November 14, 2015

Telsa Motors could get to millions of cars per year by 2025

Tesla CEO Elon Musk announced his intentions to produce millions of cars by 2025. Production on that scale would make Tesla about the size BMW.

More assembly plants will be needed once Tesla reaches 500,000 sales a year. The automaker currently produces vehicles at its Fremont, Calif. plant, and plans to add another plant in China. A Gigafactory facility in Nevada will produce battery packs for Tesla and other automakers, reducing the cost of the now expensive components by at least 30 percent

Elon Musk has talked about maintaining a 30% growth rate for ten years to reach a market capitalization of $700 billion.

If you take this year’s revenue around $6 billion or thereabouts, and if we are able to maintain a 30% growth rate for 10 years added to your 10% profitability number and have a 20PE, our market cap would be basically the same as Apple’s is today. Now that’s going to require a bit — on the order of $700 billion. Obviously, getting there will require some significant CapEx.

But I’m hopeful that we can do this without any significant dilution to the company — maybe minor dilution, but nothing serious.

Elon Musk owns about 24% of Telsa Motors. This is about $7 billion of the current 28 billion valuation. If he had 20% of a $700 billion Telsa, then it would be $140 billion.

A Quantitative Criterion for Defining Planets

Since the late 1980s, scientists have discovered nearly 5,000 planetary bodies orbiting stars other than the sun. But astronomers are still working on what exactly we should call them.

Today at an American Astronomical Society meeting, UCLA professor Jean-Luc Margot described a simple test that can be used to clearly separate planets from other bodies like dwarf planets and minor planets.

The current official definition of a planet, which was issued by the International Astronomical Union in 2006, applies only to bodies in our solar system, which Margot said has created a “definitional limbo” for the newly discovered bodies.

The new approach would require only estimates of the star’s mass and the planet’s mass and orbital period — all of which can be easily obtained with Earth- or space-based telescopes. According to Margot’s criteria, all eight planets in our solar system and all classifiable exoplanets — the large bodies that orbit stars other than our sun — would be confirmed as planets.

Margot, a professor of planetary astronomy, wanted to ensure that the new system would be easy to follow. “One should not need a teleportation device to decide whether a newly discovered object is a planet.”

Arxiv - A Quantitative Criterion for Defining Planets

Gene drive can propel genes throughout populations combined with CRISPR genetic engineering can eliminate Lyme disease and Malaria

For the foreseeable future, CRISPR’s greatest impact will lie in its ability to help scientists rapidly rewrite the genomes of animal and plant species. In laboratories, agricultural companies have already begun to use CRISPR to edit soybeans, rice, and potatoes in an effort to make them more nutritious and more resistant to drought. Scientists might even be able to edit allergens out of foods like peanuts

Normally, it takes years for genetic changes to spread through a population. That is because, during sexual reproduction, each of the two versions of any gene has only a fifty per cent chance of being inherited. But a gene drive which is named for its ability to propel genes through populations over many generations manages to override the traditional rules of genetics. A mutation made by CRISPR on one chromosome can copy itself in every generation, so that nearly all descendants would inherit the change. A mutation engineered into a mosquito that would block the parasite responsible for malaria, for instance, could be driven through a large population of mosquitoes within a year or two. If the mutation reduced the number of eggs produced by that mosquito, the population could be wiped out, along with any malaria parasites it carried.

Kevin Esvelt, an evolutionary biologist at Harvard, was the first to demonstrate how gene drives and CRISPR could combine to alter the traits of wild populations. Recently, he has begun to study the possibility of using the technology to eliminate Lyme disease by rewriting the genes of mice in the wild. Lyme disease is caused by a bacterium and transmitted by ticks, and more than eighty-five per cent of the time they become infected after biting a mouse. Once exposed, however, some mice naturally acquire resistance or immunity.

"My idea is to take the existing genes that confer resistance to Lyme and make sure that all mice have the most effective version", Esvelt said. To do that, scientists could encode the most protective genes next to the CRISPR system and force them to be passed on together. Esvelt stressed that such an approach would become possible only after much more research and a lengthy series of public discussions on the risks and benefits of the process.

Last year, by deleting all three copies of a single wheat gene, a team led by the Chinese geneticist Gao Caixia created a strain that is fully resistant to powdery mildew, one of the world's most pervasive blights. In September, Japanese scientists used the technique to prolong the life of tomatoes by turning off genes that control how quickly they ripen. Agricultural researchers hope that such an approach to enhancing crops will prove far less controversial than using genetically modified organisms, a process that requires technicians to introduce foreign DNA into the genes of many of the foods we eat.

