The backing method doesn’t matter as long as it works. This is clear from good RAG survey papers, Wikipedia, and (broadly) understanding the ethos of machine learning engineers and researchers: specific implementation details are usually means to an end, not definitional boundaries.
“The equiprobability bias (EB) is a tendency to believe that every process in which randomness is involved corresponds to a fair distribution, with equal probabilities for any possible outcome. The EB is known to affect both children and adults, and to increase with probability education. Because it results in probability errors resistant to pedagogical interventions, it has been described as a deep misconception about randomness: the erroneous belief that randomness implies uniformity. In the present paper, we show that the EB is actually not the result of a conceptual error about the definition of randomness.”
You can also find an ELI5 Reddit thread on this topic where one comment summarizes it as follows:
“People are conflating the number of distinguishable outcomes with the distribution of probability directly.”
The backing method doesn’t matter as long as it works. This is clear from good RAG survey papers, Wikipedia, and (broadly) understanding the ethos of machine learning engineers and researchers: specific implementation details are usually means to an end, not definitional boundaries.
This may be of interest:
https://github.com/ibm-self-serve-assets/Blended-RAG
> So we'd probably find an even split of people who would call this RAG or not.
Maybe but not likely. This is sometimes called the 50-50 fallacy or the false balance of probability or the equiprobability bias.
https://pmc.ncbi.nlm.nih.gov/articles/PMC4310748/
“The equiprobability bias (EB) is a tendency to believe that every process in which randomness is involved corresponds to a fair distribution, with equal probabilities for any possible outcome. The EB is known to affect both children and adults, and to increase with probability education. Because it results in probability errors resistant to pedagogical interventions, it has been described as a deep misconception about randomness: the erroneous belief that randomness implies uniformity. In the present paper, we show that the EB is actually not the result of a conceptual error about the definition of randomness.”
You can also find an ELI5 Reddit thread on this topic where one comment summarizes it as follows:
“People are conflating the number of distinguishable outcomes with the distribution of probability directly.”
https://www.reddit.com/r/explainlikeimfive/comments/1bpor68/...