach & Mediator Speech Actions Declarative Deduction Scripts Speech Acts Tasks Institutions Chime Thumos SQuAD SAT ROC Story ConvAI Images Context Episodic Induction Plans Intentions Summarizatio n Values ImageNet VQA DSTC RALI General-AI Translation Narration Dynamic Abductive Goals Cultures Debate Negotiation WMT DeepVideo Alexa Prize ICCMA AT Learning from Labeled Training Data and Searching (Optimization) Learning by Watching and Reading (Education) Learning by Doing and being Responsible (Exploration) 2015 2018 2021 2024 2027 2030 2033 2036 4/29/2018 (c) IBM 2017, Cognitive Opentech Group 9 Which experts would be really surprised if it takes less time… and which experts really surprised if it takes longer? Approx. Year Human Level ->
- 10. Future of AI 4/29/2018 ©IBM Cognitive Opentech Group (COG) 10 Dota 2 “Deep Learning” for “AI Pattern Recognition” depends on massive amounts of “labeled data” and computing power available since ~2012; Labeled data is simply input and output pairs, such as a sound and word, or image and word, or English sentence and French sentence, or road scene and car control settings – labeled data means having both input and output data in massive quantities. For example, 100K images of skin, half with skin cancer and half without to learn to recognize presence of skin cancer.
- 11. 4/29/2018 © IBM 2015,IBM Upward University Programs Worldwide accelerating regional development 11
- 12. Trust: Two Communities 4/29/2018 ©IBM MAP COG2018 12 Service Science OpenTech AI Trust: Value Co-Creation, Transdisciplinary Trust: Ethical, Safe, Explainable, Open Communities Special Issue AI Magazine? Handbook of OpenTech AI?
- 13. Resilience: Rapidly Rebuilding FromScratch • Dartnell L (2012) The Knowledge: How to Rebuild Civilization in the Aftermath of a Cataclysm. Westminster London: Penguin Books. 4/29/2018 © IBM MAP COG2018 13
Editor's Notes
- #2 Please reuse – contact spohrer@us.ibm.com Reference: Spohrer, J (2018) OpenTechAI. Sunday April 29, 2018 http://slideshare.net/spohrer/opentechai_20180429_v1
- #3 Source: Vijay Bommireddipally (CODAIT Director) and Fred Reiss (CODAIT Chief Architect)
- #4 Source: Animesh Singh, IBM STSM and FfDL Chief Architect
- #10 Expert predictions on HMLI: URL https://arxiv.org/pdf/1705.08807.pdf 2015 Pattern Recognition Speech: URL: http://spandh.dcs.shef.ac.uk/chime_challenge/chime2016/results.html 2015 Pattern Recognition Images: URL: http://www.image-net.org/ 2015 Patten Recognition Translation: URL: http://www.statmt.org/wmt17/ 2018 Video Understanding Actions: URL: http://www.thumos.info/home.html > Also UCF101 http://crcv.ucf.edu/data/UCF101.php 2018 Video Understanding Context: URL: http://visualqa.org/challenge.html 2018 Video Understanding DeepVideo: URL: http://cs.stanford.edu/people/karpathy/deepvideo/ 2021 Memory Declarative: URL: https://rajpurkar.github.io/SQuAD-explorer/ Also Allen AI Kaggle Science Challenge https://www.kaggle.com/c/the-allen-ai-science-challenge 2024 Reasoning Deduction: URL: http://www.satcompetition.org/ 2027: Social Interaction Scripts: URL: https://competitions.codalab.org/competitions/15333 2030: Fluent Conversation Speech Acts: URL: http://convai.io/ 2030: Fluent Conversation Intentions: URL: http://workshop.colips.org/dstc6/ 2030: Fluent Conversation Alexa Prize: URL: https://developer.amazon.com/alexaprize 2033: Assistant & Collaborator Summarization: URL: http://rali.iro.umontreal.ca/rali/?q=en/Automatic%20summarization 2033: Assistant & Collaborator Debate: URL: http://argumentationcompetition.org/2015/ 2036: Coach & Mediator General AI: URL: https://www.general-ai-challenge.org/ 2036: Coach & Mediator Negotiation: URL: https://easychair.org/cfp/AT2017
- #11 1950 Nathaniel Rochester (IBM) 701 first commercial computer that did super-human levels of numeric calculations routinely. He worked at MIT on arithmetic unit of WhirlWind I programmable computer. Dota 2 is most recent August 11, 2017 as a super-human game player in Valve Dota 2 competition – Elon Musk’s OpenAI result. Miles Bundage tracks gaming progress: http://www.milesbrundage.com/blog-posts/my-ai-forecasts-past-present-and-future-main-post DOTA2: https://blog.openai.com/more-on-dota-2/
- #14 URL Amazon: https://www.amazon.com/Knowledge-Rebuild-Civilization-Aftermath-Cataclysm-ebook/dp/B00DMCV5YS/ URL TED Talk: https://www.youtube.com/watch?v=CdTzsbqQyhY Citation: Dartnell L (2012) The Knowledge: How to Rebuild Civilization in the Aftermath of a Cataclysm. Westminster London: Penguin Books. Jim Spohrer Blogs: Grand Challenge: http://service-science.info/archives/2189 Re-readings: http://service-science.info/archives/4416