The technology has also made it possible to study complicated illnesses in an entirely new way. A few well-known disorders, such as Huntington's disease and sickle-cell anemia, are caused by defects in a single gene. But most devastating illnesses, among them diabetes, autism, Alzheimer's, and cancer, are almost always the result of a constantly shifting dynamic that can include hundreds of genes. The best way to understand those connections has been to test them in animal models, a process of trial and error that can take years. CRISPR promises to make that process easier, more accurate, and exponentially faster.

USC and Sangamo researchers advance genome editing of blood stem cells

In an upcoming study in Nature Biotechnology, co-first authors Colin M. Exline, PhD, from USC and Jianbin Wang, PhD, from Sangamo BioSciences describe a new, more efficient way to edit genes in blood-forming or "hematopoietic" stem and progenitor cells (HSPCs).

"Gene therapy using HSPCs has enormous potential for treating HIV and other diseases of the blood and immune systems," said co-corresponding author Paula Cannon, PhD, professor of molecular microbiology and immunology, pediatrics, biochemistry and molecular biology, and stem cell biology and regenerative medicine at USC. "And using genome editing techniques now allows us to make very precise changes that could repair genetic mutations -- the gene typos -- that can cause disease."

Despite the enormous potential of such targeted gene medicine to cure patients, getting genome editing to work has proven challenging in human HSPCs -- especially in the most primitive, least differentiated cells with the greatest ability to become any blood cell type

CAPTION - HIV (yellow) infecting a human immune cell.
CREDIT Seth Pincus, Elizabeth Fischer and Austin Athman, National Institute of Allergy and Infectious Diseases, National Institutes of Health

Manipulating domain walls in magnetic nanowire with sound could enable high density racetrack memory

A team from the Universities of Sheffield and Leeds may have found the answer to faster computing: sound. The research – published in Applied Physics Letters – has shown that certain types of sound waves can move data quickly, using minimal power.

The world’s 2.7 zettabytes (2.7 followed by 21 zeros) of data are mostly held on hard disk drives: magnetic disks that work like miniaturised record players, with the data read by sensors that scan over the disk’s surface as it spins. But because this involves moving parts, there are limits on how fast it can operate.

For computers to run faster, we need to create “solid-state” drives that eliminate the need for moving parts – essentially making the data move, not the device on which it’s stored. Flash-based solid-state disk drives have achieved this, and store information electrically rather than magnetically. However, while they operate much faster than normal hard disks, they last much less time before becoming unreliable, are much more expensive and still run much slower than other parts of a modern computer – limiting total speed.

Applied Physics Letters - A sound idea: Manipulating domain walls in magnetic nanowires using surface acoustic waves

November 13, 2015

Google planning a ‘watershed’ quantum computing announcement for December 8

According to Steve Jurvetson, venture capitalist and board member at pioneer quantum computing company D-WAVE, Google has what may be a “watershed” quantum computing announcement scheduled for early next month. This comes as D-WAVE, which notably also holds the Mountain View company as a customer, has just sold a 1000+ Qubit 2X quantum computer to national security research institution Los Alamos.

Jurvetson says to “stay tuned” for more information coming on December 8th. This is the first we’ve heard of a December 8th date for a Google announcement, and considering its purported potential to be a turning point in computing, this could perhaps mean an actual event is in the cards.

On Flickr, Steve Jurvetson mentioned that Los Alamos just purchased a D-Wave 2X with over 1000 qubits. And stay tuned for what may be a watershed announcement from Google on Dec 8.

TensorFlow - Google’s latest machine learning system, is open sourced for everyone

Google is announcing TensorFlow, its open ­source platform for machine learning, giving anyone a computer and internet connection (and casual background in deep learning algorithms) access to one of the most powerful machine learning platforms ever created. More than 50 Google products have adopted TensorFlow to harness deep learning (machine learning using deep neural networks) as a tool, from identifying you and your friends in the Photos app to refining its core search engine. Google has become a machine learning company. Now they’re taking what makes their services special, and giving it to the world.

TensorFlow is a library of files that allows researchers and computer scientists to build systems that break down data, like photos or voice recordings, and have the computer make future decisions based on that information. This is the basis of machine learning: computers understanding data, and then using it to make decisions. When scaled to be very complex, machine learning is a stab at making computers smarter. That's the broader, and more ill-defined field of artificial intelligence. TensorFlow is extraordinary complex, because of its precision and speedin digesting and outputting data, and can unequivocally be placed in the realm of artificial intelligence tools.

