Open||Source||Data
Gratis podcast

Open||Source||Data

Podcast af Charna Parkey

What can we learn from ai-native development through stimulating conversations with developers, regulators, academics and people like you that drive forward development, seek to understand impact, and are working to mitigate risk in this new world? Join Charna Parkey and the community shaping the future of open source data, open source software, data in AI, and much more. 

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Alle episoder

89 episoder
episode Building Trust in AI: From Open Source to Global Impact with host, Charna Parkey artwork
Building Trust in AI: From Open Source to Global Impact with host, Charna Parkey

Join Charna Parkey as she recaps a transformative year in AI, exploring the delicate balance between innovation and ethics. From open source communities to global regulations, discover how trust, diversity, and collaboration are shaping the future of technology.

08. okt. 2024 - 44 min
episode AI Regulations in Financial Services with Vinay Kumar artwork
AI Regulations in Financial Services with Vinay Kumar

Episode Quotes Vinay Kumar "I always believe in this: you don't need to solve a very large problem. Maybe it will take a lot of time to do that. A lot of resources to do that but something small, which you can have an opportunity to solve that could be very big or a fundamental for quite a bit is fantastic. Think of a scenario where your small fundamental idea is a base for another small fundamental idea for someone else."   Charna Parkey We also want to ground it a little bit in impact we've been seeing. And I think in the financial, banking, insurance industries it's not, I would say, an even distribution of advancement. Different countries have different regulations and different appetites for risk." Timestamps - [00:00:00] Introduction by Charna Parkey. - [00:01:57] Vinay Kumar begins talking about his journey. - [00:05:27] Discussion on building a search engine for STEM researchers. - [00:07:06] Challenges with early deep learning. - [00:09:55] Conversation shifts to ML observability. - [00:17:06] Discussion on simplifying verticalized AI. - [00:22:30] Impact of large language models (LLMs) on AI. - [00:30:58] Comparison of autonomous cars with AI regulation. - [00:37:58] Vinay mentions his science fiction novels. - [00:42:19] Conversation summary with Producer Leo Godoy.

24. sep. 2024 - 54 min
episode The importance and the Challenges & Solutions of AI Literacy with Brian Magerko artwork
The importance and the Challenges & Solutions of AI Literacy with Brian Magerko

QUOTES BRIAN MAGERKO “We're really trying to show that we could co-create experiences with AI technology that augmented our experience rather than served as something to replace us in creative act”. “For every project like [LuminAI], there's a thousand companies out there just trying to do their best to get our money... That's an uncomfortable place to be in for someone who has worked in AI for decades”. “I had no idea what was going to happen kind of in the future. When we started EarSketch... we were advised by a couple of colleagues to not do it. And here we are, having engaged over a million and a half learners globally”. CHARNA PARKEY "I remember the first robot that I built. It was part of the first robotic systems... and watching these machines work with each other was just crazy." “If you're building a product and your goal is to engage underrepresented groups, it is on you to make sure that you're educating the folks in a way that you're trying to reach.” EPISODE TIMESTAMPS (01:11) Brian Magerko's Journey into AI and Robotics  (05:00) LuminAI and Human-Machine Collaboration in Dance (09:00) Challenges of AI Literacy and Public Perception (17:32) Explainable AI and Accountability  (20:00) The Future of AI and Its Impact on Human Interaction  (22:10) EarSketch and learning: computing as a meaningful concept  (27:18) The need for interdisciplinary collaboration to ensure AI developments are beneficial for society as a whole. (30:02) Brian Magerko's next reshape of the future, better understanding models of collaboration and improvisation between people and computers (35:51) Brian Magerko's advice to researchers based on his own identity and experiences (44:20) Projects and updates related to EarSketch and LuminAI’s improvisation model. (46:24) Backstage with Executive Producer Leo Godoy

13. aug. 2024 - 54 min
episode Demystifying AI Governance: A Practical Guide for Organizations with Heather Domin artwork
Demystifying AI Governance: A Practical Guide for Organizations with Heather Domin

