RAM
TU Munich博士生Andreas Bergmeister提出的扩散模型强化学习后训练方法，通过Reinforce Adjoint Matching实现后训练提速50倍，基于第一性原理推导出可扩展的训练目标
Timeline (last 90 days)
The expert FFN weights of MoE models occupy most of the volume, but only a small portion is read each time, so this part should be placed in RAM, and when RAM is insufficient the operating system pages it in from the SSD.
When RAM ≥ 70% of the expert weights, the MoE model runs at almost the same speed as running entirely in memory; when RAM is between 40% and 70%, the speed fluctuates with the prompt; when RAM < 40%, it is usually not worth running.
When a model runs, its weights need to be loaded into RAM (system memory) or VRAM (video memory), and having large storage capacity does not mean the model can actually run.
Running AI models on-device requires more RAM, which is driving up demand for memory chips across the entire industry.
机器学习笔记本内存建议至少16GB，系统内存与显存是完全独立且不能互相替代的两个资源
All Facts (6)
显存带宽与系统内存带宽之间相差大约10倍
85%UnverifiedThe expert FFN weights of MoE models occupy most of the volume, but only a small portion is read each time, so this part should be placed in RAM, and when RAM is insufficient the operating system pages it in from the SSD.
50%UnverifiedWhen RAM ≥ 70% of the expert weights, the MoE model runs at almost the same speed as running entirely in memory; when RAM is between 40% and 70%, the speed fluctuates with the prompt; when RAM < 40%, it is usually not worth running.
50%UnverifiedWhen a model runs, its weights need to be loaded into RAM (system memory) or VRAM (video memory), and having large storage capacity does not mean the model can actually run.
50%UnverifiedRunning AI models on-device requires more RAM, which is driving up demand for memory chips across the entire industry.
50%Unverified机器学习笔记本内存建议至少16GB，系统内存与显存是完全独立且不能互相替代的两个资源
50%