GPT 4 can self-correct and improve itself. With exclusive discussions with the lead author of the Reflexions paper, I show how significant this will be across a variety of tasks, and how you can benefit.

I go on to lay out an accelerating trend of self-improvement and tool use, laid out by Karpathy, and cover papers such as Dera, Language Models Can Solve Computer Tasks and TaskMatrix, all released in the last few days.

I also showcase HuggingGPT, a model that harnesses Hugging Face and which I argue could be as significant a breakthrough as Reflexions. I show examples of multi-model use, and even how it might soon be applied to text-to-video and CGI editing (guest-starring Wonder Studio). I discuss how language models are now generating their own data and feedback, needing far fewer human expert demonstrations. Ilya Sutskever weighs in, and I end by discussing how AI is even improving its own hardware and facilitating commercial pressure that has driven Google to upgrade Bard using PaLM.

Reflexion Results: https://bit.ly/3KxRtC5
Karpathy Tweet: https://twitter.com/karpathy/status/1640042620666920960
Reflexion GPT 4 Post: https://bit.ly/3K62zwI
Reflexion paper: https://bit.ly/4349qiz
ALFWorld: https://bit.ly/3KbdgOk
Sparks Report: https://bit.ly/4349tuL
GPT 4 Technical Report: https://bit.ly/3KuxX9h
DERA Dialogue: https://bit.ly/43gv9Er
Language Models Can Solve Computer Tasks: https://bit.ly/3K6zH7m
HuggingGPT: https://bit.ly/4317aZF
TaskMatrix Paper: https://bit.ly/437sPQ2
Language Models Can Self-Improve: https://bit.ly/3KsTVcX
Wonder Studio: https://twitter.com/WonderDynamics/status/1633627396971827200
Alpaca Paper: https://stanford.io/3GeqfOj
Ilya Interview: https://www.youtube.com/watch?v=Yf1o0TQzry8&t=997s
Reuters Nvidia: https://reut.rs/3GeqhFV
Bard Upgrade: https://nyti.ms/430Iz7c

https://bit.ly/435ug1i