The TensorFlow system uses data flow graphs. In this system, data with multiple dimensions (values) are passed along from mathematical computation to mathematical computation. Those complex bits of data are called tensors. The math-y bits are called nodes, and the way the data changes from node to node tells the overall system relationships in the data. These tensors flow through the graph of nodes, and that's where the name TensorFlow comes from.

Open-­sourcing TensorFlow allows researchers and even grad students the opportunity to work with professionally-built software, sure, but the real effect is the potential to inform every machine learning company’s research across the board. Now organizations of all sizes—from small startups to huge companies on par with Google—can take the TensorFlow system, adapt it to their own needs, and use it to compete directly against Google itself. More than anything, the release gives the world’s largest internet company authority in artificial intelligence.

Google's internal deep learning infrastructure DistBelief, developed in 2011, has allowed Googlers to build ever larger neural networks and scale training to thousands of cores in our datacenters. We’ve used it to demonstrate that concepts like “cat” can be learned from unlabeled YouTube images, to improve speech recognition in the Google app by 25%, and to build image search in Google Photos. DistBelief also trained the Inception model that won Imagenet’s Large Scale Visual Recognition Challenge in 2014, and drove our experiments in automated image captioning as well as DeepDream.

While DistBelief was very successful, it had some limitations. It was narrowly targeted to neural networks, it was difficult to configure, and it was tightly coupled to Google’s internal infrastructure -- making it nearly impossible to share research code externally.

TensorFlow is their second-generation machine learning system, specifically designed to correct these shortcomings. TensorFlow is general, flexible, portable, easy-to-use, and completely open source. They added all this while improving upon DistBelief’s speed, scalability, and production readiness -- in fact, on some benchmarks, TensorFlow is twice as fast as DistBelief.

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

China's two child policy should add 17 million babies from now to 2020 and a 0.5% annual GDP boost

China expects the new two child policy will result in an extra 17 million babies born within the next five years – more than three million more each year than at present. In some of those years, there are expected to be more than 20 million births.

Ninety million of the 140 million child-bearing age women who have been married and given birth to a child would now be allowed to have a second.

Prior to the introduction of the two-child policy, more than 38 per cent of the population were expected to be older than 60 by 2050. Beijing hoped the two-child policy could reduce this by two percentage points, Wang said. He added that the labour force would increase by 30 million by 2050.

The two-child policy would boost economic growth by 0.5 of a percentage point, a study by the Chinese Academy of Social Sciences estimated.

Wang said that the new policy had already provided a boost to the maternity industry, which had been performing well in the stock market recently.

After reaching 1.45 billion the population would drop back to 1.38 billion in 2050, Wang said, but the pressure of overpopulation would remain

Experimental drug targeting Alzheimer's disease shows anti-aging effects in animal tests

Salk Institute researchers have found that an experimental drug candidate aimed at combating Alzheimer’s disease has a host of unexpected anti-aging effects in animals.

The Salk team expanded upon their previous development of a drug candidate, called J147, which takes a different tack by targeting Alzheimer’s major risk factor–old age. In the new work, the team showed that the drug candidate worked well in a mouse model of aging not typically used in Alzheimer’s research. When these mice were treated with J147, they had better memory and cognition, healthier blood vessels in the brain and other improved physiological features.

“Initially, the impetus was to test this drug in a novel animal model that was more similar to 99 percent of Alzheimer's cases,” says Antonio Currais, the lead author and a member of Professor David Schubert’s Cellular Neurobiology Laboratory at Salk. “We did not predict we’d see this sort of anti-aging effect, but J147 made old mice look like they were young, based upon a number of physiological parameters.”

Journal Aging -A comprehensive multiomics approach toward understanding the relationship between aging and dementia 

Could the USA double energy efficiency by 2030

Assuming the US Congress ever became capable of passing legislation again, how much more energy-efficient could the United States actually get?

By some accounts, the United States could stand to get twice as efficient in the coming decades, saving hundreds of billions of dollars and slashing its global-warming emissions in the process. Yet other economists have been a bit more skeptical that boosting energy efficiency is really so easy — or a surefire way of tackling global warming.

The Alliance to Save Energy has a report on how the United States could double its "energy productivity" by 2030 — that is, double the amount of economic activity generated from a given unit of energy.

