Open Source Deep Learning for Developers at Red Hat Summit

While we are a long way out from machines that can perform artificial general intelligence (AGI) tasks, deep learning can be used for many narrow artificial intelligence (AI) tasks including image or audio classification, facial recognition, object recognition, image caption generation, and natural language processing. We will explore how developers can easily integrate open source deep learning models into their applications.

Transcript

1. Open Source
   Deep Learning
   for Developers
   —
   Bradley Holt
   Program Manager, Developer Advocacy
   Center for Open-Source Data & AI Technologies
   ↳ (CODAIT)
   @BradleyHolt
   

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2. It’s a hybrid world
   Enterprises want the ability to
   span traditional IT, private and
   public clouds.
   Containers are strategic
   Enterprises need agility to meet
   the demands of their clients and
   their markets.
   Innovation is the path forward
   Mission critical projects need
   industry leading middleware
   and data.
   IBM and Red Hat Share Three Common Beliefs
   2 © 2019 IBM Corporation
   IBM and Red Hat – Partners for 20 years
   For over 20 years IBM and Red Hat have collaborated with the open source
   community to drive innovation and power businesses around the world.
   

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3. Artificial
   Intelligence
   Center for Open-Source Data & AI Technologies (CODAIT) / May 8, 2019 / © 2019 IBM Corporation
   @BradleyHolt
   

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4. ↳ General AI
   Metal Skull With Terminator Eye by L.C. Nøttaasen, on Flickr (CC BY-SA 2.0).
   

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5. ↳ Broad AI
   -[ electrIc b88Gal88 ]- by JD Hancock, on Flickr (CC BY 2.0).
   

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6. ↳ Narrow AI
   Danbo on the Lookout by IQRemix, on Flickr (CC BY-SA 2.0).
   

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7. Approaches to
   Artificial Intelligence
   Center for Open-Source Data & AI Technologies (CODAIT) / May 8, 2019 / © 2019 IBM Corporation
   Machine Learning (ML)
   • Predictive analytics
   • Data mining
   • Anomaly detection
   • Email filtering
   Deep Learning
   • Image or audio
   classification
   • Facial recognition
   • Object recognition
   • Image caption
   generation
   • Natural language
   processing
   @BradleyHolt
   

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8. https://github.com/CODAIT/magicat
   

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9. 23895621638_535be71dee_k.jpg
   37038669284_899d7784a9_k.jpg
   37489697170_31d05aa027_k.jpg
   37699459356_24fd526a5e_k.jpg
   37699976806_5ce694be36_k.jpg
   Animal photos by Susanne Nilsson, on Flickr (CC BY-SA 2.0).
   

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10. Scan Directory with magicat
    $ magicat . --contains sheep
    Scanning directory '~/tfjs-demos/magicat' for sheep...
    Sheep found in:
    37038669284_899d7784a9_k.jpg
    37489697170_31d05aa027_k.jpg
    @BradleyHolt
    

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11. Save Image Segment with magicat
    $ magicat 37699976806_5ce694be36_k.jpg --save horse
    The image '37699976806_5ce694be36_k.jpg' contains the
    following segments: background, horse.
    saved 37699976806_5ce694be36_k-horse.png
    Animal photos by Susanne Nilsson, on Flickr (CC BY-SA 2.0).
    

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12. ↳ Deep Learning Code Patterns
    @BradleyHolt
    

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13. Software Programming
    Center for Open-Source Data & AI Technologies (CODAIT) / May 8, 2019 / © 2019 IBM Corporation
    Untitled by Marcin Wichary, on Flickr (CC BY 2.0).
    