Timestamps 00:00:00 - 00:01:23 - Introduction 00:01:23 - 00:04:30 - Heather Domin's Journey 00:09:50 - 00:12:48 - Open Source and AI Ethics 00:12:48 - 00:15:25 - Generative AI and Governance 00:23:40 - 00:26:22 - Future of Responsible AI Practices 00:35:37 - 00:37:31 - Advice for the Audience 00:37:31 - 00:46:04 - Reflection on Risk and Hope in AI   Quotes Heather Domin "I think that each of us individually can scan our environment and understand, you know, where can I make an impact? What problem can I help solve? What is the next thing that I can really contribute to?" "There are absolutely ways to automate, you know, the prompt testing and many of the routine tasks that you want to leverage automation in that way so that you can actually have the humans focus on other, other things so they can focus on the critical thinking and outside the box sort of thinking that we want the humans to be focused on." Charna Parkey "I think that it's a hard for people getting into it for the first time to jump to hope if they've experienced something that they should fear in the past. By that, I mean, groups that have been marginalized by other forms of technology are not going to start hopeful with this new one that is is using their data without their permission.." "If for some reason I came to understand in a month what that meant, I should be able to go back and revoke and be like, nope, I actually don't want you to have that anymore. So I think that that would help people feel better."   Check Heather's paper: On the ROI of AI Ethics and Governance Investments  [https://cmr.berkeley.edu/2024/07/on-the-roi-of-ai-ethics-and-governance-investments-from-loss-aversion-to-value-generation/]   Connect with Heather [https://www.linkedin.com/in/heatherdomin/] Connect with Charna [https://www.linkedin.com/in/charnaparkey/]

30. jul. 2024 - 47 min
episode Transforming Food Systems with Regenerative AI with Ethan Soloviev artwork
Transforming Food Systems with Regenerative AI with Ethan Soloviev

Timestamps 1. Introduction and Background (00:00:00 - 00:01:16) 2. Ethan's Journey (00:01:16 - 00:05:12) 3. The Role of Food and Agriculture (00:05:12 - 00:06:52) 4. Investment in Regenerative Agriculture and Generative AI (00:06:52 - 00:07:44) 5. Levels of AI Impact (00:07:44 - 00:12:42) 6. HowGood's Use of AI (00:12:42 - 00:13:20) 7. Consumer Impact and Corporate Responsibility (00:13:20 - 00:15:44) 8. Future of AI in Food Systems (00:15:44 - 00:20:30) 9.  Innovative Perspectives on AI Training (00:20:30 - 00:21:10) 10. Action models in agriculture, optimizing water and soil use on a larger scale. (00:24:14 - 00:25:28) 11. Discussion on integrating human cultural geography into AI models. (00:27:37 - 00:30:00) 12. Charna and Ethan discuss procurement decisions and their impact on sustainability. (00:30:20- 00:40:15) 13. The ethical implications of AI in corporate and government decision-making. (00:42:01 - 00:54:31) 14. Leo brings up the impact of AI on consumers, discussing how AI can change purchasing decisions by highlighting product sustainability. (00:54:40 - 00:55:30) 15. Charna elaborates on using AI to understand different business models and how generational changes affect consumer choices. (00:55:47 - 00:57:32)   Quotes Ethan Soloviev "What if we're using ecological data? What if we're training on trees and insects and animals and whale song? What kind of questions would a gen AI trained on whale song and hummingbird language ask us?" Charna Parkey "If we have this great translator that is Gen AI, we already have text and language to code. We can do code generation. We can already interpret this code and tell me what it's going to do. Take that code to language. Why can't we do that with some of these other senses and these other measurements?" Connect with Ethan [https://www.linkedin.com/in/ethansoloviev/] Connect with Charna [https://www.linkedin.com/in/charnaparkey/]

16. jul. 2024 - 1 h 0 min
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