The US is less energy-efficient than many other industrialized nations, including Japan, France, and Germany. Cross-country comparisons can sometimes be misleading, since different countries are in different situations with regard to their size, industrial structure, climate, and so on.

The report notes, for instance, that many buildings in the United States could employ much more-efficient lighting, insulation, roofing, and boilers to cut their energy use by up to 50 percent. But, for the most part, these readily available technologies have been slow to catch on.

Ultrathin coating can defeat ultrahigh frequency microwave radar for more stealthy fighter jets

A group of scientists from China may have created a stealth material that could make future fighter jets very difficult to detect by some of today’s most cutting-edge anti-stealth radar.

The researchers developed a new material they say can defeat microwave radar at ultrahigh frequencies, or UHF. Such material is usually too thick to be applied to aircraft like fighter jets, but this new material is thin enough for military aircraft, ships, and other equipment.

Today’s synthetic aperture radar use arrays of antennas directing microwave energy to essentially see through clouds and fog and provide an approximate sense of the object’s size, the so-called radar cross section. With radar absorbent material not all of the signal bounces back to the receiver. A plane can look like a bird.

Their proposed absorber is almost ten times thinner than conventional ones.

They proposed and fabricated an ultra-thin broadband AFSS absorber with an ST pattern for UHF applications. Based on the TL model, the resonance frequency and real part of input impedance are given as functions of loaded and distributed parameters. With ST coefficients of x = y = 1, the tunability and strong absorption are concisely demonstrated. The calculated results suggest that the varactor modulates the imaginary part of the input impendence, producing the tunability, while the resistor mainly adjusts real part, producing the strong absorption. Applying various ST coefficients to the unit cell pattern, they found that a small x/y effectively expands the tunable bandwidth. The measured reflectivity of the proposed absorber covers a broad band of 0.7–1.9 GHz below −10 dB, and the total thickness 7.8 mm is only ∼λ/29 of the center frequency. As radar detection equipment continues to improve, their thin absorbers with broad bandwidth and working in the UHF band will be widely useful.

Journal of Applied Physics - An ultra-thin broadband active frequency selective surface absorber for ultrahigh-frequency applications

US Army seaks to Unleash brainpower for cognitive dominance using virtual reality and machine augmentation

"Human performance will be as important, if not more important, than technology in 2030," predicted a high-level Army intelligence expert.

The reason is that "we've seen an erosion in our technological advantage to overmatch adversaries," a trend that will continue, said Thomas Greco, G-2 for the U.S. Army Training and Doctrine Command.

Greco and Dr. Kira Hutchinson, director, intelligence/engagement, TRADOC, G-2, spoke during a Nov. 9 media teleconference that summarized findings of the Mad Scientist 2015 conference's "Human Dimension 2025 and Beyond: Building Cohesive Teams to Win in a Complex World," held Oct. 27 - 28 on Fort Leavenworth, Kansas.

Brainpower Unleashed

The key to optimizing human performance, Greco said, is tapping into the energy and power of the human brain.

To reduce the risk of technological overmatch, the Army must create a culture of rapid learning, enhanced empathy and neural plasticity, he said.

Hutchinson said neural plasticity refers to structural and processing changes to the brain due to effective cognitive training. It was once thought that the brain developed to a great extent only in early childhood, but studies have since shown that the brain can continue to develop throughout a person's lifetime.

Army scientists, for example, have effectively used cognitive therapy to mitigate the effects of damage to the brain following wounds and injuries, she said. But in the current context, the idea is to explore how neural plasticity can also work to help healthy Soldiers perform even more optimally.

November 12, 2015

Common units and understanding energy and the global scale of energy

Dr. Ripudaman Malhotra, co-author of A Cubic Mile of Oil, discusses the moral imperative for increasing total global energy supply equivalent to several cubic miles of oil. He shows what it would take to scale any technology to produce 1 cmo of energy per year.

In 2006, the world used a cubic mile of oil. In total the energy the world used was equal to about 3.1 cubic miles of oil when we convert the other energy to be equal amounts of oil.

Thorcon Plan - Scaling factory mass production nuclear power to really compete with coal

The developing world will be going from almost no power to some kind of power. If we do not have something cheaper than coal then they will use coal because they do not have money for anything else.

We have to have 100 GW per year at least to seriously compete with coal.

