yanglet

We just released the Agentic FinSearch, which is currently a Google extension. It is a user-friendly agent, a potential replacement of Bloomberg Terminal

Is it like a personal assistant that guides an individual through existing practical tools?

Any thoughts about the (financial) data sources, to avoid garbage input?

Thanks!

Thanks for sharing the links!! Appreciate it.

A few points to share:

1). Finance is high dynamic. BloombergGPT retrains LLM using a mixed dataset of finance and general sources is too much expensive (1.3M hours). Lightweight adaptation is highly favorable.

2). Internet-scale finance data (timely updates using an automatic data curation pipeline) is critical. BloombergGPT has privileged data access and API access. A promising alternative is "democratizing Internet-scale finance data".

3). Another key technology is "RLHF (Reinforcement learning from human feedback)", which is missing in BloombergGPT. RLHF enables learning individual preferences (risk-aversion level, investing habits, personalized robo-advisor, etc.)

1). Finance is high dynamic. BloombergGPT retrains LLM using a mixed dataset of finance and general sources is too much expensive (1.3M hours). Lightweight adaptation is highly favorable.

2). Internet-scale finance data (timely updates using an automatic data curation pipeline) is critical. BloombergGPT has privileged data access and API access. A promising alternative is "democratizing Internet-scale finance data".

3). Another key technology is "RLHF (Reinforcement learning from human feedback)", which is missing in BloombergGPT. RLHF enables learning individual preferences (risk-aversion level, investing habits, personalized robo-advisor, etc.)

We are aiming for feeding Internet-scale financial data into LLMs, and adapt LLMs to the finance sector. Happy to know your thoughts!

FinGPT better be open-source and open-finance.

https://news.ycombinator.com/item?id=35403167

DO NOT expect Wall Street to open-source LLMs nor open APIs.

Anyone interested to build a ChatGPT for FinTech, or FinGPT? I and my team are actively developing this project: https://github.com/AI4Finance-Foundation/ChatGPT-for-FinTech

Seems that chatGPT may help upgrade trade, like robo-advisor?

Is AI going to change algo-trading forever?

FinRL can be found here: https://github.com/AI4Finance-Foundation

There is a previous discussion here: https://news.ycombinator.com/item?id=30819436

The first author wrote several blogs about crypto trading using rl, available here: https://github.com/AI4Finance-Foundation/Blogs

Deep Reinforcement Learning for Cryptocurrency Trading: Practical Approach to Address Backtest Overfitting

Thanks for the information and sharing the paper. I also read it. Agree with you that the "simulation-to-reality gap" would be more critical to the reinforcement learning community.

NVIDIA's Isaac Gym project revealed GPU's capability of performing massively parallel simulation for gym-style environments. Detailed information can be found in the following paper:

[1] Makoviychuk, Viktor, et al. "Isaac Gym: High-Performance GPU Based Physics Simulation For Robot Learning." Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2). 2021.

At its release, people commented on Twitter that "it is the MNIST moment for reinforcement learning." And over the past year, I saw several follow-up works and tested NVIDIA's implementations.

For example, a demo by this blog

https://towardsdatascience.com/a-new-era-of-massively-parall...

The question is, does that technique help advance Reinforcement Learning, as expected?