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Edward G. Miner Library

AI: Home

A Comprehensive Resource on Artificial Intelligence Applications, Innovations, and Academic Pursuits

Welcome 👋

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:
AI in Medical Education: Faculty as Learners and Educators

May, 22nd, 2024 at 3:00 PM (EDT)

World Summit AI
October 9-10, 2024 · Taets Art & Event Park, Amsterdam

AI Guide by metaLAB



The AI Pedagogy Project was created by the metaLAB (at) Harvard within the Berkman Klein Center for Internet & Society

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

AI is characterized as having the following capabilities: 1) the ability to learn in a self-supervised way, 2) the ability to solve problems from various domains without extensive retraining, and 3) the ability to generalize between tasks.
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

IBM's AI GlossaryProvides definitions of key AI terms, especially relevant for understanding IBM's specific technologies and research.
AI For Anyone: The A-Z of AI - Offers a broad range of AI terms explained in an accessible manner.
Wikipedia: Glossary of Artificial Intelligence - A detailed glossary of AI terms and concepts.
Graphite Note - Comprehensive AI and Machine Learning Glossary

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.

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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?

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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?

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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 ...

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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.