Adam

Diffusion-GR2: Diffusion Generative Reasoning Re-ranker

Generative reasoning re-rankers achieve strong recommendation accuracy by emitting a chain-of-thought before re-ordering a candidate list, but they are slow at inference: an autoregressive (AR) decoder spends one sequential forward pass per reasoning token, and the reasoning trace far exceeds the ranking it produces. To reduce this cost, block-diffusion language models decode many positions in parallel over a few denoising steps and are substantially faster, yet naively converting an AR re-ranker into one opens two accuracy gaps: (1) a structural gap: answer positions are denoised in parallel

1-Lipschitz Neural Networks on Hadamard Manifolds

Controlling the Lipschitz constant of a neural network is a standard way to promote robustness and stability. Most existing constraining strategies are designed for Euclidean spaces. In this work, we construct and analyze a class of 1-Lipschitz neural networks on Hadamard manifolds. Our layers are of gradient-descent type, $1$-Lipschitz, and quasi-$α$-firmly nonexpansive. The core building blocks of the proposed architecture are Busemann functions, and we exploit the properties of Busemann gradient flows to design $1$-Lipschitz geometry-preserving layers. We provide explicit constructions and

Beyond Adam: SOAP and Muon for Faster, Label-Efficient Training of Machine Learning Interatomic Potentials

Machine learning interatomic potentials (MLIPs) have become a hallmark of AI for scientific simulation. While efforts on new architectures and datasets have led to increasingly accurate and general models, the choice of optimizer for training has largely remained unexplored, defaulting to Adam and its variants in the community. Here, we implement and systematically compare a class of recently proposed matrix-structured optimizers, including Muon, SOAP, and the hybrid SOAP-Muon, for training NequIP and Allegro MLIP models. We find that these optimizers can substantially outperform Adam in both

Meta’s Adam Mosseri says AI token budgets could soon be capped per engineer

Instagram head Adam Mosseri believes companies will eventually need to manage AI token spending the same way they manage payroll or other operating expenses, predicting that engineers could soon face limits on how much they spend using AI tools.

SkewAdam: A tiered optimizer that cuts MoE state memory by 97% (fits a 6.7B MoE on a 40GB GPU) [R]

<table> <tr><td> <a href="https://www.reddit.com/r/MachineLearning/comments/1v38k1m/skewadam_a_tiered_optimizer_that_cuts_moe_state/"> <img alt="SkewAdam: A tiered optimizer that cuts MoE state memory by 97% (fits a 6.7B MoE on a 40GB GPU) [R]" src="https://preview.redd.it/1457xi9fcqeh1.jpg?width=140&amp;height=90&amp;auto=webp&amp;s=879aad6df9e51a2735d91112d01518ff76ba3cbe" title="SkewAdam: A tiered optimizer that cuts MoE state memory by 97% (fits a 6.7B MoE on a 40GB GPU) [R]" /> </a> </td><t

Instagram’s Adam Mosseri: If you don&#8217;t like AI, &#8216;then you shouldn&#8217;t have it in your feed&#8217;

Though Instagram head Adam Mosseri doesn't want to filter out AI content on the platform, he argues that you "shouldn't have it in your feed" if you don't like it. "I don't think we should filter out AI content," Mosseri said during an interview on Lenny Rachitsky's podcast. "I think we should let you know [&#8230;]

Adam Shostack Talks Hugging Face & PHANTOM-B - Dark Reading

<a href="https://news.google.com/rss/articles/CBMimgFBVV95cUxPZGNZNGdGUHRkemtNcmxUZ01ZTE9zOTNiZ2thTWU4Z1ZrWWNhQjJwRzBxdE9fSmQ5dnBDcWZEaWJfRzJKVnkxUW1qYUp2b3RjNmhRQ18zci03RUs1cjhNWUQxUTBnZmQzQTNVcGF6R0RzNU1TRVZHSzE3dDNMcUcxS3NVNHdWYWJzYy03aWxhRG51S2xBQkc4ajV3?oc=5" target="_blank">Adam Shostack Talks Hugging Face & PHANTOM-B</a>&nbsp;&nbsp;<font color="#6f6f6f">Dark Reading</font>

adamlui/chatgpt-infinity

∞ Generate endless answers from all-knowing ChatGPT (on any topic!)

lordadamson/learning_llms

mrwadams/stride-gpt

An AI-powered threat modeling tool that leverages OpenAI's GPT models to generate threat models for a given application based on the STRIDE methodology.

adamlui/chatgpt-widescreen

🖥️ Award-winning extension to enhance ChatGPT with wide/full/tall-screen + spamblock modes. Also works on poe.com!

lucidrains/adam-atan2-pytorch

Implementation of the proposed Adam-atan2 from Google Deepmind in Pytorch

AdamBien/airails

AI and LLM conventions for modern Java 25 CLI apps, MicroProfile servers, serverless applications, Java AWS CDK IaC, and dependency-free static web development.

adamlui/autoclear-chatgpt-history

🕶️ Adds chat auto-clear functionality to ChatGPT for more privacy

Ryan-Adams57/model-fit

Terminal tool that ranks which LLMs can realistically run on your machine based on RAM, CPU, and GPU.