China J31 stealth fighter (a knockoff of the US F35), has to overcome engine and sensor issues

The J-31 fighter jet had poor performance in air demonstrations at the 2014 Airshow China in Zhuhai. This has prompted officials from the state-run Aviation Industry Corporation of China (AVIC) to emphasise the future development path for the aircraft. The builder AVIC is attempting to convey the perception that the actual "FC-31" production-standard aircraft will incorporate improvements to address the shortcomings seen in the airframe's performance to date. One item most commonly mentioned is a new engine that would replace the Klimov/Sarkisov RD-93 engine that is installed in the J-31. The RD-93, a version of the Mikoyan MiG-29's RD-33, differs from the original by having an accessory pack that includes the engine's gearbox rotated from the top to the bottom of the engine installation.

The J31 is believed to have been built from stolen detailed designs of the US F35 stealth fighter. China is trying to sell J31 planes to Pakistan and Iran.

Aviation Industry Corporation of China (AVIC) is making an aggressive push to sell the J-31 stealth fighter to international customers at the Dubai airshow. AVIC intends to fly a production version of its “Gyrfalcon” by 2019. The aircraft could become operational as early as 2022. Full operational capability would follow roughly three years later.

China is working on jet engine technology. But Beijing has not yet mastered propulsion technology that would allow its products to compete on the international marketplace independent of Russian largesse. The Russians supply the engines for most of China’s offering like the FC-1 Xiaolong—which is also known as the JF-17 Thunder. The JF-17 is powered by a single 19,000lbs thrust-class Klimov RD-93 afterburning turbofan that was derived from the MiG-29’s RD-33 engine.

However, the Chinese are known to be working on an indigenous replacement for the RD-93 on the JF-17 called the Guizhou WS-13. The indigenous motor—should it prove to be viable—has slightly more thrust than the Russian engine. A prototype JF-17 has flown with the new engine according to Chinese officials who spoke at the Paris air show.

If the Chinese are truly close to perfecting a production ready WS-13—as some in the Pentagon claim—then that engine could be developed into a propulsion system for the J-31. Chinese officials speaking to reporters at the Dubai airshow indicated that the production FC-31 would be powered by a Chinese-made “advanced medium thrust engine” producing roughly 20,000lbs of thrust.

Coal is still King in China as 155 coal plants were approved so far in 2015

In the first nine months of this year, state-owned companies in China received preliminary or full approval to build the 155 coal power plants that have a total capacity of 123 gigawatts, the report said. That capacity is equal to 15 percent of China’s coal-fired power capacity at the end of 2014.

The construction boom — with capital costs estimated by Greenpeace at $74 billion — is a clear sign that China remains entrenched in investment-driven growth, despite promises by leaders to transform the economic model to one based on consumer spending.

It also raises questions about whether China is weaning itself from coal as quickly as it can and whether officials are sufficiently supporting nonfossil fuel sources over coal.

The dominance of coal power had led to “a sharp decline in investments in renewable energy.”

Hydropower is generated by provincial or central state-owned enterprises. The China Electricity Council, a power industry association, said in a report this year that investment in hydropower had dropped for three straight years and that the amount in the first quarter of 2015 was half that of the same period in 2012.

Nextbigfuture notes that China is reaching the limit of how much hydropower is possible. China has dammed almost every river that can generate hydropower.

China is building more renewable and nuclear energy capacity. The government has said that by 2020, 15 percent of energy consumption will be met by sources beyond fossil fuel. The growth in renewables and nuclear power is expected to meet an estimated 3 to 4 percent annual growth in electricity demand in the coming years

Mexico will boost nuclear energy and increase non-fossil fuel energy from 21% now to 35% in 2024

A Mexican senator is preparing legislation that would pave the way for expansion of the nation’s only nuclear power plant as part of its drive toward developing more clean energy.

The bill is meant to encourage additional investment in the nuclear sector, beginning with the Laguna Verde plant in the state of Veracruz in eastern Mexico, said author Jose Luis Lavalle, a senator in the National Action Party. Laguna Verde has two working reactors, but was designed for four with a capacity to generate 1,510-megawatts of electricity, according to the Comision Federal de Electricidad, or CFE.

The nuclear effort follows Mexico’s move to build up its oil and natural gas industry by inviting investment from foreign companies. The government set a mandate in 2012 to get 35 percent of the country’s energy from non-fossil fuel sources by 2024, up from 21 percent now.

November 11, 2015

Super H-mode plasma could greatly increase tokomak fusion power

Meet "Super H mode," a newly discovered state of tokamak plasma that could sharply boost the performance of future fusion reactors. This new state raises the pressure at the edge of the plasma beyond what previously had been thought possible, creating the potential to increase the power production of the superhot core of the plasma.

