How Memorization Happens: Overparametrized Models

Posted on Mi 18 Dezember 2024 in ml-memorization

You've heard claims that we will "run out of data" to train AI systems. Why is that? In this article in the series on machine learning memorization you'll explore model size as a factor in memorization and the trend for bigger models as a general problem in machine learning.

To …


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How memorization happens: Novelty

Posted on Mo 09 Dezember 2024 in ml-memorization

So far in this series on memorization in deep learning, you've learned how massively repeated text and images incentivize training data memorization, but that's not the only training data that machine learning models memorize. Let's take a look at another proven memorization: novel examples.

Prefer to learn by video? This …


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How memorization happens: Repetition

Posted on Di 03 Dezember 2024 in ml-memorization

In this article in the deep learning memorization series, you'll learn how one part of memorization happens -- highly repeated data from the "head" of the long-tailed distribution.

Prefer to learn by video? This post is summarized on Probably Private's YouTube.

Recall from the data collection article that some examples are …


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Gaming Evaluation - The evolution of deep learning training and evaluation

Posted on Di 26 November 2024 in ml-memorization

In this article in the series on machine learning memorization, you'll dive deeper into how typical machine learning training and evaluation happens, a crucial step in ensuring the machine learning model actually "learns" something. Let's review the steps that lead up to training a deep learning model.

Two major steps are shown in rectangular boxes: Data Preparation and Preprocessing and Model Training and Evaluation. Above each of these major steps there are smaller boxes outlining substeps. The data preparation substeps are data collection, data cleaning and data labeling (if needed). The substeps for model training and evaluation are data encoding, model training and model evaluation. High-level steps to …


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Encodings and embeddings: How does data get into machine learning systems?

Posted on Mo 18 November 2024 in ml-memorization

In this series, you've learned a bit about how data is collected for machine learning, but what happens next? You need to turn the collected data -- images, text, video, audio or even just a spreadsheet -- into numbers that can be learned by a model. How does this happen?

TLDR (too …

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Machine Learning dataset distributions, history, and biases

Posted on Mi 13 November 2024 in ml-memorization

You probably are already aware that many machine learning datasets come from scraped internet data. Maybe you received the infamous GPT response: "Please note that my knowledge is limited to information available up until September 2021." You might have also read fear-mongering opinions and articles that companies will "run out …


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Deep learning memorization, and why you should care

Posted on Mo 04 November 2024 in ml-memorization

When's the last time that ChatGPT parroted someone else's words to you? Or the last time a diffusion model you used recreated someone's art, someone's photo, someone's face? Has Copilot given you someone else's code without permission or attribution? If this happened, how would you know for sure?

In this …


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A Deep Dive into Memorization in Deep Learning

Posted on So 03 November 2024 in ml-memorization

Want to learn more about how, when and why machine learning, particularly deep learning systems memorize data? By studying memorization, you'll learn more about how machine learning systems really function, along with how privacy works from a technical point-of-view. You'll also be better able to decide how, when and where …


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