Tag Archives: Artificial Intelligence

Tech Tip: Bluesky

This month I’m highlighting a decentralized social app called Bluesky. It was developed by former Twitter CEO, Jack Dorsey. It aims to create a new form of social media that is open, transparent, and community-driven. The platform uses an open-source framework and has a Twitter-like user interface with algorithmic choice, federated design, and community-specific moderation. Its goal is… Read More »

Free GenAI prompt literacy course, resources

Nick Gaspar was a member of the Generative AI Advisory (GAIA) Committee that wrote the GenAI report for the university. “During that time I saw a widening gap of knowledge across the university when it came to writing prompts for AI, so I built a free prompt literacy course for the campus community.” AI prompts are text or… Read More »

Tech Tip: Arc Max

This month, I’m highlighting some new, innovative AI features that were recently added to the already impressive Arc web browser: Arc Max. Rather than simply adding a sidebar for ChatGPT like many other browsers are doing, they identified five specific integrations that can make browsing the web easier and more enjoyable: Each of them may be individually enabled… Read More »

Tech Tip: Upscayl

This month’s tip is an AI tool for upscaling low-quality images with surprisingly good accuracy and detail: Upscayl. It’s an excellent app for those looking to enhance the quality of their photos, especially those taken with older digital cameras. Multiple settings are available, like selecting the type of image, how much to upscale, file type, and advanced users… Read More »

Getting started with generative artificial intelligence: U-M Instructor Guide

The U-M Teaching and Technology Collaborative (TTC) is excited to share the official Getting Started with Generative Artificial Intelligence: U-M Instructor Guide with campus. The guide is differentiated, portable, and easy-to-use. It reflects the variety of new GenAI resources available, ranging from custom U-M AI tools, GenAI workshops, and a new U-M GenAI website.

Building the world’s first accessible AI chat interface

On August 21, 2023, the University of Michigan launched what we believe to be the first accessible web chat interface to send prompts to GPT-4 and other large language models — U-M GPT. This application is designed for accessibility according to international standards, optimized for usability with common assistive technology, and built without the barriers found in some… Read More »

Deep learning algorithm detects Acute Respiratory Distress Syndrome with expert-level accuracy

A team from Michigan Medicine and the Michigan Center for Integrative Research in Critical Care (MCIRCC) is using a new artificial intelligence algorithm to analyze chest x-rays for Acute Respiratory Distress Syndrome (ARDS), a life-threatening lung injury that progresses rapidly and can often lead to long-term health problems or death. “In our previous work, we found that physicians have difficulty… Read More »

AI – transformative and biased, say U-M panelists

A panel of U-M experts discussed the film “Coded Bias” at a Dissonance Event on April 15. “Coded Bias” follows the journey of Joy Buolamwini, a computer scientist and digital activist based at the MIT Media Lab, as she worked with others to push for the first legislation in the U.S. to govern against bias in artificial intelligence (AI) algorithms. The Dissonance organizing committee brought the panelists together for an online discussion of bias in AI, transformative opportunities for its use, and more.

“Coded Bias” watch event; Join experts for panel discussion afterwards

You are invited to a free, on-demand screening of the documentary film Coded Bias—available anytime from April 8 to 14 and a panel discussion of the film April 15. Coded Bias explores the fallout from an MIT Media Lab researcher’s discovery that facial recognition does not identify dark-skinned faces and women’s faces accurately. The film follows her journey to push for the first legislation in the U.S. to govern against bias in the algorithms.