Mathy AI Substack
Mike Erlihson, Mathy AI, Shmulik Cohen, Omri Sapir, Niv Cohen, Andrey Finkelshtein, Barak Or, Shlomi BereznikDeep learning paper reviews, blogs about machine learning techniques, LLM discussions
| Platform |  | Pricing | Only free issues | Publishes | Daily |
|---|---|---|---|---|---|
| Issues | 245 | Subscribers | Read | aiwithmike.substack.com |
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Latest Issues
Recent posts by this newsletter. Browse the email archive.
Conceptual-Level Planning in Latent Space
You might remember the paper on Concept Language Models that I reviewed about six months ago. Well, there is a follow-up, and I’m happy about it because I really liked the original idea.
The Geometry of Probabilities in LLMs
Continuing the line of reviews with somewhat “tough” mathematics regarding LLMs. This time, the paper discusses the subject of “concept shifting” within the representation space of our models. For example, if you want the model to mention a...
Merging via Lie Algebra: Preserving Manifold Geometry in Deep Model Merging
Prepare yourselves for a slightly “tough” experience with this review, mathematically speaking, of course…
LLMs as Operators on Measures: A Clean Mathematical Pipeline for Tokenization, Training, Attention, and Decoding
This paper’s novelty is not a new model class, but a disciplined re-expression of the entire modern LLM stack as a sequence of explicit mathematical objects and maps. It reads like an attempt to make LLM engineering “closed under definition...
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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
Applied ML & NLP Researcher
PhD candidate - Weizmann Institute of Science
AI and Data Science Expert
AI Researcher, Entrepreneur, and Educator I work on building reliable artificial intelligence systems, from deep learning algorithms to real-world deployment, and on training professionals to apply AI correctly, rigorously, and responsibly.
Shlomi Bereznik is a data scientist studying public discourse, opinion, and text using statistical modeling and machine learning. He is also a wildlife volunteer and bird observer exploring the intersection of data science and the natural world.
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