r/mlscaling
19k members
r/mlscaling is a subreddit with 19k members. The community frequently discusses ai, scaling, models, training, and model, and the most common flair used is r, code, r, emp, x, and n, econ, hardware.
ML/AI/DL research on approaches using large models, datasets, and compute: "more is different"
Popular Topics in r/mlscaling
#1
Ai
: "Google DeepMind Presents: An Ai system to help scientists write expert-level empirical software"
110 posts
#2
Scaling
: "The Art of Scaling Reinforcement Learning Compute for LLMs—Khatri, Madaan et al 2025 (extensive 400k GPU-hour exploration of how RL scales)"
66 posts
#3
Models
: "Google Research: Introducing 'Nested Learning': A new ML paradigm for continual learning | "A new approach that views Models as a set of smaller, nested optimization problems, each with its own internal workflow, in order to mitigate or even completely avoid the issue of ' catastrophic forgetting""
44 posts
#4
Training
: ""Muon is Scalable for LLM Training", Liu et al 2025 {Moonshot AI}"
35 posts
#5
Model
: "Diffusion Models are Super, Data Learners"
32 posts
#6
Deep Learning
: "Loss Functions in Deep Learning: A Comprehensive Review"
23 posts
#7
Ml
: "Epoch AI estimates compute used by GPT-5"
21 posts
#8
Llm
: ""Llm Daydreaming", Gwern Branwen 2025"
20 posts
#9
Reasoning
: "Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities"
18 posts
#10
Language
: ""Diffusion Language Models are Super Data Learners", Ni et al. 2025"
18 posts
Flair Used in r/mlscaling
#1
R
: "Google Research: A New Paper Suggests That LLMs Don’t Just Memorize Associations, They Spontaneously Organize Knowledge Into Geometric Structures That Enable Reasoning"
50 posts
#2
Code
: "Google DeepMind Presents: An AI system to help scientists write expert-level empirical software"
3 posts
#3
R, Emp
: "DeepScientist: Advancing Frontier-Pushing Scientific Findings Progressively, Weng et al. 2025 [20k GPU-hours, >$60k in API costs, >1k autonomous experiments, surpassed human SotA in all 3 targeted ML tasks]"
3 posts
#4
X
: "Elon Musk pushes out more xAI founders as AI coding effort falters"
2 posts
#5
N, Econ, Hardware
: "Cerebras, an A.I. Chip Maker, Files to Go Public as Tech Offerings Ramp Up"
2 posts
#6
OP, D
: ""LLMs as Giant Lookup-Tables of Shallow Circuits", Niplav (metaphor for how to think of NN learning/capabilities)"
2 posts
#7
R, Emp, T
: "HRM-Text: Efficient Pretraining Beyond Scaling, Wang et al. 2026"
2 posts
#8
DM
: "Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities"
2 posts
#9
R, RL, Emp
: "Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning, Wang et al. 2025"
2 posts
#10
OA
: "Terence Tao's Thoughts On GPT-5.2 Fully Automously Solving Erdos Problem #728"
1 post
Member Growth in r/mlscaling
Yearly
+5k members(34.1%)
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Last updated: June 13, 2026