laplacesdemon48

I recently subscribed to Perplexity Pro and prior to this release, was already strongly considering discontinuing ChatGPT Premium.

When I first subscribed to ChatGPT Premium late last year, the natural language understanding superiority was amazing. Now the benchmark advances, low latency voice chat, Sora, etc. are all really cool too.

But my work and day-to-day usage really rely on accurately sourced/cited information. I need a way to comb through an ungodly amount of medical/scientific literature to form/refine hypotheses. I want to figure out how to hard reset my car's navigation system without clicking through several SEO-optimized pages littered with ads. I need to quickly confirm scientific facts, some obscure, with citations and without hallucinations. From speaking with my friends in other industries (e.g. finance, law, construction engineering), this is their major use case too.

I really tried to use ChatGPT Premium's Bing powered search. I also tried several of the top rated GPTs - Scholar AI, Consensus, etc.. It was barely workable. It seems like with this update, the focus was elsewhere. Unless I specify explicitly in the prompt, it doesn't search the web and provide citations. Yeah, the benchmark performance and parameter counts keep impressively increasing, but how do I trust that those improvements are preventing hallucinations when nothing is cited?

I wonder if the business relationship between Microsoft and OpenAI is limiting their ability to really compete in AI driven search. Guessing Microsoft doesn't want to disrupt their multi-billion dollar search business. Maybe the same reason search within Gemini feels very lacking (I tried Gemini Advanced/Ultra too).

I have zero brand loyalty. If anybody has a better suggestion, I will switch immediately after testing.

This book had a big influence on me. I highly recommend it. I read both the first and second editions.

It is very clearly written, full of practical examples (with code), and doesn't assume heavy math knowledge.

This section from the preface sums up the intended audience:

"The principle audience is researchers in the natural and social sciences, whether new PhD students or seasoned professionals, who have had a basic course on regression but nevertheless remain uneasy about statistical modeling. This audience accepts that there is something vaguely wrong about typical statistical practice in the early twenty-first century, dominated as it is by p-values and a confusing menagerie of testing procedures. They see alternative methods in journals and books. But these people are not sure where to go to learn about these methods."

Is there a way to extend this to measure a multivariate relationship?

For example: Cor(X, Y & Z)

I know you could run them pairwise but it’s possible Cor(X, Y) and Cor(X, Z) are close to zero but Cor(X, Y & Z) is close to 1.