3D4Medical: Project Esper — from vimeo.com by 3D4Medical
3D4Medical: Project Esper from 3D4Medical on Vimeo.
3D4Medical: Project Esper — from vimeo.com by 3D4Medical
3D4Medical: Project Esper from 3D4Medical on Vimeo.
Interesting: Mount Sinai Launches Q-Lab for Deep Brain Stimulation Patients https://t.co/JmF7t53GKS
— Daniel Christian (he/him/his) (@dchristian5) August 17, 2021
“In person” classes offered in virtual reality — from zdnet.com by Greg Nichols; with thanks to Will Richardson for the resource
A virtual reality college campus welcomes students this fall.
Excerpt:
“With this cadaver lab, our pre-med students will no longer need to rely on other universities for advanced anatomy and biology classes,” said Dr. Shirley Brown, Dean of Fisk University. “Virtual reality technology takes our university to a level equal to the most advanced schools in the country.”
How Morehouse School of Medicine is growing the biotech worker pipeline — from highereddive.com by Chandra Thomas Whitfield
The historically Black institution created summer bridge programs to attract students to a sector in which diversity has long lagged.
College students and recent graduates considering a future in the biotechnology sector have a new way to try it out, thanks to a tuition-free summer program at the Morehouse School of Medicine.
From DSC:
Again, as you can see from the items below…there are various plusses and minuses regarding the use of Artificial Intelligence (AI). Some of the items below are neither positive or negative, but I found them interesting nonetheless.
How Amazon is tackling the A.I. talent crunch — from fortune.com by Jonathan Vanian
Excerpt:
“One way Amazon has adapted to the tight labor market is to require potential new programming hires to take classes in machine learning, said Bratin Saha, a vice president and general manager of machine learning services at Amazon. The company’s executives believe they can teach these developers machine learning basics over a few weeks so that they can work on more cutting-edge projects after they’re hired.”
…
“These are not formal college courses, and Saha said the recruits aren’t graded like they would be in school. Instead, the courses are intended to give new developers a foundation in machine learning and statistics so they can understand the theoretical underpinnings.”
Machine Learning Can Predict Rapid Kidney Function Decline — from sicklecellanemianews.com by Steve Bryson PhD; with thanks to Sam DeBrule for this resource
Excerpt:
Machine learning tools can identify sickle cell disease (SCD) patients at high risk of progressive kidney disease as early as six months in advance, a study shows. The study, “Using machine learning to predict rapid decline of kidney function in sickle cell anemia,” was published in the journal eJHaem.
NYPD’s Sprawling Facial Recognition System Now Has More Than 15,000 Cameras — from vice.com by Todd Feathers; with thanks to Sam DeBrule for this resource
The massive camera network is concentrated in predominantly Black and brown neighborhoods, according to a new crowdsourced report.
Excerpt:
The New York City Police Department has built a sprawling facial recognition network that may include more than 15,000 surveillance cameras in Manhattan, Brooklyn, and the Bronx, according to a massive crowdsourced investigation by Amnesty International.
…
“This sprawling network of cameras can be used by police for invasive facial recognition and risk turning New York into an Orwellian surveillance city,” Matt Mahmoudi, an artificial intelligence and human rights researcher at Amnesty, wrote in the group’s report. “You are never anonymous. Whether you’re attending a protest, walking to a particular neighbourhood, or even just grocery shopping—your face can be tracked by facial recognition technology using imagery from thousands of camera points across New York.”
Related to that article is this one:
The All-Seeing Eyes of New York’s 15,000 Surveillance Cameras — from wired.com by Sidney Fussell
Video from the cameras is often used in facial-recognition searches. A report finds they are most common in neighborhoods with large nonwhite populations.
Excerpt:
A NEW VIDEO from human rights organization Amnesty International maps the locations of more than 15,000 cameras used by the New York Police Department, both for routine surveillance and in facial-recognition searches. A 3D model shows the 200-meter range of a camera, part of a sweeping dragnet capturing the unwitting movements of nearly half of the city’s residents, putting them at risk for misidentification. The group says it is the first to map the locations of that many cameras in the city.
Don’t End Up on This Artificial Intelligence Hall of Shame — from wired.com by Tom Simonite
A list of incidents that caused, or nearly caused, harm aims to prompt developers to think more carefully about the tech they create.
Excerpt:
The AI Incident Database is hosted by Partnership on AI, a nonprofit founded by large tech companies to research the downsides of the technology. The roll of dishonor was started by Sean McGregor, who works as a machine learning engineer at voice processor startup Syntiant. He says it’s needed because AI allows machines to intervene more directly in people’s lives, but the culture of software engineering does not encourage safety.
The Future Of AI In Healthcare — from forbes.com by Gil Press
Excerpt:
Two AI luminaries, Fei-Fei Li and Andrew Ng got together today on YouTube, to discuss the state of AI in healthcare. Covid-19 has made healthcare a top priority for governments, businesses, and investors around the world and accelerated efforts to apply artificial intelligence to improve our health, from drug discovery to more efficient hospital operations to better diagnostics.
Also see:
Will This AI Launch The Next Stage Of In-Vitro Fertilization (IVF)? — from forbes.com by Gil Press
Excerpt:
AiVF announced today that it has received European approval of its AI-based digital embryology management platform, for the use in IVF fertility clinics. The Tel-Aviv, Israel-based startup combines AI, computer vision, and big data to reduce the cost and improve the success rates of fertility treatments.
Academia needs a reality check: Life is not back to normal — from sciencemag.org by June Gruber, Jay J. Van Bavel , William A. Cunningham, Leah H. Somerville, Neil A. Lewis, Jr.; with special thanks to Dr. Kate Byerwalter for this resource
Excerpts:
The problems don’t end there. Many academics are also grappling with ongoing racial injustices and associated protests, wildfires, and hurricanes. We continue to see widespread effects on mental health, with roughly one-third of Americans reporting symptoms of clinical depression or anxiety. June and her colleague recently described the escalating mental health crisis as the next biggest coronavirus challenge.
We have struggled with our own mental and physical well-being—as well as challenges associated with canceled vacations, lack of child care, the illnesses and death of people close to us, and the mental weight of difficult conversations about racial injustices. We’ve also been worrying about our trainees and the undergraduate students in our classes. The academic and non-academic job markets have cratered, and some of our colleagues and students have lost internships and job offers as organizations have been forced to cut expenses.
Expecting the same output as in previous years, even though many people have less time and more stress than ever, is not a sustainable or humane solution. The world is not normal—so the way we do science cannot be normal either.
DC: Will be interesting to see if the level of innovation/investment takes a leap forward during this time…https://t.co/jw1ibbQkwg#highereducation #innovation #edtech #AR #XR #science #chemistry #biology #physics
— Daniel Christian (@dchristian5) September 9, 2020
Also see: