Mathy AI Substack
Mike Erlihson, Mathy AI, Shmulik Cohen, Teddy Lazebnik, Nurit Cohen IngerDeep learning paper reviews, blogs about machine learning techniques, LLM discussions
| Platform |  | Pricing | Only free issues | Publishes | Daily |
|---|---|---|---|---|---|
| Issues | 200 | Subscribers | Read | aiwithmike.substack.com |
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Latest Issues
Recent posts by this newsletter. Browse the email archive.
Nested Learning: Is Deep Learning Just a Stack of Optimizers?
Today’s paper fundamentally challenges the “stack of layers” paradigm that has defined deep learning for decades. The core, novel idea is to re-imagine a model not as a deep architecture, but as a deep stack of nested optimization problems....
Forget BIT, It is All about TOKEN
This paper argues that Shannon’s classical information theory, built on the ‘bit’, is fundamentally insufficient for understanding Large Language Models. Shannon’s theory solves the technical problem of transmitting symbols accurately (Leve...
Disentangling Memory from Reason: A Look Inside the Transformer’s Loss Landscape
We all know transformers are two-faced. One face is the brilliant reasoner that generalizes complex patterns. The other is a dull parrot that recites training data verbatim, a behavior that’s increasingly problematic for privacy and copyrig...
Rome Wasn’t Destroyed in a Day: On the Robustness of LLMs to Small Changes
In recent years, transformer-based LLMs with many neural network layers have become a central component in modern AI systems. However, they inherit the vulnerability of those same neural networks to adversarial inputs: tiny changes in the i...
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Authors
The writers behind this newsletter.
Seasoned Data Scientist and Math PhD with >20 years of experience in a wide range of algorithm development/data domains
AI Engineer and Master's student with a passion for making complex technology accessible. I share practical guides, project insights, and curated tech developments to help you become your own AI Superhero
Studying the integration between real-world problems and novel computational methods
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