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I think some of the financial applications around LLMs right now are better suited for things like summarization, aggregation, etc.

We at Tradytics recently built two tools on top of LLMs and they've been super popular with our usercase.

Earnings transcript summary: Users want a simple and easy to understand summary of what happened in an earnings call and report. LLMs are a nice fit for that - https://tradytics.com/earnings

News aggregation & summarization: Given how many articles get written everyday in financial markets, there is need for a better ingestion pipelines. Users want to understand what's going on but don't want to spend several hours reading through news - https://tradytics.com/news



As more of the reports get written by layers of AI it makes me wonder how lossy and noisy this whole pipeline is becoming.


That's a fair point. But models like GPT4 do not hallucinate much when it comes to summarizing. So I don't think these applications contribute to anything negative.


Surprisingly, they hallucinate more than you might think.

https://x.com/lefthanddraft/status/1777495120910426436?s=46




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