The blind may be able to see with help from this chip.
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Category: computing – Page 772
Drawing inspiration from the plant world, researchers have invented a new electrode that could boost our current solar energy storage by an astonishing 3,000 percent.
The technology is flexible and can be attached directly to solar cells — which means we could finally be one step closer to smartphones and laptops that draw their power from the Sun, and never run out.
A major problem with reliably using solar energy as a power source is finding an efficient way to store it for later use without leakage over time.
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Unimaginable Radical Abundance:
Yesterday I took the time to read chapter 11 of Eric Drexler’s book Radical Abundance as to get a glimpse of what might be possible with Atomically Precise Manufacturing (APM). I highly recommend the book.
The potential of APM is truly unimaginable.
Try to imagine billion core processors, memory storage in the billions of gigabytes per cm2. Solar panels far exceeding todays best laboratory efficiencies. Batteries that are a billion times more energy dense. All this with a negligible impact on the environment.
APM can produce these products and many more at costs of roughly 20¢ per kilogram!
Just let that sink in. Just to illustrate this $1 would buy you more memory storage than is currently available throughout the entire world (roughly 10 Zettabytes).
“A future without animal testing is getting closer. On Tuesday, the Food and Drug Administration agreed to a research-and-development collaboration with Emulate, a company that makes “organs-on-chips” technology.
The hope is that instead of testing new drugs or supplements on animals, researchers can use Emulate’s chips.
To start, the collaboration between the FDA and Emulate will focus on the company’s Liver-Chips, which are meant to show how an animal’s liver may react to a certain drug.
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The race to build larger and larger quantum computers is heating up, with several technologies competing for a role in future devices. Each potential platform has strengths and weaknesses, but little has been done to directly compare the performance of early prototypes. Now, researchers at the JQI have performed a first-of-its-kind benchmark test of two small quantum computers built from different technologies.
The team, working with JQI Fellow Christopher Monroe and led by postdoctoral researcher Norbert Linke, sized up their own small-scale quantum computer against a device built by IBM. Both machines use five qubits—the fundamental units of information in a quantum computer—and both machines have similar error rates. But while the JQI device relies on chains of trapped atomic ions, IBM Q uses coupled regions of superconducting material.
To make their comparison, the JQI team ran several quantum programs on the devices, each of which solved a simple problem using a series of logic gates to manipulate one or two qubits at a time. Researchers accessed the IBM device using an online interface, which allows anyone to try their hand at programming IBM Q.
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Material scientists have predicted and built two new magnetic materials, atom-by-atom, using high-throughput computational models. The success marks a new era for the large-scale design of new magnetic materials at unprecedented speed.
Although magnets abound in everyday life, they are actually rarities—only about five percent of known inorganic compounds show even a hint of magnetism. And of those, just a few dozen are useful in real-world applications because of variability in properties such as effective temperature range and magnetic permanence.
The relative scarcity of these materials can make them expensive or difficult to obtain, leading many to search for new options given how important magnets are in applications ranging from motors to magnetic resonance imaging (MRI) machines. The traditional process involves little more than trial and error, as researchers produce different molecular structures in hopes of finding one with magnetic properties. Many high-performance magnets, however, are singular oddities among physical and chemical trends that defy intuition.
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I’ve been reading about Gcam, the Google X project that was first sparked by the need for a tiny camera to fit inside Google Glass, before evolving to power the world-beating camera of the Google Pixel. Gcam embodies an atypical approach to photography in seeking to find software solutions for what have traditionally been hardware problems. Well, others have tried, but those have always seemed like inchoate gimmicks, so I guess the unprecedented thing about Gcam is that it actually works. But the most exciting thing is what it portends.
I think we’ll one day be able to capture images without any photographic equipment at all.
Now I know this sounds preposterous, but I don’t think it’s any more so than the internet or human flight might have once seemed. Let’s consider what happens when we tap the shutter button on our cameraphones: light information is collected and focused by a lens onto a digital sensor, which converts the photons it receives into data that the phone can understand, and the phone then converts that into an image on its display. So we’re really just feeding information into a computer.
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“These re-engineered organisms will change our lives over the coming years, leading to cheaper drugs, ‘green’ means to fuel our cars and targeted therapies for attacking ‘superbugs’ and diseases, such as cancer,” wrote Drs. Ahmad Khalil and James Collins at Boston University, who were not involved in the study.
Our brains are often compared to computers, but in truth, the billions of cells in our bodies may be a better analogy. The squishy sacks of goop may seem a far cry from rigid chips and bundled wires, but cells are experts at taking inputs, running them through a complicated series of logic gates and producing the desired programmed output.
Take beta cells in the pancreas, which manufacture and store insulin. If they detect a large spike in blood sugar, then they release insulin; else they don’t. Each cell adheres to commands like these, allowing us—the organism—to operate normally.
This circuit-like nature of cellular operations is not just a handy metaphor. About 50 years ago, scientists began wondering: what if we could hijack the machinery behind these algorithms and reprogram the cells to do whatever we want?
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Interesting link within concerning an injectable interface.
To be able to design a device that measures brain activity an understanding of the brains function is required. This section gives a high-level overview of some of the key elements of brain function. Human brains contain approximately 80 billion neurons, these neurons are interconnected with 7,000 synaptic connections each (on average). The combination of neurons firing and their communication is, in very simple terms the basis of all thoughts conscious and subconscious. Logically if the activity of these neurons and their connections were read in real-time, a sufficiently intelligent algorithm could understand all thoughts present. Similarly, if an input could be given at this level of granularity new thoughts could be implanted.
All human brains abide by the general structure shown in the picture below, certain areas, by and large do certain things. If higher levels of thoughts like creativity, idea generation and concentration want to be read, the frontal lobe is the place to look. If emotions and short-term memory are the target, the temporal lobe is the place to read from.
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