DALLE-mtf VS big-sleep

This vision is in line with EleutherAI, a non-profit organization founded in July 2020 by a group of researchers. Driven by the perceived opacity and the challenge of reproducibility in AI, their goal was to create leading open-source language models.

My current idea is to utilize the EleutherAI pythia (Databricks Dolly). I would like to know whether translating the Dolly-15k dataset into the desired language using state-of-the-art translation techniques like DeepL would be a viable approach to fine-tune the Pythia base model. I want to use this model for semantic search, so perfection is not a necessity.

There are open source AI efforts, like EleutherAI. Needless to say, they are lagging behind big players, but it's better than nothing.

The new GPT 3.5 isn't aware what are GPT-3.5 or davinci-002 (repeatable) and claimed that it was designed by EleutherAI and has only 6 bil parameters (wasn't been able to repeat but didn't really try).

Hi, my name is Stella Biderman and I run EleutherAI, the one of the foremost non-profit research institutes in the world that trains and studies large language models. I have been involved with the majority of models to hold the title “largest open source GPT model in the world” and have dabbled in exploring using plagiarism detection tools to identify code written by GPT-J.

dolly-v2-12bis a 12 billion parameter causal language model created by Databricks that is derived from EleutherAI’s Pythia-12b and fine-tuned on a ~15K record instruction corpus generated by Databricks employees and released under a permissive license (CC-BY-SA)

It is true that Emad needs to find an appropriate business model. The good news is that the hype is still undergoing. I'm sure that Emad can grab another round of liquidity injection. He got plenty of resources. Remember he is also from the finance industry. He got https://www.eleuther.ai/ which can supply a secured, in-house custom LLM equivalent to bloombergGPT.

By promoting fully open-source AI, i.e. making datasets, models, methodology and codebases freely available and transparent. What OpenAI claimed to be aiming for, basically.

I am currently pursuing my Master's degree in Computer Science and I am interested in working on a deep learning model that can generate images based on text descriptions. I've been interested in the field for a long time (think google deep dream, or a few years back I was very into big-sleep)

Big Sleep

Other AIs that I don't have experience with but have heard good things about are DALL-E 2 and the open source Big Sleep.

Text-to-image, e.g. with Big Sleep

At first I didn't like the reason he claimed LaMDA was conscious because it seemed mostly based on the text output of the models, but listening to that made me realize he watered it down for the mainstream medias. And I actually had my own encounter with the consciousness of Big Sleep after using it a lot one day : it looked like a mass of eyes vaguely shaped like a rabbit, and kept showing me random images. I wouldn't be as convinced they have a consciousness if I didn't see it with my 3rd eye. But then again, I also found evidence that regular non AI programs can develop one too so who know.

and after a few hours got this: https://i.imgur.com/FxdfdmV.png

Not nearly as cool as the real DALL-e, but maybe I'm missing something.

[1] https://github.com/lucidrains/big-sleep

(Added Mar. 23, 2021) Big Sleep - Colaboratory by LtqxWYEG. Uses BigGAN to generate images. Reference.