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UNIVERSITY PARK, Pa.— A person’s distrust in humans predicts they will have more trust in artificial intelligence’s ability to moderate content online, according to a recently published study. The findings, the researchers say, have practical implications for both designers and users of AI tools in social media.

“We found a systematic pattern of individuals who have less trust in other humans showing greater trust in AI’s classification,” said S. Shyam Sundar, the James P. Jimirro Professor of Media Effects at Penn State. “Based on our analysis, this seems to be due to the users invoking the idea that machines are accurate, objective and free from ideological bias.”

The study, published in the journal of New Media & Society also found that “power users” who are experienced users of information technology, had the opposite tendency. They trusted the AI moderators less because they believe that machines lack the ability to detect nuances of human language.

Watch NVIDIA CEO Jensen Huang unveil the new Ada Lovelace GPU architecture, new advances to its computing platforms, and new cloud services to further the era of AI and the metaverse, and transform every industry.

Dive into the announcements and discover more content at https://www.nvidia.com/gtc.

00:00 GeForce Beyond: A Special Broadcast at GTC
19:34 NVIDIA Omniverse.
37:07 NVIDIA Robotics Platforms: Isaac, DRIVE, Clara Holoscan, Metropolis.
57:22 NVIDIA AI
1:08:48 Large Language Models.
1:15:39 Hopper and Grace Hopper.
1:21:47 AI & Omniverse Services to Enterprise.
1:30:25 Closing Summary.

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Inflated expectations around the capabilities of AI technologies may lead people to believe that computers can’t be wrong. The truth is AI failures are not a matter of if but when. AI is a human endeavor that combines information about people and the physical world into mathematical constructs. Such technologies typically rely on statistical methods, with the possibility for errors throughout an AI system’s lifespan. As AI systems become more widely used across domains, especially in high-stakes scenarios where people’s safety and wellbeing can be affected, a critical question must be addressed: how trustworthy are AI systems, and how much and when should people trust AI?

For the memory prosthetic, the team focused on two specific regions: CA1 and CA3, which form a highly interconnected neural circuit. Decades of work in rodents, primates, and humans have pointed to this neural highway as the crux for encoding memories.

The team members, led by Drs. Dong Song from the University of Southern California and Robert Hampson at Wake Forest School of Medicine, are no strangers to memory prosthetics. With “memory bioengineer” Dr. Theodore Berger—who’s worked on hijacking the CA3-CA1 circuit for memory improvement for over three decades—the dream team had their first success in humans in 2015.

The central idea is simple: replicate the hippocampus’ signals with a digital replace ment. It’s no easy task. Unlike computer circuits, neural circuits are non-linear. This means that signals are often extremely noisy and overlap in time, which bolsters—or inhibits—neural signals. As Berger said at the time: “It’s a chaotic black box.”

Sailing on light pressure to Near Earth Asteroid (NEA) 2020 GE NEA Scout will be the first mission to use solar light as propulsion to reach a destination in space. It will be launched to the moon by NASA’s Artemis I Space Launch System rocket and sail from there to the asteroid. Learn about this exciting mission directly from Dr. Les Johnson, the Principal Investigator of the light sail.

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Certain physical problems such as the rupture of a thin sheet can be difficult to solve as computations breakdown at the point of rupture. Here the authors propose a regularization approach to overcome this breakdown which could help dealing with mathematical models that have finite time singularities.

Corporate Venturing For Integrated Digital Healthcare Solutions — Bill Taranto, President, Global Health Innovation Fund, Merck


Bill Taranto is President of the Global Health Innovation Fund at Merck (https://www.merckghifund.com/taranto.html) and founding partner since inception in 2010.

Merck Global Health Innovation Fund (Merck GHI) is a corporate venture capital group utilizing a healthcare ecosystem strategy, investing globally in platform companies with proven technologies or business models where Merck’s expertise can accelerate revenue growth and enhance value creation to ultimately develop integrated healthcare solutions.