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Miner Library's Guide to AI includes knowledge that encompass a variety of resources related to neural networks, machine learning, and large language models.
AI Tool Evaluation Checklist
Events
Past Events:
Embracing the Digital Future of Healthcare Symposium
May 16th, 2023 8:30-4:00 pm
A Set of Accessible Talks on AI
May 20th, 2023 10 am-5 pm
Data + AI Summit by Databricks
San Francisco, June 26-29th, 2023
Virtual, June 28-29th, 2023
6th AAAI/ACM Conference on AI, Ethics, and Society
August 9-11th 2023
The AI Summit New York
Dec 6, 2023 - Dec 7, 2023 · New York City, NY
Upcoming Events:
AAMC Webinars and Online Courses
Utilizing AI for the Medical Education Classroom
04/30/2024 at 3:00 PM (EDT)
World Summit AI
October 9-10, 2024 · Taets Art & Event Park, Amsterdam
Machine Learning Datasets and Models
The Data Cards Playbook is an emerging metadata standard focused on increasing transparency and providing structured documentation for machine learning datasets and models. The following resource provides a basic description: https://ai.googleblog.com/2022/11/the-data-cards-playbook-toolkit-for.html
Overview
Littman ML, Ajunwa I, Berger G, et al. Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report. Stanford University, Stanford, CA, September 2021. Doc: http://ai100.stanford.edu/2021-report.
Glossaries
CBMM10 Panel: Research on Intelligence in the Age of AI
Poggio, T. (2023, October 7th). Center for Brains, Minds, and Machines. CBMM10 Panel: Research on Intelligence in the Age of AI [Video]. YouTube.
1:19-3:26: Discussion on the significance of theory in AI, focusing on comparing AI models with human intelligence. This segment offers insight into how neural networks might bypass the curse of dimensionality, a significant problem in machine learning and AI.
4:19-7:02: Geoffrey Hinton’s perspective on the evolution and potential of AI, discussing the role of neuroscience in artificial intelligence. Hinton's insights here are particularly valuable given his status as a pioneer in the field.
9:19-13:48: Pietro Perona’s take on the role of embodied intelligence in AI and the difference between learning from text and learning from a physical experience. This segment is key to understanding the broader concept of intelligence in AI.
22:48-29:03: Demis Hassabis emphasizes the subtle influences of neuroscience on AI development. Hassabis, as an AI leader with a background in neuroscience, provides a unique viewpoint on the synergies between these fields.
29:37-34:15: Ilya Sutskever’s thoughts on the future of AI, especially in relation to neuroscience. His insights give a glimpse into what future AI research might focus on, coming from a leading figure in the industry.
1:16:43-1:24:58: The panel engages in a broader discussion on the creativity of AI systems and their ability to generate new, original ideas. This segment is critical for understanding the limits and potential of current AI technologies.
Contact:
Consult your librarian to learn more:
Ehsan Moghadam, MLIS
I am currently developing library-hosted events highlighting the use of AI in medicine! If you have a topic that would make a great event please feel free to contact me.
News (University of Rochester)
Human brain’s ‘temporal scaffolding’ inspires new AI approaches
October 24, 2023 ... Associate Professor of Computer Science Christopher Kanan will develop deep-learning models and algorithms based on temporal scaffolding, a hypothesis about how the human brain uses sleep and awake periods to learn over time.
Keeping a Human in the Loop: Managing the Ethics of AI in Medicine
Oct. 19, 2023 ... Assistant Professor of Health Humanities and Bioethics, Jonathan Herington was a member of the AI Task Force of the Society for Nuclear Medicine and Medical Imaging, which laid out recommendations on how to ethically develop and use AI medical devices.
AI helps bring clarity to LASIK patients facing cataract surgery
September 20, 2023 ... Marcos' Lab are using machine learning algorithms to find relationships between pre- and post-operation data, providing parameters that can inform the best outcomes.
Online AI-based test for Parkinson’s disease severity shows promising results
September 6, 2023 ... Associate Professor of Computer Scientist Ehsan Hoque and his colleagues have harnessed machine learning to accurately identify signs of the neurological disease by analyzing facial muscles.
AI helps show how the brain’s fluids flow
June, 2023 ... Professor Douglas Kelley develops novel AI velocimetry measurements to accurately calculate brain fluid flow.
How will AI chatbots like ChatGPT affect higher education?
Feb, 2023 ... U of R administrators and faculty weigh in on the pros and cons of ChatGPT and AI chatbots, the newest online learning tools.
How can we be sure machine learning is accurate?
May 2, 2022 ... Associate Professor of Chemical Engineering Andrew White has developed a way to verify the predictions of machine learning models used in drug discovery by using counterfactuals.
More than words: Using AI to map how the brain understands ...
Mar 22, 2021 ... New research involving neuroimaging and AI, describes the complex network within the brain that comprehends the meaning of a spoken ...
Visit the following page to explore more AI news at the U of R.