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Little p weekly Vol.10

2022-06-26 02:43:00 【SenseParrots】

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Academic frontier

Microsoft has restricted the use of facial recognition tools in the ethical reform of artificial intelligence

Microsoft is overhauling its AI ethics policy , And said it would no longer allow other companies to use their facial recognition technology to infer emotions 、 Sex or age .

As its new “ Responsible AI standards ” (Responsible AI principles from Microsoft) Part of , Microsoft says it intends to “ People and their goals are at the center of system design decisions ”. The company said , These high-level principles will bring real changes to practice , They will adjust some functions , At the same time, other functions will not be sold .

for example , Microsoft Azure Face Service is a facial recognition tool , By Uber As part of their authentication process . Now? , Any company that wants to use the facial recognition feature of the service needs to actively apply for it , Including companies that have built it into their products , To prove that they meet Microsoft's artificial intelligence ethical standards , And prove that these functions are beneficial to the end users and the society .

Microsoft said , Even companies that have been granted permission will no longer be able to use Azure Face Some of the more controversial features of , They will remove facial analysis techniques that claim to infer attributes such as emotional state and gender or age .

Microsoft has not completely abandoned emotion recognition —— The company will still use it internally , For example Seeing AI Such accessibility tools . The tool will use voice to broadcast the world around the visually impaired users .

Again , Microsoft has also restricted the use of its custom neurovoice technology , This technology allows the creation of synthetic sounds that sound almost the same as the original source . Earlier this year , Microsoft began to watermark its synthetic voice , Add subtle... To the output 、 An inaudible wave , This means that Microsoft can know that a recording is made with its technology .

DeepMind: Through large-scale interpretation of high accuracy differential image classification

Differential privacy (Differential Privacy) Is a mechanism to protect user data privacy , Prevent people who can access the machine learning model from extracting the information of a single training point . Differential privacy random gradient descent method (DP-SGD) It is the most popular in deep learning DP Training methods , This kind of information protection is realized by injecting noise into training .

However, previous work has found that ,DP-SGD It often leads to the performance of standard image classification benchmarks being greatly degraded . Besides , Some authors speculate that ,DP-SGD The performance on the large model is poor , Because the noise criterion required to protect privacy is proportional to the model dimension .

DeepMind The team proved DP-SGD The performance on the hyperparametric model is much better than previously thought . A combination of careful hyperparametric adjustment and simple techniques to ensure signal propagation and improve convergence , The author team is CIFAR-10 Upper use 40 Layer of Wide-ResNet stay \((8, 10^{-5})\)-DP New without additional data SOTA by 81.4%, Than before SOTA by 71.7% Improved . When it comes to pre trained NFNet-F3 When fine tuning , stay \((0.5, 8*10^{-7})\)-DP Next , The author team is ImageNet We got it 83.8% The highest accuracy of . Besides , The author team is still \((8, 8\cdot 10^{-7})\)-DP Realized under 86.7% The highest accuracy of , This is only more than the current non private SOTA low 4.3%.

For more information please visit DeepMind Of the topic The original page .

Basic technology

How to exclude `.DS_Store` file

MacOS All file systems contain a hidden file .DS_Store. Submitted to the Git when , It will be submitted together , I hate it very much .

This article teaches you a way , stay Git It is excluded from the global settings of , It is not necessary to set each library once .

Five minutes to understand software architecture patterns

The author uses simple language , Five common patterns of software architecture are explained , For example, the following figure shows the event driven architecture .

Design philosophy

20 A controversial programming point of view

This article summarizes StackOverflow above 20 A controversial programming point of view , such as “ For good software design , Using design patterns does more harm than good ”.