> To collect such data, we have explored several approaches: using few-shot prompting with a long CoT as an example, directly prompting models to generate detailed answers with reflection and verification, gathering DeepSeek-R1-Zero outputs in a readable format, and refining the results through post-processing by human annotators.

> If you need to perform a case mapping on a string, you can use LCMap­String­Ex with LCMAP_LOWERCASE or LCMAP_UPPERCASE, possibly with other flags like LCMAP_LINGUISTIC_CASING. If you use the International Components for Unicode (ICU) library, you can use u_strToUpper and u_strToLower.

Its at a smaller scale, but it can be seen with counterfeit currency today. Cash-heavy businesses have to absorb whatever amount of counterfeits they accept, so they are really valuing your dollar at $0.99 if they might have to throw it out.

As per the article, they are arguing that seniors are particularly affected by climate change due to heat waves, and these are causing deaths.

The 2022 heatwaves had hundreds of deaths attributed to climate change in Switzerland: https://lenews.ch/2023/07/08/climate-change-behind-60-percen...

https://en.wiktionary.org/wiki/heart

Unsure if it’s pseudoscience, but similar to the argument around morning vs. evening preference being related to having someone alert for the tribe at the right times.

But there is also the downside of "tuning" the RAG to return less tokens you will miss extra context that could be useful to the model.

The main issues I see is that there is little distinction in what constitutes a crime that would fit under the "cybercrime" banner, potentially allowing a state that has e.g. anti-LGBT laws to request assistance in prosecuting that crime by e.g. getting de-anonymized data from a US-based social network.