From 0a9103678954b9a912cde62f258d6716305fe440 Mon Sep 17 00:00:00 2001 From: Vijay Janapa Reddi Date: Tue, 17 Oct 2023 18:20:33 -0400 Subject: [PATCH] Built site for gh-pages --- .nojekyll | 2 +- about.html | 6 + acknowledgements.html | 6 + ai_for_good.html | 6 + benchmarking.html | 6 + case_studies.html | 6 + community.html | 6 + contributors.html | 22 +- copyright.html | 6 + data_engineering.html | 6 + dedication.html | 6 + dl_primer.html | 6 + efficient_ai.html | 6 + embedded_ml.html | 6 + embedded_ml_exercise.html | 6 + embedded_sys.html | 6 + embedded_sys_exercise.html | 12 +- frameworks.html | 6 + front.html | 6 + generative_ai.html | 6 + hw_acceleration.html | 6 + index.html | 6 + introduction.html | 6 + learning_resources.html | 6 + ondevice_learning.html | 6 + ops.html | 6 + optimizations.html | 6 + privacy_security.html | 6 + references.html | 6 + responsible_ai.html | 6 + robust_ai.html | 747 +++++++++++++++++++++++++++++++++++++ search.json | 51 ++- sustainable_ai.html | 12 +- tools.html | 6 + training.html | 6 + workflow.html | 6 + zoo_datasets.html | 6 + zoo_models.html | 6 + 38 files changed, 1022 insertions(+), 16 deletions(-) create mode 100644 robust_ai.html diff --git a/.nojekyll b/.nojekyll index 75b70e5b..2346b079 100644 --- a/.nojekyll +++ b/.nojekyll @@ -1 +1 @@ -296f76c5 \ No newline at end of file +319bc4cb \ No newline at end of file diff --git a/about.html b/about.html index 94b0ef59..b9fc4508 100644 --- a/about.html +++ b/about.html @@ -312,6 +312,12 @@ 19  Sustainable AI + +
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    Contributors

    Marcelo Rovai
    Marcelo Rovai
    📖 -Jessica Quaye
    Jessica Quaye
    📖 +Ikechukwu Uchendu
    Ikechukwu Uchendu
    📖 -Matthew Stewart
    Matthew Stewart
    📖 +ishapira
    ishapira
    📖 -Shvetank Prakash
    Shvetank Prakash
    📖 +oishib
    oishib
    📖 -Marco Zennaro
    Marco Zennaro
    📖 +Vijay Janapa Reddi
    Vijay Janapa Reddi
    📖 -Vijay Janapa Reddi
    Vijay Janapa Reddi
    📖 +Matthew Stewart
    Matthew Stewart
    📖 sjohri20
    sjohri20
    📖 @@ -449,13 +455,13 @@

    Contributors

    -Ikechukwu Uchendu
    Ikechukwu Uchendu
    📖 +Shvetank Prakash
    Shvetank Prakash
    📖 -oishib
    oishib
    📖 +Marco Zennaro
    Marco Zennaro
    📖 -ishapira
    ishapira
    📖 +Jessica Quaye
    Jessica Quaye
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    Conclusion

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  • diff --git a/robust_ai.html b/robust_ai.html new file mode 100644 index 00000000..397c887c --- /dev/null +++ b/robust_ai.html @@ -0,0 +1,747 @@ + + + + + + + + + + +MACHINE LEARNING SYSTEMS - 20  Robust AI + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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    20  Robust AI

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    Robust AI focuses on ensuring that AI systems operate reliably and safely in real-world environments. As AI systems are deployed in critical applications, from healthcare to autonomous vehicles, it’s essential that they can handle unexpected situations, adversarial attacks, and hardware or software faults. This chapter delves into the various challenges and solutions associated with building robust AI systems, especially for TinyML.

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    21 Hardware Resilience

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    Explanation: With the proliferation of TinyML on edge devices, the hardware on which these models run can be exposed to various environmental factors and wear-and-tear. Ensuring hardware resilience is crucial to maintain consistent AI performance.

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    21.1 Compute Faults

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    Description: Discusses issues related to faults in the computation units, such as CPUs, GPUs, and custom accelerators. This can include issues like overheating, transistor failures, or other malfunctions.

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    21.2 Memory Faults

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    Description: Addresses faults in the memory components of a system, including RAM, cache, and storage. Topics can include bit flips, wear-out, and other memory-related issues.

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    22 Software Resilience

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    Explanation: Software forms the backbone of any AI system. Ensuring its resilience means that the system can handle unexpected inputs, software bugs, or other issues without catastrophic failure.

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    22.1 Framework Faults

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    Description: Discusses potential issues in the software stack, from the OS to the AI framework. This can include bugs, version incompatibilities, or other software-related problems.

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    22.2 Faulty Inputs

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    Description: Explores how AI systems can handle unexpected or corrupted inputs. This is especially important for systems in the real world where input data can be noisy or unreliable.

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    23 Model Resilience

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    As the core of any AI system, the model’s resilience to various challenges, from adversarial attacks to real-world data shifts, is paramount for reliable operation.

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    23.1 Worst-case Faults

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    Description: Investigates the model’s behavior under worst-case scenarios, such as extreme data values or conditions outside the training distribution.

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    23.2 Adversarial Attacks

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    Description: Discusses potential threats where malicious actors intentionally manipulate inputs to deceive the AI model, and strategies to defend against these attacks.

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    24 Conclusion

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    Explanation: Conclude with the key highlights.

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    Edited by Prof. Vijay Janapa Reddi (Harvard University)
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    This book was built with Quarto.
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    + + + + \ No newline at end of file diff --git a/search.json b/search.json index 692c7193..e81526f3 100644 --- a/search.json +++ b/search.json @@ -25,7 +25,7 @@ "href": "contributors.html", "title": "Contributors", "section": "", - "text": "We extend our sincere thanks to the diverse group of individuals who have generously contributed their expertise, insights, and time to enhance both the content and codebase of this project. Below you will find a list of all contributors. If you would like to contribute to this project, please see our GitHub page.\n\n\n\n\n\n\n\n\nMarcelo Rovai📖\n\n\nJessica Quaye📖\n\n\nMatthew Stewart📖\n\n\nShvetank Prakash📖\n\n\nMarco Zennaro📖\n\n\nVijay Janapa Reddi📖\n\n\nsjohri20📖\n\n\n\n\nIkechukwu Uchendu📖\n\n\noishib📖\n\n\nishapira📖" + "text": "We extend our sincere thanks to the diverse group of individuals who have generously contributed their expertise, insights, and time to enhance both the content and codebase of this project. 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