Meeting minutes for 2023-08-24
Please find below the meetings notes for our 2023/08/24 session.
| Timestamp | Speaker | Topic |
|---|---|---|
| 00:00:35 | Keith O'Donnell | The meeting begins, Keith welcomes participants, and James enters the room. |
| 00:00:48 | Patrick Downing | Patrick Downing mentions recording the meeting. |
| 00:01:21 | Keith O'Donnell | Keith discusses the music and mentions Charlie's presence. |
| 00:02:04 | James McLeod | James talks about building a music playlist for calls. |
| 00:02:18 | N/A | Laughter and random sounds. |
| 00:03:18 | James McLeod | James welcomes attendees and introduces the theme. |
| 00:04:38 | N/A | Discussion about starting calls with music. |
| 00:05:40 | Kendall Waters-Perez | Kendall provides legal and conduct reminders. |
| 00:06:46 | Keith O'Donnell | Keith gives information about upcoming events. |
| 00:08:11 | N/A | A fantasy-themed introduction to the meeting's agenda. |
| 00:08:29 | N/A | Introduction to the agenda and the flexible nature of the meeting. |
| 00:10:03 | Keith O'Donnell | Keith announces the upcoming showcase by Matt Bain. |
| 00:10:30 | Keith O'Donnell | Keith announces the new schedule for SIG meetings. |
| 00:11:45 | Keith O'Donnell | Keith introduces the deep dive segment by Matt Bain. |
| 00:15:14 | Matt Bain | Matt demonstrates AI-powered analysis of application models. |
| 00:20:39 | Matt Bain | Matt discusses potential use cases of AI language models. |
| 00:22:05 | Keith O'Donnell | Keith presents administrative details, Github repo, mailing list. |
| 00:22:21 | Keith O'Donnell | Keith invites participants to take action after the meeting. |
| 00:23:20 | Keith O'Donnell | Keith concludes the presentation and opens the floor for discussion. |
| 00:24:10 | James McLeod | James McLeod references a question in the chat about the stability of Chat GPT and its non-deterministic nature. |
| 00:24:21 | James McLeod | James raises the question of whether Chat GPT is stable and discusses the variance in its quality when run multiple times. |
| 00:24:34 | Keith O'Donnell | Keith talks about his experience using Chat GPT for code reviews and vulnerability testing, leveraging its non-deterministic nature to explore various perspectives. |
| 00:24:46 | Keith O'Donnell | Keith continues discussing the potential applications of Chat GPT for penetration testing and addressing challenges related to determinism. |
| 00:25:04 | Keith O'Donnell | Keith refers to a presentation by Matt using Chat GPT for architecture discussions and mentions the need to enhance open source tools like LLAMA to be more robust. |
| 00:25:22 | Keith O'Donnell | Keith opens the floor for others to share their views on the topic of Chat GPT's determinism and stability. |
| 00:25:38 | Keith O'Donnell | Keith acknowledges a correction from Ricardo about LLAMA not being open source. |
| 00:25:59 | Ricardo Sueiras | Ricardo Sueiras expresses interest in the topic of AI and its simultaneous appeal and frustration due to its non-reliable nature. |
| 00:26:17 | Ricardo Sueiras | Ricardo discusses the challenges of using AI, especially in regulated industries that require repeatability and consistency. |
| 00:26:35 | Keith O'Donnell | Keith shares his perspective on ChatGPT, seeing it as an assistant that offers alternative viewpoints rather than a fully reliable tool. |
| 00:26:55 | Keith O'Donnell | Keith emphasizes the potential use of ChatGPT as an assistant and points out its limitations for full-fledged production. |
| 00:27:24 | James McLeod | James McLeod asks a question to Ricardo and Keith about the differences between LLAMA and ChatGPT, as well as the challenges of open source AI. |
| 00:27:29 | James McLeod | James requests clarification on LLAMA and open source AI models and their differences from proprietary models. |
| 00:27:48 | James McLeod | James reflects on the importance of understanding terminology for those new to the topic. |
| 00:27:55 | Keith O'Donnell | Keith asks Ricardo to elaborate on LLAMA and open source AI models. |
| 00:28:01 | Ricardo Sueiras | Ricardo explains the challenges of defining open source AI, including data and infrastructure considerations, and mentions efforts to define open source AI standards. |
| 00:28:15 | Ricardo Sueiras | Ricardo discusses the complexities of open source AI models and the differences between open source and open innovation. |
| 00:28:49 | Alvin Shih | Keith, Ricardo, and Alvin share insights on open source AI, the challenges of sourcing information, and the importance of trust and transparency. |
| 00:29:59 | Ricardo Sueiras | Ricardo poses a question about the group's comfort level with using proprietary AI models as a foundation for open source tools. |
| 00:30:50 | Keith O'Donnell | Keith reflects on the potential challenges of using proprietary AI models as an abstraction layer for open source tools. |