Discovery of this mode has led to a new line of research within plasma physics that aims to define a path to higher power. The route could prove particularly promising for ITER, the international experiment under construction in France to demonstrate the feasibility of fusion energy.

Researchers led by Wayne Solomon of the U.S. Department of Energy's Princeton Plasma Physics Laboratory (PPPL) accessed the new state on the DIII-D National Fusion Facility that General Atomics operates for DOE in San Diego. Motivating their findings were theoretical predictions of a plasma state beyond H-mode, the current regime for high-level plasma performance.

In this figure, the red signifies instability while blue is the quiescent region. Plasma density needs to increase along the narrow blue channel to reach the Super H-mode state. CREDIT Image adapted from General Atomics.

The team is led by Dr. Xianzu Gong of ASIPP and Dr. Andrea Garofalo of General Atomics (GA) in San Diego. Using both China's EAST facility and the DIII-D National Fusion Facility, operated by GA for the U.S. Department of Energy, the team has investigated the "high-bootstrap current" scenario, which enhances self-generated ("bootstrap") electrical current to find an optimal tokamak configuration for fusion energy production.

oving the plasma closer to the wall removed the kink mode and enabled higher plasma pressure, which, in turn, makes the plasma less dependent on externally injected flow. This is important because in a tokamak reactor, such as ITER, it is very difficult and expensive to drive a rapid plasma flow with external means.

The team performed the most recent bootstrap exploration in DIII-D, following-up work on the record-setting milestone achieved at China's EAST tokamak, where GA scientists have also been collaborating. An ASIPP scientist Dr. Qilong Ren will deliver the invited talk on the topic of Magnetic Confinement-Experiments.

Bell Lockheed say Valor Tiltrotor future vertical lift vehicle could be operation by2025

As the Pentagon considers the future of military vertical lift, Bell Helicopter is talking with the US Navy and Air Force about designing a next-generation tiltrotor solution that could be ready by 2025.

Bell is partnered with Lockheed Martin to build a rotorcraft flight demonstrator as part of the US Army’s Joint Multi-Role program, which will gauge the art of the possible for the path ahead. The demonstrator program will inform the Army’s Future Vertical Lift effort to buy a new state-of-the-art family of helicopters in the 2030s.

The Bell-Lockheed team is offering its V-280 Valor tiltrotor, which builds on the technology developed for Bell-Boeing’s V-22. The competing team, made up of Sikorsky Aircraft and Boeing, is working on a coaxial helicopter known as the SB-1 Defiant for the demonstrator effort.

Although the demonstrator prototypes will fly in 2017, the Army is not planning a contract award until the late 2020s, Harris said. But he stressed that company officials believe the Bell-Lockheed team could achieve initial operational capability by 2025.

“It wouldn’t be with the Army then, unless we could get the Army to come to the left,” Harris said. “The other services are already thinking ahead of the power curve, and they are thinking that they can move that to the left. We can actually be in full-rate production of this aircraft for another service by 2024 or 2025.”

Bell’s goal is ultimately to replace all the Pentagon’s helicopters with the V-280, Harris said, touting the plane’s speed and flexibility. The Valor will have twice the speed and range of the Army’s UH-60 Black Hawk, more than doubling operational reach, according to Bell’s website. The future plane will also outperform the V-22, Harris said, with a combat radius of 1,200 nautical miles compared to the Osprey’s 900 nautical miles.

Thorium summary video

A half barrel of rock holds the Thorium need to provide 91000 kwh which is the annual power needed for electricity, transportation and heat.

54 barrels of oil = 12 tons of coal = 5300 cubic feet of natural gas = 4 grams of thorium

5000 tons of thorium to power the current world energy needs.
Monazite rare earth waste streams would have all the thorium that we need.

The current nuclear reactors answer the question how would you power a 1950s era nuclear submarine.

Rich countries can over pay for things. Over pay for medicine, over pay for energy. 80% of the world cannot afford to do this.

All the batteries in the world would hold 10 minute of the power used in the world.

Elon Musk tracking all advanced battery developments and sees nothing in the near term that would disrupt the Gigafactory of batteries

Tesla Motors and Elon Musk track about 60 different advanced battery development efforts around the world. Some of the efforts to develop improved batteries and hold some long-term promise. they rate all of them from one to five, where five is Tesla should be doing business with them and one is complete BS.”

Elon Musk said there were no four or fives, but there were some threes, based on that rating system.

