Created
July 28, 2024 01:09
-
-
Save ek/63d55fcf102512ba0b35e48b32d4830d to your computer and use it in GitHub Desktop.
# Summary and Key Points re: How AI is eating Finance — with Mike Conover of Brightwave
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| # How AI is eating Finance — with Mike Conover of Brightwave | |
| ### How we can use AI for as a "partner in thought", losing faith in long context windows for improved reasoning, and why we should stop anthropomorphizing LLMs | |
| ### Jun 11, 2024 | |
| [https://www.latent.space/p/brightwave](https://www.latent.space/p/brightwave) | |
| # Key Points from Mike Conover Interview on BrightWave and AI in Finance | |
| ## About BrightWave | |
| - [00:42](https://youtu.be/Uz2Qpp-GOkE?t=42) BrightWave is a startup founded by Mike Conover, focusing on AI-driven financial analysis | |
| - [04:51](https://youtu.be/Uz2Qpp-GOkE?t=291) Raised $6 million seed round led by Decibel, with participation from Point72 and Moonfire Ventures | |
| - [05:38](https://youtu.be/Uz2Qpp-GOkE?t=338) Aims to expand individuals' ability to reason about the structure of the economy and markets using AI | |
| ## Product and Technology | |
| - [09:36](https://youtu.be/Uz2Qpp-GOkE?t=576) Acts as a "partner in thought" for finance professionals | |
| - [31:56](https://youtu.be/Uz2Qpp-GOkE?t=1916) Uses multiple AI subsystems for specific tasks rather than a single large model | |
| - [35:49](https://youtu.be/Uz2Qpp-GOkE?t=2149) Employs RAG (Retrieval Augmented Generation) with context-aware prompting | |
| - [38:13](https://youtu.be/Uz2Qpp-GOkE?t=2293) Focuses on extracting structured information into knowledge graphs | |
| - [20:04](https://youtu.be/Uz2Qpp-GOkE?t=1204) Prioritizes grounded reasoning and factuality in outputs | |
| ## Key Features | |
| - [09:36](https://youtu.be/Uz2Qpp-GOkE?t=576) Can analyze complex financial scenarios and provide insights | |
| - [31:27](https://youtu.be/Uz2Qpp-GOkE?t=1887) Handles temporality of data, crucial for financial analysis | |
| - [34:00](https://youtu.be/Uz2Qpp-GOkE?t=2040) Balances private and public data sources in analysis | |
| - [40:00](https://youtu.be/Uz2Qpp-GOkE?t=2400) Provides highly facetable, pivotable product interface | |
| ## Team and Hiring | |
| - [06:07](https://youtu.be/Uz2Qpp-GOkE?t=367) Co-founded with Brandon Katara, who has experience in finance and deep learning | |
| - [1:03:55](https://youtu.be/Uz2Qpp-GOkE?t=3835) Hiring across AI, engineering, machine learning, and design roles | |
| ## Views on AI and Finance | |
| - [50:42](https://youtu.be/Uz2Qpp-GOkE?t=3042) Believes AI hedge funds may already exist in some form | |
| - [55:51](https://youtu.be/Uz2Qpp-GOkE?t=3351) Sees potential for AI in idea generation and thematic investing | |
| - [56:02](https://youtu.be/Uz2Qpp-GOkE?t=3362) Emphasizes human role in final decision-making and strategy alignment | |
| ## Open Source LLMs | |
| - [57:44](https://youtu.be/Uz2Qpp-GOkE?t=3464) Notes convergence in model behavior and diminishing returns on pretraining | |
| - [59:20](https://youtu.be/Uz2Qpp-GOkE?t=3560) Predicts future innovation in instruction tuning and fine-tuning data creation | |
| - [57:44](https://youtu.be/Uz2Qpp-GOkE?t=3464) Emphasizes importance of private evaluation datasets | |
| ## Industry Trends | |
| - [58:43](https://youtu.be/Uz2Qpp-GOkE?t=3523) Observes decreasing incentives for companies to train their own foundation models | |
| - [1:02:43](https://youtu.be/Uz2Qpp-GOkE?t=3763) Predicts focus shifting to differentiating models through specific behavioral fine-tuning | |
| --- | |
| # Summary - Key Points from Mike Conover Interview on BrightWave and AI in Finance | |
| ## About BrightWave | |
| - BrightWave is a startup founded by Mike Conover, focusing on AI-driven financial analysis | |
| - Raised $6 million seed round led by Decibel, with participation from Point72 and Moonfire Ventures | |
| - Aims to expand individuals' ability to reason about the structure of the economy and markets using AI | |
| ## Product and Technology | |
| - Acts as a "partner in thought" for finance professionals | |
| - Uses multiple AI subsystems for specific tasks rather than a single large model | |
| - Employs RAG (Retrieval Augmented Generation) with context-aware prompting | |
| - Focuses on extracting structured information into knowledge graphs | |
| - Prioritizes grounded reasoning and factuality in outputs | |
| ## Key Features | |
| - Can analyze complex financial scenarios and provide insights | |
| - Handles temporality of data, crucial for financial analysis | |
| - Balances private and public data sources in analysis | |
| - Provides highly facetable, pivotable product interface | |
| ## Team and Hiring | |
| - Co-founded with Brandon Katara, who has experience in finance and deep learning | |
| - Hiring across AI, engineering, machine learning, and design roles | |
| ## Views on AI and Finance | |
| - Believes AI hedge funds may already exist in some form | |
| - Sees potential for AI in idea generation and thematic investing | |
| - Emphasizes human role in final decision-making and strategy alignment | |
| ## Open Source LLMs | |
| - Notes convergence in model behavior and diminishing returns on pretraining | |
| - Predicts future innovation in instruction tuning and fine-tuning data creation | |
| - Emphasizes importance of private evaluation datasets | |
| ## Industry Trends | |
| - Observes decreasing incentives for companies to train their own foundation models | |
| - Predicts focus shifting to differentiating models through specific behavioral fine-tuning |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment