genioux Fact post by Fernando Machuca and Claude
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Introduction
Open-source generative models allow safer exploration avoiding risks from commercial services while requiring rigorous governance as capabilities rapidly evolve.
genioux GK Nugget
"Open-source innovation lowers barriers for testing generative AI but responsible oversight around bias, transparency and permissioning remains imperative to earn trust." — Fernando Machuca and Claude
genioux Foundational Fact
The article advocates open-source models like Bloom over commercial services to mitigate data ownership issues but notes licenses, potential leakage, updating training data, bias perpetuation and public skepticism still necessitate mitigation. It references guidelines including Stanford's AI Data Stewardship Framework.
Top 10 genioux Facts
Lighthouse of the Big Picture of the Digital Age |
- Closed models ingest proprietary data worrying managers considering exploration.
- Options exist avoiding external usage through localized experimenting and fine-tuning.
- Complex licensing around models and datasets requires legal parsing.
- Preventing exposure risks in fluid conversational interfaces needs addressing.
- Responsibly maintaining systems on current data presents tradeoffs.
- Inequalities in the world replicate absent thoughtful oversight.
- Transparency and permissioning build customer confidence and agency.
- Participatory development brings inclusivity over unilateral control.
- Best practices still emerging necessitate tracking advisement.
- Cross-disciplinary teams underscore multifaceted considerations.
Lighthouse of the Big Picture of the Digital Age |
Conclusion
While open platforms democratize generative AI access, responsible progress centralizing security, ethics, and public benefit remains a human imperative only fulfilled through vision spanning technology's benefits and limitations alike.
REFERENCE
The GK Article
Aron Culotta and Nicholas Mattei, Use Open Source for Safer Generative AI Experiments, MIT Sloan Management Review, November 20, 2023.
Aron Culotta
Aron Culotta is an Associate Professor of Computer Science at Tulane University¹². He is also the Director of the Center for Community-Engaged Artificial Intelligence³. His research investigates computational methods to learn about human behavior from online social networks, combining machine learning, natural language processing, and social network analysis¹.
His application domains include public health, emergency management, and political science². He obtained his Ph.D. in Computer Science from the University of Massachusetts, Amherst in 2008¹². He has been a Microsoft Live Labs Fellow, a Nayar Prize Finalist, and recipient of best paper awards at AAAI and CSCW¹.
His interdisciplinary research is supported by several NSF-funded collaborations with researchers in public health, political science, marketing, and emergency management¹. For more information about his work and publications, you can visit his personal website¹.
Source: Conversation with Bing, 12/5/2023
(1) Aron Culotta | tulane - School of Science & Engineering. https://sse.tulane.edu/aron-culotta.
(2) Aron Culotta - School of Science and Engineering. https://online.sse.tulane.edu/faculty/aron-culotta/.
(3) People | Jurist Center for Artificial Intelligence. https://ai.tulane.edu/ceai/people.
Nicholas Mattei
Nicholas Mattei is an Assistant Professor of Computer Science at Tulane University¹. His research focuses on the theory and practice of artificial intelligence, with a particular interest in problems that require a blend of techniques to develop systems and algorithms that support decision making for autonomous agents and/or humans¹.
Before joining Tulane, he was a Research Staff Member in the IBM TJ Watson Research Laboratory in the IBM Research AI – Reasoning Lab where he worked on a number of topics including Complex Question Answering / Natural Language Inference, Decision Making, and issues in AI, Ethics, and Society¹. He was also a senior researcher working with Prof. Toby Walsh in the AI & Algorithmic Decision Theory Group at Data61¹.
He received his Ph.D. from the University of Kentucky under the supervision of Prof. Judy Goldsmith in 2012¹. He has served on the SPC or PC of AAAI, AAMAS, AIES, IJCAI, COMSOC, ECAI, CP and other major AI conferences¹. He serves as the AI, Ethics, and Society Officer for ACM:SIGAI and as the Public Relations coordinator for JAIR¹.
For more information about his work and publications, you can visit his personal website¹.
Source: Conversation with Bing, 12/5/2023
(1) Nicholas Mattei | tulane - School of Science & Engineering. https://sse.tulane.edu/nicholas-mattei.
(2) Nicholas Mattei | Tulane University Innovation Institute. https://innovation.tulane.edu/nicholas-mattei.
(3) Tulane researcher recognized for work in artificial intelligence. https://sse.tulane.edu/content/tulane-researcher-recognized-work-artificial-intelligence.
(4) Tulane researcher recognized for work in artificial intelligence. https://news.tulane.edu/pr/tulane-researcher-recognized-work-artificial-intelligence.
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Source: Conversation with Bing, 11/27/2023
(1) g-f New World - Genioux.com Corporation. https://gnxc.com/g-f-new-world.
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Source: Conversation with Bing, 11/27/2023
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Source: Conversation with Bing, 11/27/2023
(1) “genioux facts”: The online program on "MASTERING THE BIG PICTURE OF .... https://blog.geniouxfacts.com/2023/09/g-f21310-genioux-ai-powered-chatbot.html.
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The categorization and citation of the genioux Fact post
g-f(2)1668 The 10 Most Read genioux Fact Posts of the Week (12/03/2023) |
Categorization
Type: Breaking Knowledge, Free Speech
g-f(2)1675: The Juice of Golden Knowledge
GK Juices or Golden Knowledge Elixirs |