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PODCAST

Mechanical Dreams

Mechanical Dirk
An automatically generated podcast about machine learning and natural language processing. The two fictional hosts talk about papers that I want to learn more about on my way to work.It"s not good, but it"s useful.
science natural sciences

All Episodes

10:07
Small-scale proxies for large-scale Transformer...
Mechanical Dreams ·
2024/11/26
en-us
10:28
Hardware Scaling Trends and Diminishing Returns in...
Mechanical Dreams ·
2024/11/25
en-us
8:33
Scaling Laws and Compute-Optimal Training Beyond...
Mechanical Dreams ·
2024/11/19
en-us
9:10
Understanding WSD Learning Rates
Mechanical Dreams ·
2024/11/18
en-us
7:29
Toward Understanding Why Adam Converges Faster Than...
Mechanical Dreams ·
2024/11/16
en-us
13:36
Amuro & Char - Analyzing the Relationship between...
Mechanical Dreams ·
2024/11/08
en-us
6:27
Evaluation data contamination in LLMs: How do we...
Mechanical Dreams ·
2024/11/07
en-us
7:40
How Does Critical Batch Size Scale in Pre-training?
Mechanical Dreams ·
2024/11/04
en-us
8:53
The Road Less Scheduled
Mechanical Dreams ·
2024/11/01
en-us
4:37
Learning-Rate-Free Learning by D-Adaptation
Mechanical Dreams ·
2024/10/31
en-us
9:54
Scaling FP8 Training to Trillion Token LLMs
Mechanical Dreams ·
2024/10/30
en-us
15:43
Geometric Dynamics of Signal Propagation Predict...
Mechanical Dreams ·
2024/10/29
en-us
8:58
A Survey on Model MoErging
Mechanical Dreams ·
2024/10/28
en-us
8:11
Liquid Time-constant Networks
Mechanical Dreams ·
2024/10/27
en-us
10:07
Scaling Laws for Predicting Downstream Performance in...
Mechanical Dreams ·
2024/10/26
en-us
16:52
A Spectral Condition for Feature Learning
Mechanical Dreams ·
2024/10/25
en-us
7:07
Don't decay the learning rate
Mechanical Dreams ·
2024/10/24
en-us
6:59
OLMoE
Mechanical Dreams ·
2024/10/23
en-us
11:32
An Empirical Model of Large Batch Training
Mechanical Dreams ·
2024/10/23
en-us
99 results

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