SUSTech.
Researchers succeeded in a 3D printing strategy to construct flexible and stretchable light-emitting devices that can be integrated with soft robots.
It’s official: Apple has just sent out invites for its next hardware event. As expected, the company will share what it’s been working on for the past year on September 7th, with a live broadcast from Apple Park starting at 1PM ET. The invite features the words “Far out.” Make of that what you will.
The company is widely expected to announce four new iPhone models at the event. Leading up to today’s announcement, most reports have suggested the 2022 iPhone lineup will consist of a 6.1-inch iPhone 14, a 6.7-inch iPhone 14 Max, a 6.1-inch iPhone 14 Pro and a 6.7-inch iPhone 14 Pro Max. Apple reportedly won’t offer a new “mini” model this year due to lackluster sales of the iPhone 12 mini and iPhone 13 mini.
Enhancements on the standard iPhone 14 models reportedly include the addition of more RAM, longer-lasting batteries and a better selfie camera with autofocus. Meanwhile, the Pro models are expected to feature a new design that trades away Apple’s signature display notch for a Samsung-style hole-punch front camera cutout. Additionally, the Pro variants will reportedly feature a new 48-megapixel main camera and thinner display bezels. They’re also expected to be the only models to ship with Apple’s next-generation A16 chip.
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With the release of Nerdist Presents: The Hive, we have to wonder are there any NON-evil Hive minds in real life?? Kyle explores real life collective intelligence on this week’s Because Science!
Continue reading “The Hive Mind in the Real World (Because Science w/ Kyle Hill)” »
TABLE OF CONTENTS —————
0:00–15:11 : Introduction.
15:11–36:12 CHAPTER 1: POSTHUMANISM
a. Neurotechnology b. Neurophilosophy c. Teilhard de Chardin and the Noosphere.
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Cloning people is a staple of science fiction, and now something science can do, but what are the future social and legal consequences of cloning, and can we learn to make fully grown clones or even duplicate our memories?
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Continue reading “Cloning & Duplication: Me, Myself, and I” »
All around smart guy Dr Goerge Church talking about genetic engineering technologies.
George Church, Ph.D. is a professor of genetics at Harvard Medical School and of health sciences and technology at both Harvard and the Massachusetts Institute of Technology. Dr. Church played an instrumental role in the Human Genome Project and is widely recognized as one of the premier scientists in the fields of gene editing technology and synthetic biology.
Continue reading “George Church, PhD: Rewriting Genomes to Eradicate Disease and Aging” »
Electronically accessible states in vanadium dioxide can be arbitrarily manipulated on short timescales and tracked beyond 10,000 s after excitation.
The technology is based on integrated circuits, which typically rely on silicon semiconductors in order to process information in a way that is similar to the role played by the brain in the human body.
The research team discovered that integrated circuits capable of performing computational tasks could be achieved using “nearly any material” around us.
“We have created the first example of an engineering material that can simultaneously sense, think and act upon mechanical stress, without requiring additional circuits to process such signals,” said Ryan Harne, an associate professor of mechanical engineering at Penn State.
Our approach to aligning AGI is empirical and iterative. We are improving our AI systems’ ability to learn from human feedback and to assist humans at evaluating AI. Our goal is to build a sufficiently aligned AI system that can help us solve all other alignment problems.
Our alignment research aims to make artificial general intelligence (AGI) aligned with human values and follow human intent. We take an iterative, empirical approach: by attempting to align highly capable AI systems, we can learn what works and what doesn’t, thus refining our ability to make AI systems safer and more aligned. Using scientific experiments, we study how alignment techniques scale and where they will break.
We tackle alignment problems both in our most capable AI systems as well as alignment problems that we expect to encounter on our path to AGI. Our main goal is to push current alignment ideas as far as possible, and to understand and document precisely how they can succeed or why they will fail. We believe that even without fundamentally new alignment ideas, we can likely build sufficiently aligned AI systems to substantially advance alignment research itself.
