What is federated learning and why do Big Tech companies like Amazon love it?

Why Federated Learning is a game-changer for safer and more efficient AI

3 min readOct 26, 2023

Do you understand Federated Learning? Well, you should- it’s a game-changer for distributed AI. Companies like Amazon rely on it heavily to do their data processing.

Think of all the Alex Devices, Prime Video apps, and different devices people use for their Amazon accounts. If Amazon directly sent the data back to the centers, their costs would spiral out of control. Not to mention, the huge privacy red flag of Amazon Data centers storing your conversations, shopping, etc. Clearly, this is not a good idea. But then, how would you update the models based on new user interactions?

What if you just let the models be updated on the local device? Say, one day I watch a lot of horror movies on Prime on my phone. So we update the recommendation systems on my phone to account for my new tastes. Once these updates have been made, I share the updates with the Amazon centers. You, my love, have just learned about federated learning.

This has several benefits. Firstly, the data of model updates are much smaller than the raw data, which makes it much cheaper to process and store. Secondly, this comes with a huge benefit when it comes to privacy. Even if someone did gain access to this data, all they’d see is mumbo jumbo. The model update data is not human-readable, so no one can see what shows you’ve been binging. And without knowing the exact architecture, it can’t be plugged into models to reconstruct your habits.

Federated Learning is one of the 3 techniques that Amazon uses to make their AI safer. To learn about the other techniques, read the following breakdown:

How Amazon makes Machine Learning Trustworthy

With all the discussion around Bias in ChatGPT and Machine Learning, these techniques might be very helpful

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