| 00:31:06 | Alvin Shih | Alvin discusses the idea of using AI models as a starting point and mentions a project called Supercharger that aims to generate code with nonzero temperature. |
| 00:32:04 | Alvin Shih | Alvin and Keith share insights on AI models and their potential applications, along with the challenges of trust, sourcing, and innovation. |
| 00:33:14 | James McLeod | James McLeod suggests introducing participants and their roles to provide context for the discussion. |
| 00:33:27 | Alvin Shih | Alvin Shih introduces himself as a developer from Morgan Stanley, specializing in open source and machine learning research. |
| 00:34:17 | Ricardo Sueiras | Ricardo Sueiras introduces himself as a developer at AWS with expertise in open source and innovation, focusing on open source strategy and emerging technologies. |
| 00:35:10 | Keith O'Donnell | Keith asks for further contributions from participants on the topic of open source AI and proprietary models. |
| 00:36:11 | Ricardo Sueiras | Ricardo discusses the challenges of vendor lock-in, trust, and standardization in the context of open source AI and proprietary models. |
| 00:37:04 | James McLeod | James McLeod shares his perspective on the benefits of open source, the importance of transparency, and the challenges of building trust in AI models. |
| 00:40:52 | Carly Richmond emphasizes the importance of sourcing information, references, and documentation in AI models, along with the challenges of determining accuracy and building trust. | |
| 00:42:23 | James McLeod | James McLeod introduces the topic, reflecting on the recent London user group meeting where concerns were raised about the transparency of AI-generated responses. |
| 00:43:01 | Ricardo Sueiras | Ricardo Sueiras builds on the concern of transparency and control in AI systems, especially in the context of financial services. He highlights the challenges of understanding and influencing AI-generated responses. |
| 00:43:37 | Ricardo Sueiras | Ricardo Sueiras discusses the difficulties architects face in knowing who has control over AI systems and how to ensure reliable responses, given the growing complexity of these tools. |
| 00:44:18 | Keith O'Donnell | The conversation shifts to the Brain Trust, an amalgamation of financial services members focusing on open source AI. Michael Wilson shares the progress his team has made in integrating generative AI with platforms and discusses the importance of taxonomy and entitlement in handling large-scale AI content. |
| 00:45:40 | Michael Wilson | Michael Wilson explains their work in API integration and publishing AI content, emphasizing the significance of proper entitlement and organizational taxonomy to manage the increasing volume of AI-generated content. |
| 00:47:08 | Michael Wilson | Michael Wilson provides information about how interested parties can join the Brain Trust and engage with the community. Keith J. O'Donnell elaborates on the structure of the Brain Trust and its involvement in various financial services discussions. |
| 00:49:26 | Keith O'Donnell | Keith J. O'Donnell encourages interested individuals to reach out for membership details and highlights the benefits of being part of the Brain Trust and broader Finos community. |
| 00:49:31 | Keith O'Donnell | Keith J. O'Donnell acknowledges the progress and playfulness in the Zenith meetings and announces upcoming themes. |
| 00:49:40 | Ricardo Sueiras | Participants discuss their experiences with generative AI tools. Ricardo Sueiras shares his observations about the effectiveness of such tools, particularly in working with established technologies versus emerging ones. The limitations and challenges of using these tools, as well as the importance of developer experience, are discussed. |
| 00:52:04 | Michael Wilson | Michael Wilson commends the progress made in integrating AI with platforms and acknowledges the fun and innovation that participants bring to the discussions. |
| 00:53:00 | James McLeod | James McLeod invites participants to share updates about their work, experiences, and experiments with AI tools. |
| 00:53:19 | András Velvárt | András Velvárt presents a different perspective, suggesting that generative AI tools can be helpful for experienced developers to learn new technologies and overcome hurdles. Ricardo Sueiras and others express their views on the potential benefits and limitations of these tools in different learning scenarios. |
| 01:00:01 | Ricardo Sueiras | Ricardo discusses copyright concerns related to code generated by AI tools. He highlights the recent legal developments, such as the inability to copyright content created solely by AI. |
| 01:00:58 | Keith O'Donnell | Keith wraps up the meeting, summarizing the discussions and encouraging participants to stay engaged through the website and related activities. |