Lifeboat Foundation

Comparing his experience to Jodie Foster’s character in the movie Contact, Shatner added, “I discovered that the beauty isn’t out there, it’s down here, with all of us. Leaving that behind made my connection to our tiny planet even more profound.”

In the excerpt, Shatner wrote that he later learned he “was not alone in this feeling,” which is called the “Overview Effect” and is “not uncommon among astronauts.”

Continue reading “William Shatner Reveals Mixed Emotions from Record Breaking Space Trip” »

Scientists have long looked to the brain as an inspiration for designing computing systems. Some researchers have recently gone even further by making computer hardware with a brain-like structure. These “neuromorphic chips” have already shown great promise, but they have used conventional digital electronics, limiting their complexity and speed. As the chips become larger and more complex, the signals between their individual components become backed up like cars on a gridlocked highway and reduce computation to a crawl.

Now, a team at the National Institute of Standards and Technology (NIST) has demonstrated a solution to these communication challenges that may someday allow artificial neural systems to operate 100,000 times faster than the human brain.

The human brain is a network of about 86 billion cells called neurons, each of which can have thousands of connections (known as synapses) with its neighbors. The neurons communicate with each other using short electrical pulses called spikes to create rich, time-varying activity patterns that form the basis of cognition. In neuromorphic chips, electronic components act as artificial neurons, routing spiking signals through a brain-like network.

Researchers have reported a nano-sized neuromorphic memory device that emulates neurons and synapses simultaneously in a unit cell, another step toward completing the goal of neuromorphic computing designed to rigorously mimic the human brain with semiconductor devices.

Neuromorphic computing aims to realize artificial intelligence (AI) by mimicking the mechanisms of neurons and synapses that make up the human brain. Inspired by the cognitive functions of the human brain that current computers cannot provide, neuromorphic devices have been widely investigated. However, current Complementary Metal-Oxide Semiconductor (CMOS)-based neuromorphic circuits simply connect artificial neurons and synapses without synergistic interactions, and the concomitant implementation of neurons and synapses still remains a challenge. To address these issues, a research team led by Professor Keon Jae Lee from the Department of Materials Science and Engineering implemented the biological working mechanisms of humans by introducing the neuron-synapse interactions in a single memory cell, rather than the conventional approach of electrically connecting artificial neuronal and synaptic devices.

Similar to commercial graphics cards, the artificial synaptic devices previously studied often used to accelerate parallel computations, which shows clear differences from the operational mechanisms of the human brain. The research team implemented the synergistic interactions between neurons and synapses in the neuromorphic memory device, emulating the mechanisms of the biological neural network. In addition, the developed neuromorphic device can replace complex CMOS neuron circuits with a single device, providing high scalability and cost efficiency.

A scientist resurfaces a psychedelic retelling of human evolution.

Learn how your company can create applications to automate tasks and generate further efficiencies through low-code/no-code tools on November 9 at the virtual Low-Code/No-Code Summit. Register here.

With the increasing digitization of services across multiple industries, large corporations are pushing for new security measures to keep their customers’ documents and sensitive information secure. Among these measures are passwordless logins, with new authentication methods adding an extra layer of data protection.

The transition to passwordless logins is undeniable, with approximately 60% of large and global enterprises and 90% of midsize enterprises predicted to adopt passwordless methods in at least 50% of use cases, according to a recent Gartner study. This comes as no surprise, as security problems associated with password-only authentication are among the digital world’s biggest vulnerabilities. Consumers are often tempted to reuse passwords across different services due to the difficulty of managing so many passwords.

A Canadian startup called TransPod wants to revolutionize ground-based transportation by sending magnetically levitated trains through vacuum-sealed tubes at ludicrous speeds.

It’s a highly ambitious — and immensely expensive, nevermind comically vague — concept that’s generated some serious buzz in recent weeks.

Continue reading “Startup Says Train Powered by ‘Veillance Flux’ Could Travel 620 MPH” »

These days when we are struggling with the pandemic, even breathing with peace of mind has become challenging. Especially the form of the mammalian respiratory system, requiring inhalation and exhalation, leaves us more vulnerable to the propagation of viral diseases.

But now, a group of South Korean artists, Bongkyu Song of BKID and Moon&Jeon, has devised a metal lung concept that uses algae to convert carbon dioxide into oxygen. This device named Super Lung is inspired by the respiratory system of birds. Moreover, its designers assert that this concept increases mammalian respiratory efficiency by 300%. But how?

“The Ce electrolyte is highly oxidative, which poses a challenge towards the stability of anion membrane,” Daoud said. “Thus, the stability and selectivity of anion membrane require further improvement.”

The device achieved a voltage plateau of 2.3 V at 20 mA cm − 2, energy efficiency of 71.3% at 60 mA cm − 2, and a record average Coulombic efficiency of 94% during cycling.

A new AI system can create natural-sounding speech and music after being prompted with a few seconds of audio.

AudioLM, developed by Google researchers, generates audio that fits the style of the prompt, including complex sounds like piano music, or people speaking, in a way that is almost indistinguishable from the original recording. The technique shows promise for speeding up the process of training AI to generate audio, and it could eventually be used to auto-generate music to accompany videos.