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14. Center for Open-Source Data & AI Technologies (CODAIT) / May 8, 2019 / © 2019 IBM Corporation
    01011001001011000001
    10101101010100100110
    00010110101010011100
    10101010110101010100
    10001001011101000101
    Software Program
    Business Logic
    @BradleyHolt
    

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15. Center for Open-Source Data & AI Technologies (CODAIT) / May 8, 2019 / © 2019 IBM Corporation
    01011001001011000001
    10101101010100100110
    00010110101010011100
    10101010110101010100
    10001001011101000101
    Software Program
    Input
    Program Execution
    Output
    @BradleyHolt
    

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16. Deep Learning & ML vs.
    Software Programming
    Center for Open-Source Data & AI Technologies (CODAIT) / May 8, 2019 / © 2019 IBM Corporation
    Deep Learning & ML
    • Training
    • High-quality examples
    (i.e., training data)
    • Approximation of a
    correct function
    Software Programming
    • Programming
    • Set of direct
    instructions
    • Precisely-defined
    function
    @BradleyHolt
    

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17. Center for Open-Source Data & AI Technologies (CODAIT) / May 8, 2019 / © 2019 IBM Corporation
    Input Layer Hidden Layers Output Layer
    @BradleyHolt
    

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18. Fashion-MNIST dataset by Zalando Research, on GitHub (MIT License).
    Backpropagation
    Labeled Training Data
    Coat
    Sneaker
    T-shirt Sneaker
    Pullover
    Output Errors
    Pullover
    Coat
    Coat
    Sneaker T-shirt
    ❌
    ❌ ❌
    

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19. Fashion-MNIST dataset by Zalando Research, on GitHub (MIT License).
    Input Output
    Sneaker
    Neural Network Inferencing
    

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20. Center for Open-Source Data & AI Technologies (CODAIT) / May 8, 2019 / © 2019 IBM Corporation
    @BradleyHolt
    

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21. @BradleyHolt
    

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22. Applying Deep Learning
    Center for Open-Source Data & AI Technologies (CODAIT) / May 8, 2019 / © 2019 IBM Corporation
    Data Science
    Expertise
    Computing
    Resources
    High-Quality
    Training Data
    Model Deployment Time
    Model Integration
    Inferencing Code
    And more…
    @BradleyHolt
    

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23. Model Asset Exchange
    Classify
    Generate
    Recognize
    Center for Open-Source Data & AI Technologies (CODAIT) / May 8, 2019 / © 2019 IBM Corporation
    @BradleyHolt
    

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24. Microservice
    Center for Open-Source Data & AI Technologies (CODAIT) / May 8, 2019 / © 2019 IBM Corporation
    Choose deployable model
    Deep Learning asset from the Model Asset Exchange (MAX)
    Deploy
    Swagger specification Inference endpoint Metadata endpoint
    Input preprocessing, model execution, and output post-processing
    Deploy
    model
    Use
    model
    @BradleyHolt
    

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25. AI Lifecycle
    Center for Open-Source Data & AI Technologies (CODAIT) / May 8, 2019 / © 2019 IBM Corporation
    Deploy &
    Run
    Operate
    & Manage
    Prepare,
    Build &
    Train
    @BradleyHolt
    

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26. Preparing, Building,
    and Training AI Models
    Center for Open-Source Data & AI Technologies (CODAIT) / May 8, 2019 / © 2019 IBM Corporation
    Model Asset Exchange (MAX)
    @BradleyHolt
    

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27. Deploying and
    Running AI Models
    Center for Open-Source Data & AI Technologies (CODAIT) / May 8, 2019 / © 2019 IBM Corporation
    ONNX.js
    Model Asset Exchange (MAX)
    @BradleyHolt
    

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28. Operating and
    Managing AI Systems
    Fabric for Deep Learning (FfDL)
    Train and deploy deep learning models on Kubernetes using TensorFlow,
    Caffe2, PyTorch, and other frameworks
    AI Fairness 360 (AIF360)
    Comprehensive set of fairness metrics for machine learning models,
    explanations for these metrics, and algorithms to mitigate bias in models
    Adversarial Robustness Toolbox (ART)
    Python library for adversarial attacks and defenses for neural networks
    with multiple framework support
    @BradleyHolt
    

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29. IBM Data & AI Portfolio
    Center for Open-Source Data & AI Technologies (CODAIT) / May 8, 2019 / © 2019 IBM Corporation
    The Ladder to AI
    Pre-built Use Cases
    Watson Applications
    Multicloud Data & AI Platform
    IBM Cloud Platform for Data
    Hybrid Data Management
    Db2 Family
    Data Governance & Integration
    InfoSphere Family
    Open Source meets a
    multicloud, working as ONE
    Watson
    Machine
    Learning
    Watson
    Knowledge
    Catalog
    Watson
    Studio
    Watson
    OpenScale
    Prepare Build Manage
    Run
    @BradleyHolt
    

