Small is beautiful

"As technology progresses, we generally expect processing capabilities to scale up. 

"Every year, we get more processor power, faster speeds, greater memory, and lower cost. 

"However, we can also use improvements in software to get things running on what might otherwise be considered inadequate hardware. 

"Taking this to the extreme, while large language models (LLMs) like GPT are running out of data to train on and having difficulty scaling up, [DaveBben] is experimenting with scaling down instead, running an LLM on the smallest computer that could reasonably run one.

"Of course, some concessions have to be made to get an LLM running on underpowered hardware."