There is a slight chance that there could be some super secret laboratory somewhere where a new battery technology is being developed that Tesla doesn’t know about. But he said it’s unlikely because Tesla is the biggest consumer of lithium-ion in the consumer world, so it would make the most sense for them to license to Tesla.

With the Gigafactory, Tesla aims to use the economy of scale to bring down the price of its technology, and thus of its vehicles.

“Certainly incremental improvements to the battery pack range are important, but the thing that is really is reducing the cost per kilowatt hour...the fundamental focus is the cost per unit of energy. So that is what the Gigafactory is about. It’s taking economy of scale as far as we can possibly imagine, to a very extreme level,” Musk said.

Video of Elon Musk talking with Ron Baron

Elon Musk sits with Ron Baron from Baron Capital Management at the Baron Investment Conference.

00:00. Introduction
03:50. Early days, motivation & oil industry FUD campaign
11:25. Birth and rise of Tesla
16:20. Huge Tesla factory
19:25. Tesla ambition - millions of cars
20:33. Gigafactory Government fundings
24:19. Gigafactory media incident
25:22. Battery technology outlook & costs
33:00. Tesla safety
40:13. SpaceX reusable rockets
44:15. Lyft vs. Uber
Question and Answer
46:20. Model 3 driving experience
48:50. Charging locations

Nvidia’s Jetson TX1 is more than five times as energy efficient for machine learning applications versus Intel Skylake chip

Nvidia is hoping to attract machine learning developers with the Jetson TX1, an ARM-based development board powered by the top-end Tegra X1 SoC. The company claims that in certain deep learning tasks that rely on dynamic input and computations—autonomous drones, facial recognition and behavioural analysis, and computer vision—the Jetson TX1 will beat out an Intel Core i7 6700K Skylake CPU in performance.

The TX1's machine learning prowess—should Nvidia's benchmarks hold out under real-world testing—is largely down to the GPU, which excels at the kind of parallel processing required by machine learning and deep neural networks. While the graphics performance of the GPU in the TX1 is just shy of the GPU performance of an i7-6700K, it offers far more performance per watt—up to five times according to Nvidia.

The full TX1 kit comes bundled with Ubuntu 14.04 LTS and Linux 4 Tegra, complete with full OpenGL and OpenGL ES support. While that might sound enticing for knocking up your own custom HTPC, the TX1 doesn't come cheap. The full kit costs $599 (~£450) at retail, or $299 (~£250) to educational institutions. Pre-orders open November 12 in the US, with units shipping on November 16. An international launch will follow later. The standalone module will be available early next year for $299.

Los Alamos National Laboratory Orders a 1000+ Qubit D-Wave 2X Quantum Computer

D-Wave Systems Inc., the world's first quantum computing company, announced that Los Alamos National Laboratory will acquire and install the latest D-Wave quantum computer, the 1000+ qubit D-Wave 2X™ system. Los Alamos, a multidisciplinary research institution engaged in strategic science on behalf of national security, will lead a collaboration within the Department of Energy and with select university partners to explore the capabilities and applications of quantum annealing technology, consistent with the goals of the government-wide National Strategic Computing Initiative. The National Strategic Computing Initiative, created by executive order of President Barack Obama in late July, is intended "to maximize [the] benefits of high-performance computing (HPC) research, development, and deployment."

"Eventually Moore's Law (that predicted that the number of transistors on an integrated circuit would double every two years) will come to an end," said John Sarrao, associate director for Theory, Simulation, and Computation at Los Alamos. "Dennard Scaling (that predicted that performance per watt of computing would grow exponentially at roughly the same rate) already has. Beyond these two observations lies the end of the current 'conventional' computing era, so new technologies and ideas are needed."

NVIDIA Jetson TX1 for teraflop computing in a credit card size form

NVIDIA Jetson is the world's leading visual computing platform for GPU-accelerated parallel processing in the mobile embedded systems market. Its high-performance, low-energy computing for deep learning and computer vision makes Jetson the ideal solution for compute-intensive embedded projects like:

  • Drones
  • Autonomous Robotic Systems
  • Advanced Driver Assistance Systems (ADAS)
  • Mobile Medical Imaging

Jetson TX1 is a supercomputer on a module that's the size of a credit card. It features the new NVIDIA Maxwell™ architecture, 256 NVIDIA CUDA® cores, 64-bit CPUs, and unmatched power efficiency. Plus, it includes the latest technology for deep learning, computer vision, GPU computing, and graphics, making it ideal for embedded visual computing.