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30. Watson Data Science Platform
    Center for Open-Source Data & AI Technologies (CODAIT) / May 8, 2019 / © 2019 IBM Corporation
    Build and Deploy Upon Open Source Frameworks
    Watson
    Studio
    A universal runtime to embed,
    share and optimize AI models
    Design, build and train AI models,
    with visual modeling & generation
    Watson
    Machine
    Learning
    Watson
    OpenScale
    Operate and scaling AI value &
    usage with trust & transparency
    Unify on a Multicloud Data & AI Platform
    Watson
    Knowledge
    Catalog
    Data Discovery
    Data Preparation
    Policy-based Catalogs
    Visual Design
    Develop & Train
    Automation (AutoAI)
    Deploy & Manage
    Model-ops
    Retraining
    Optimize Outcomes
    Explainability & Lineage
    Automated Evolution
    Unified catalog to data users find,
    curate, categorize and share data
    Prep Build Run Manage
    @BradleyHolt
    

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31. What will you
    build with
    deep learning?
    Dynamic Earth - Continental Shelf by NASA Goddard Space Flight Center, on Flickr (CC BY 2.0).
    

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32. Resources: Machine Learning Libraries
    • TensorFlow
    https://www.tensorflow.org/
    • Train your first neural network: basic classification | TensorFlow
    https://www.tensorflow.org/tutorials/keras/basic_classification
    • Keras
    https://keras.io/
    • PyTorch
    https://pytorch.org/
    • Caffe2
    https://caffe2.ai/
    @BradleyHolt
    

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33. Resources: IBM Developer
    • IBM Developer
    https://developer.ibm.com/
    • IBM Cloud
    https://ibm.biz/Bd2NAr
    • Center for Open-Source Data & AI Technologies (CODAIT)
    http://codait.org/
    • IBM Developer Model Asset Exchange (MAX)
    https://developer.ibm.com/exchanges/models/
    • magicat
    https://github.com/CODAIT/magicat
    @BradleyHolt
    

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34. Resources: Preparing, Building, and
    Training AI Models
    • Project Jupyter
    https://jupyter.org/
    • IBM Developer Model Asset Exchange (MAX)
    https://developer.ibm.com/exchanges/models/
    • IBM Watson Knowledge Catalog
    https://www.ibm.com/cloud/watson-knowledge-catalog
    • IBM Watson Studio
    https://www.ibm.com/cloud/watson-studio
    @BradleyHolt
    

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35. Resources: Deploying and Running AI Models
    • Data Mining Group (PMML & PFA)
    http://dmg.org/
    • ONNX
    https://onnx.ai/
    • ONNX.js
    https://github.com/Microsoft/onnxjs
    • TensorFlow.js
    https://js.tensorflow.org/
    • TensorFlow Lite
    https://www.tensorflow.org/lite
    • Core ML
    https://developer.apple.com/machine-learning/
    • IBM Watson Machine Learning
    https://www.ibm.com/cloud/machine-learning
    @BradleyHolt
    

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36. Resources: Operating and Managing AI Systems
    • Fabric for Deep Learning (FfDL)
    https://github.com/IBM/FfDL
    • AI Fairness 360 (AIF360)
    https://github.com/IBM/AIF360
    • Adversarial Robustness Toolbox (ART)
    https://github.com/IBM/adversarial-robustness-toolbox
    • IBM Watson OpenScale
    https://www.ibm.com/cloud/watson-openscale
    @BradleyHolt
    

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37. Thank you.
    Center for Open-Source Data & AI Technologies (CODAIT) / May 8, 2019 / © 2019 IBM Corporation
    Bradley Holt
    Program Manager, Developer Advocacy
    Center for Open-Source Data & AI Technologies (CODAIT)
    —
    ibm.com
    @BradleyHolt
    

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38. Center for Open-Source Data & AI Technologies (CODAIT) / May 8, 2019 / © 2019 IBM Corporation
    

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