Meeting minutes for 2023-07-13

Please find below the meetings notes for our 2023/07/13 session.

Timestamp	Speaker	Topic
00:39	Peter Smulovics (he/him, MS)	Welcomes everyone. Good evening. One or 2 more minutes for people to join.
03:17	Julia Ritter	Julia Ritter kicks off the meeting with meeting notices about project guidelines, codes of conduct, industry participation, antitrust policies, and the recording of meetings.
04:50	Peter Smulovics (he/him, MS)	Peter Smulovics requests attendees to visit the Github link for attendance.
05:03	Keith J. O'Donnell	Keith introduces the agenda and skips the Poc program part.
05:34	Keith J. O'Donnell	Keith provides updates on blogs, videos, upcoming events, and introduces new team members Carly Richmond, Leonardo Mordasini, and Polina Levyant.
09:02	Keith J. O'Donnell	Keith discusses AI, weak AI, strong AI, artificial general intelligence (AGI), and superintelligence. He then delves into the history of AI, including the Turing test and adversarial programs.
14:50	Keith J. O'Donnell	Keith mentions the XCD and adversarial programs playing checkers in the 1950s.
15:50	Keith J. O'Donnell	mentions the clever development of the first instance of Alpha beta through a serial network, laying the groundwork for future AI applications.
16:26	Keith J. O'Donnell	discusses the emergence of the term "artificial intelligence" and how people attempted to cheat homework using intelligent programs.
17:00	Keith J. O'Donnell	talks about the development of algorithms in applied mathematics and provides a quick break.
16:16	Keith J. O'Donnell	introduces an algorithm and challenges the audience to figure out its meaning.
16:16	Keith J. O'Donnell	confirms that the algorithm proves one plus one equals two and explains its significance in training algorithms for problem-solving.
17:00	Keith J. O'Donnell	describes the development of perception and the first single-layer neural network by Frank Rosenblatt.
17:00	Keith J. O'Donnell	mentions the development of chatbots, industrial robots, and advancements in natural language processing in the 1960s.
18:00	Keith J. O'Donnell	highlights the significance of Dendr and its impact on organic chemistry and drug development.
18:00	Keith J. O'Donnell	discusses the first general-purpose robot, Shaky, and its ability to reason and make decisions.
18:00	Keith J. O'Donnell	talks about the development of backpropagation and its impact on deep learning.
18:00	Keith J. O'Donnell	mentions the progress made in the 1970s and Marvin Minsky's role in speech recognition.
19:00	Keith J. O'Donnell	introduces the Stanford car, the first autonomous vehicle, and its navigation capabilities.
19:00	Keith J. O'Donnell	talks about advancements in robotics, including music-reading robots and self-driving cars in the 1980s.
19:00	Keith J. O'Donnell	mentions the portrayal of technology in movies and its impact on public perception.
20:00	Keith J. O'Donnell	discusses the development of long short-term memory (LSTM) and its applications in handwriting and speech recognition.
20:00	Keith J. O'Donnell	recounts the game between Gary Kasparov and Deep Blue, showcasing computers' ability to play complex games.
20:00	Keith J. O'Donnell	describes the Furby as a simulation of artificial intelligence and its impact on familiarizing people with machine learning concepts.
20:00	Keith J. O'Donnell	moves into the 21st century, highlighting the advancements in robots working in hospitality and self-driving cars.
21:00	Keith J. O'Donnell	mentions the triumph of AlphaGo and its ability to defeat human players in the game of Go.
21:00	Keith J. O'Donnell	provides an overview of the current landscape of AI development tools and discusses their applications in finance and insurance.
21:00	Keith J. O'Donnell	mentions the plans to create primers focusing on commercialization, ethics, and security vulnerabilities.
22:00	Keith J. O'Donnell	talks about the importance of collaboration and use within the open-source community.
22:00	Keith J. O'Donnell	discusses technology readiness levels and their relevance in assessing the maturity of AI technologies.
23:00	Keith J. O'Donnell	introduces the concept of technology readiness scale and its different stages.
24:00	Keith J. O'Donnell	explains the purpose of technology readiness levels in evaluating the maturity of AI technologies.
25:00	Keith J. O'Donnell	discusses specific technology readiness levels for different AI disciplines and identifies potential blockers.
26:00	Keith J. O'Donnell	highlights the importance of model validation, monitoring, and machine learning deployment platforms.
26:00	Keith J. O'Donnell	talks about the importance of resource optimization and the need for specific hardware and operating systems.
