empirical-philosophy VS IF

One way that I've been framing this in my head (and in an application I'm building) is that gpt-3 will be useful for analytic tasks where as gpt-4 will be required for synthetic tasks. I'm using "analytic" and "synthetic" in the same way as in this writeup https://github.com/williamcotton/empirical-philosophy/blob/m...

Hey Simon! I've been digging your writings on LLMs lately.

I've been having some decent luck with some of the approaches that I've discussed in the following articles and projects:

From Prompt Alchemy to Prompt Engineering: An Introduction to Analytic Augmentation: https://github.com/williamcotton/empirical-philosophy/blob/m...

https://www.williamcotton.com/articles/writing-web-applicati...

https://github.com/williamcotton/transynthetical-engine

I'd love to hear your thoughts on the matter!

You’re not actually doing any research.

Here is my research: https://github.com/williamcotton/empirical-philosophy/blob/m...

It is clear that analytic augmentations will result in more factual information.

Your claims are unfounded and untested.

Take a look at

https://github.com/williamcotton/empirical-philosophy/blob/m...

https://langchain.readthedocs.io/en/latest/

They can be taught!

I've been developing a methodology around prompt engineering that I have found very useful:

https://github.com/williamcotton/empirical-philosophy/blob/m...

A few more edits and it's ready for me to submit to HN and then get literally no further attention!

That's not a rebuttable of a claim that Bing is more accurate.

A proper rebuttable would involve empirical evidence that Bing is no more accurate than other LLM tools that do not add analytical augmentations such as search results to their prompts.

Based on empirical evidence, I find that analytical augmentations do indeed result in more accurate results:

https://github.com/williamcotton/empirical-philosophy/blob/m...

Stability AI has gaps in SDXL for text, but they seem to do a better job with Deep Floyd ( https://github.com/deep-floyd/IF ). I have done a lot of interesting text things with Deep Floyd

They made https://github.com/deep-floyd/IF IF model which has a stronger understanding of text.

https://github.com/deep-floyd/IF It's a bit difficult to install right now, I can't install it on my card unfortunately. They had a huggingface space you could play with it but it seems offline right now. Hopefully it'll be incorporated into Auto1111 eventually.

I'm pretty sure this is the best open model for image + text: https://github.com/deep-floyd/IF

Text will be better due to simple scale, but the text will still be limited due to the use of a CLIP for text encoding (BPEs+contrastive). So that may be SD XL 0.9 but it should still be worse due to not using T5 like https://github.com/deep-floyd/IF

Ate you thinking of DeepFloyd IF? https://github.com/deep-floyd/IF

Or maybe people are conflating it with Deep Floyd, another SAI model: https://github.com/deep-floyd/IF

Deep Floyd IF does text really well and is out. https://github.com/deep-floyd/IF

use https://github.com/deep-floyd/IF, it uses LLM to generate exact art you need.