Quantum defects have the potential to act as ultra-sensitive sensors that could offer new kinds of navigation or biological sensor technology.
Category: biological – Page 27
Next Generation Biomanufacturing Technologies — Dr. Leonard Tender, Ph.D. — Biological Technologies Office, Defense Advanced Research Projects Agency — DARPA
Dr. Leonard Tender, Ph.D. is a Program Manager in the Biological Technologies Office at DARPA (https://www.darpa.mil/staff/dr-leonar…) where his research interests include developing new methods for user-defined control of biological processes, and climate and supply chain resilience.
Prior to coming to DARPA, Dr. Tender was a principal investigator and led the Laboratory for Molecular Interfaces in the Center for Bio/Molecular Science and Engineering at the U.S. Naval Research Laboratory. There, among other accomplishments, he facilitated numerous international collaborations with key external stakeholders in academia, industry, and government and his highly interdisciplinary research team, comprised of electrochemists, microbiologists, and engineers, is widely recognized for its many contributions to the field of microbial electrochemistry.
Dr. Tender earned a doctorate degree in analytical chemistry from the University of North Carolina, Chapel Hill; a bachelor’s degree in chemistry from the Massachusetts Institute of Technology; completed a post-doctoral fellowship in the Department of Chemistry from the University of California, Berkeley; and served as a visiting scientist in the Stanford University Department of Chemistry.
Dr. Tender co-founded the International Society for Microbial Electrochemistry and Technology and is a recipient of the Arthur S. Flemming Award, which honors outstanding federal employees, by the George Washington University’s Trachtenberg School of Public Policy and Public Administration.
Biological components are less reliable than electrical ones, and rather than instantaneously receive the incoming signals, the signals arrive with a variety of delays. This forces the brain to cope with said delays by having each neuron integrate the incoming signals over time and fire afterwards, as well as using a population of neurons, instead of one, to overcome neuronal cells that temporarily don’t fire.
Life expectancy growth has slowed since 1990, with average gains of only 6.5 years in the longest-living populations, suggesting a possible biological limit. A new study emphasizes shifting focus from merely extending life to improving the quality of life through advancements in aging science. Life expectancy saw dramatic increases throughout…
This video explores what life would be like if we became a Type 3 Civilization. Watch this next video about us becoming a Type 2 civilization: • What If We Became A Type 2 Civilizati…
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Researchers at the Department of Energy’s Oak Ridge National Laboratory, the University of Tennessee, and Texas A&M University demonstrated bio-inspired devices that accelerate routes to neuromorphic, or brain-like, computing.
Results published in Nature Communications report the first example of a lipid-based “memcapacitor,” a charge storage component with memory that processes information much like synapses do in the brain. Their discovery could support the emergence of computing networks modeled on biology for a sensory approach to machine learning.
“Our goal is to develop materials and computing elements that work like biological synapses and neurons—with vast interconnectivity and flexibility—to enable autonomous systems that operate differently than current computing devices and offer new functionality and learning capabilities,” said Joseph Najem, a recent postdoctoral researcher at ORNL’s Center for Nanophase Materials Sciences, a DOE Office of Science User Facility, and current assistant professor of mechanical engineering at Penn State.
Neural networks have a remarkable ability to learn specific tasks, such as identifying handwritten digits. However, these models often experience “catastrophic forgetting” when taught additional tasks: They can successfully learn the new assignments, but “forget” how to complete the original. For many artificial neural networks, like those that guide self-driving cars, learning additional tasks thus requires being fully reprogrammed.
Biological brains, on the other hand, are remarkably flexible. Humans and animals can easily learn how to play a new game, for instance, without having to re-learn how to walk and talk.
Inspired by the flexibility of human and animal brains, Caltech researchers have now developed a new type of algorithm that enables neural networks to be continuously updated with new data that they are able to learn from without having to start from scratch. The algorithm, called a functionally invariant path (FIP) algorithm, has wide-ranging applications from improving recommendations on online stores to fine-tuning self-driving cars.
Neural networks have a remarkable ability to learn specific tasks, such as identifying handwritten digits. However, these models often experience “catastrophic forgetting” when taught additional tasks: They can successfully learn the new assignments, but “forget” how to complete the original. For many artificial neural networks, like those that guide self-driving cars, learning additional tasks thus requires being fully reprogrammed.
Biological brains, on the other hand, are remarkably flexible. Humans and animals can easily learn how to play a new game, for instance, without having to re-learn how to walk and talk.
Inspired by the flexibility of human and animal brains, Caltech researchers have now developed a new type of algorithm that enables neural networks to be continuously updated with new data that they are able to learn from without having to start from scratch. The algorithm, called a functionally invariant path (FIP) algorithm, has wide-ranging applications from improving recommendations on online stores to fine-tuning self-driving cars.
Scientists have invented an artificial plant that can simultaneously clean indoor air while generating enough electricity to power a smartphone.
A team from Binghamton University in New York created an artificial leaf “for fun” using five biological solar cells and their photosynthetic bacteria, before realising that the device could be used for practical applications.
A proof-of-concept plant with five artificial leaves was capable of generating electricity and oxygen, while removing CO2 at a far more efficient rate than natural plants.
The US government has launched a new supercomputer in Livermore, California.
The Department of Defense (DoD) and National Nuclear Security Administration (NNSA) this month inaugurated a new supercomputing system dedicated to biological defense at the Lawrence Livermore National Laboratory (LLNL).
Specs not shared, but same architecture as upcoming El Capitan system.