27:00	Keith J. O'Donnell	discusses computer vision and natural language processing, emphasizing the need for common frameworks and standards.
28:00	Keith J. O'Donnell	addresses the intersection of quantum computing and AI and mentions the Venn diagram overlap of emerging technologies.
28:00	Keith J. O'Donnell	responds to a comment about missing aspects in the primer related to use cases, training, and data sources.
29:00	Keith J. O'Donnell	encourages discussion and comments from the participants.
29:00	Keith J. O'Donnell	opens the floor for any further comments or questions.
29:26	Velvárt András	mentions the entire process of developing an AI and raises questions about key participants in the industry and the need for compute power.
29:32	Velvárt András	asks about copyright and licensing considerations for the primer and its readiness.
30:02	Keith J. O'Donnell	proposes creating a series of videos to address the mentioned topics and adds them to the list of things to include in the primer.
30:30	Nick Williams	suggests including a primer section on definitions of terms and discusses the importance of providing content that doesn't require watching videos.
31:03	Keith J. O'Donnell	acknowledges the vastness of the field and agrees to include governance and regulatory aspects in the primer.
31:29	Keith J. O'Donnell	thanks Michael Wilson for his contribution and discusses the value propositions that will be included in the primer.
34:48	Nick Williams	suggests adding a primer section on governance and regulations in the financial sector for using AI.
35:54	Keith J. O'Donnell	mentions including security vulnerabilities, fair use, and licenses in the primer and highlights the need for governance considerations.
36:05	Keith J. O'Donnell	invites participants to raise any questions or contribute to the discussion.
36:11	Keith J. O'Donnell	presents the core blockers identified for experimentation, including AI chipsets, neural networks, and generative adversarial networks.
38:18	Keith J. O'Donnell	discusses the need to understand the needs of industries and establish a common data language and synthetic data rule set.
39:07	Keith J. O'Donnell	mentions the importance of working with regulators, audit and risk professionals, and addressing data quality and observability.
39:26	Keith J. O'Donnell	highlights the need for experiment tracking and addressing technical debt in AI-specific tasks and platforms.
39:37	Keith J. O'Donnell	emphasizes the mathematical modeling of drifting bias and the importance of avoiding PR disasters like the "Tay to Twitter" incident.
40:04	Keith J. O'Donnell	introduces the goal of creating a machine learning application in a box for micro deployment and experimentation on various platforms.
40:13	Keith J. O'Donnell	discusses the customization of out-of-the-box machine learning kits for specific purposes, such as micro-training a natural language processing system for analyzing financial contracts.
40:24	Keith J. O'Donnell	highlights the importance of customizing machine learning models and modules for specific purposes and use cases.
40:43	Keith J. O'Donnell	emphasizes the need for technologists within the fintech industry to improve efficiency and optimization in their applications.
41:12	Keith J. O'Donnell	mentions the importance of computer vision and its industrial maturity for diverse use cases.
41:58	Keith J. O'Donnell	discusses the significance of natural language processing and its potential for increasing industrial collaboration.
42:13	Keith J. O'Donnell	invites the community to contribute thoughts, ideas, and suggestions for the Zenith project.
42:39	Nick Williams	raises a question about the security and veracity of data used in machine learning models.
43:10	Keith J. O'Donnell	acknowledges the importance of data security and welcomes feedback from the community.
43:14	Keith J. O'Donnell	suggests making iterative updates to the primer based on community input and requirements.
45:00	Keith J. O'Donnell	provides information on accessing the mailing list for updates and publications related to Zenith.
46:05	Keith J. O'Donnell	announces the focus of the next deep dive session on commercialization and enterprise readiness.
46:44	Keith J. O'Donnell	encourages community members to contribute to the ongoing development and refinement of the primer.
47:25	Keith J. O'Donnell	opens the floor for any additional discussion or topics from the community.
51:32	Velvárt András	inquires about getting started with the primer and suggests collaborative document creation.
52:41	Keith J. O'Donnell	acknowledges the need to get the primer document up and running and plans for further discussions on specific topics.
53:21	Keith J. O'Donnell	expresses the goal of enhancing accessibility solutions through computer vision and collaboration.
53:59	Keith J. O'Donnell	invites community input, ideas, and suggestions for the primer and Zenith project.
54:09	Nick Williams	raises concerns about the security aspect of data used for financial advice and suggests addressing it in the primer.
54:36	Keith J. O'Donnell	acknowledges the importance of data security and encourages feedback and suggestions from the community.
56:19	Keith J. O'Donnell	emphasizes the iterative nature of the primer and welcomes community involvement and additions.