Understand the rapid development timeline of large language models and its implication for open-source initiatives. 0:25 Adopt low-rank adaptation (Lora) and quantization techniques to make the training of large language models more accessible. 5:59 Explore FinGPT as a potential framework for generating financial large language models, despite its current limitations. 10:00 Recognize the significance of data quality over data scale in fine-tuning large language models. 13:14 Consider creating open, goal-specific, fine-tuned financial large language models to advance the field beyond the capabilities of closed models like Bloomberg GPT. 18:18 Publish and share data sets and trained model weights to democratize the development of financial large language models. 21:32 Challenge proprietary control over large language models and contribute to the open-source development to ensure equitable access and innovation. 21:53
I am 100% agree what you al mention : AI the only way to stop a bad person with AI is a good person with AI. AI is make for the humanity and not for a select people that make the rules
Michael, you mention some strong views on open-sourcing these AI models etc (which I agree with) but how about open-sourcing the portfolioLab, ArbitrageLab and MLFinLab? :D
they just wanted to get published in NeuralIPS conf. and get some media attention. FinGPT is a crap. I looked at the code. I can develop that in a week. But what is the point of developing such a useless open source which solves nothing. Bloomberg GPT is also crap if any one evaluated it in detail.
![[1hr Talk] Intro to Large Language Models](http://i.ytimg.com/vi/zjkBMFhNj_g/mqdefault.jpg)
Understand the rapid development timeline of large language models and its implication for open-source initiatives. 0:25
Adopt low-rank adaptation (Lora) and quantization techniques to make the training of large language models more accessible. 5:59
Explore FinGPT as a potential framework for generating financial large language models, despite its current limitations. 10:00
Recognize the significance of data quality over data scale in fine-tuning large language models. 13:14
Consider creating open, goal-specific, fine-tuned financial large language models to advance the field beyond the capabilities of closed models like Bloomberg GPT. 18:18
Publish and share data sets and trained model weights to democratize the development of financial large language models. 21:32
Challenge proprietary control over large language models and contribute to the open-source development to ensure equitable access and innovation. 21:53
I am 100% agree what you al mention : AI the only way to stop a bad person with AI is a good person with AI.
AI is make for the humanity and not for a select people that make the rules
I think the project has advanced in the last couple of months.
Truly enjoy watching your research and analysis, keep it going .
Michael, you mention some strong views on open-sourcing these AI models etc (which I agree with) but how about open-sourcing the portfolioLab, ArbitrageLab and MLFinLab? :D
Super insightful! We will be contributing towards these open source models and tools, but also still early days.
great knowledge! thank you!
Random comment, I hear your South African accent lol. Much love from SA!
amazing video
This is gold.
Well the video's conclusion is basically finGPT is not so useful and have lots of loose ends and hardly any useful at all.
Presumably, with things moving so fast, this video is quickly obsolete?
Have you heardmof openbb terminal. Also a platform connecting but massive potential for llm.
they just wanted to get published in NeuralIPS conf. and get some media attention. FinGPT is a crap. I looked at the code. I can develop that in a week. But what is the point of developing such a useless open source which solves nothing. Bloomberg GPT is also crap if any one evaluated it in detail.
Have examples of a good project?
Your take on BB terminal?
What a shame!