yuxt

This makes more sense when the compute is tied to local solar, so excess generation can be turned into useful processing instead of being wasted or exported cheaply. That is closer to the Lektra model.

when was the last time NYC had any snow?

In the late 1980s, I went on an expedition along Kazakhstan's eastern shore of the Caspian Sea. One of our stops was supposed to be a fishing village, but when we got there, it was completely empty. Hundreds of mud huts sat abandoned as everyone had just disappeared. In one of the yards, a camel was still there. It felt haunting, like walking through a ghost town. The strangest part? There was no sea anywhere nearby! The Caspian had dried up so quickly that people had to leave their homes behind because they couldn’t live there anymore.

The paper "RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture" compares Retrieval-Augmented Generation (RAG) and fine-tuning techniques in Large Language Models (LLMs). It proposes pipelines and evaluates their trade-offs using popular LLMs like GPT-4. The paper includes a detailed case study in agriculture to provide location-specific insights to farmers. Results show that fine-tuning improves model accuracy significantly, and when combined with RAG, it enhances accuracy even further. The paper demonstrates how LLMs can be adapted for industry-specific knowledge, potentially transforming various industrial domains.

Look into stablecoins or layer 2

The issue is not really that the government is bad, the problem is it has become a proxy for ultra rich to push their agenda. You can probably make it more efficient by limiting corporate sponsorship and making it more transparent. Millennials don't have many options or tools at their disposal to influence the direction we are heading.