It's built around the revolutionary NVIDIA Maxwell™ architecture with 256 CUDA cores delivering over 1 TeraFLOPs of performance. 64-bit CPUs, 4K video endcode and decode capabilities, and a camera interface capable of 1400 MPix/s make this the best system for embedded deep learning, computer vision, graphics, and GPU computing.

Personal jetpack JB-9 flew a person around the Statue of Liberty

An aviator flew by jetpack in a controlled and sustained flight around Statue of Liberty.

The JB-9 is small enough to sit in the back seat of a car but powerful enough to fly thousands of feet high.

The JB-9 jetpack, approved for the flight by the FAA and US Coast Guard was developed by legendary Hollywood inventor (and winner of 3 Academy Awards), Nelson Tyler and Mayman. The miniature jet-turbine back pack is fast, powerful, and unlike rocket powered belts, safe and practical to operate. Tyler and Mayman have spent millions of dollars and thousands of hours secretly developing the device which has never before been seen in public. Their struggle has been documented over the last eight years by an Emmy-award winning film team.

The JB-9 is powered by two turbine jet engines that have been specially adapted.

Its inventors says it is 'inherently stable but also capable of very dynamic manoeuvres thanks to our approach to engine vectoring'

Early testing of the next version, JB-10, indicates that it will achieve flights of over 10,000 feet altitude, at speeds greater than 100 mph and with an endurance of 10 minutes + (depending on pilot weight).

The JB-9 uses a carbon-fiber corset that straps to the pilot's back, with the majority of the 'backpack' section carrying fuel.

Mounted to each side is a small jet turbine engine that provides upward thrust.

On the left controller is a yaw twistgrip.

The JB-9 carries 10 pounds of kerosene fuel that burns through two vectored thrust engines at a rate of one gallon per minute for up to ten minutes of flying time - depending on pilot weight. Weight of fuel is a consideration but it's reported to start with 500ft/minute climb rate that doubles as the fuel burns off. While this model has been limited to 55knots (100kph), the prototype of the JB-10 is reported to fly at over 200kph.

This is a true jetpack: a backpack that provides jet-powered flight. Most of the volume is the fuel tank, with twin turbine jet engines gimbal-mounted on each side. The control system is identical to the Bell Rocketbelt: tilting the handgrips vectors the thrust - left-right and forward-back - by moving the actual engines; twisting left hand moves two nozzle skirts for yaw; while twisting the right hand counterclockwise increases throttle. Jetpack Aviation was started by Australian businessman David Mayman with the technical knowhow coming from Nelson Tyler, prolific inventor of helicopter-mounted camera stabilizers and one of the engineers that worked on the Bell Rocketbelt that was used in the 1984 Olympic

November 10, 2015

Army MIND lab is able to decode brain signals in real time

In an Army Research Laboratory facility here called "The MIND Lab," a desktop computer was able to accurately determine what target image a Soldier was thinking about.

MIND stands for "Mission Impact Through Neurotechnology Design," and Dr. Anthony Ries used technology in the lab to decode the Soldier's brain signals.

Ries, a cognitive neuroscientist who studies visual perception and target recognition, hooked the Soldier up to an electroencephalogram - a device that reads brain waves - and then had him sit in front of a computer to look at a series of images that would flash on the screen.

There were five categories of images: boats, pandas, strawberries, butterflies and chandeliers. The Soldier was asked to choose one of those categories, but keep the choice to himself. Then images flashed on the screen at a rate of about one per second. Each image fell into one of the five categories. The Soldier didn't have to say anything, or click anything. He had only to count, in his head, how many images he saw that fell into the category he had chosen.

When the experiment was over, after about two minutes, the computer revealed that the Soldier had chosen to focus on the "boat" category. The computer accomplished that feat by analyzing brainwaves from the Soldier. When a picture of a boat had been flashed on the screen, the Soldier's brain waves appeared different from when a picture of a strawberry, a butterfly, a chandelier or a panda appeared on the screen.

"We want to create a solution where image analysts can quickly sort through large volumes of image data, while still maintaining a high level of accuracy, by leveraging the power of the neural responses of individuals," he said.

Dr. Anthony Ries instructs Pfc. Kenneth Blandon on how to play a computer game, using only his eyes to control the direction of fire of a bubble-shooting cannon at Aberdeen Proving Ground, Md., Nov. 3, 2015. Ries is a cognitive neuroscientist, who studies visual perception and target recognition. Blandon is a mechanic with the 20th Chemical, Biological, Radiological, Nuclear and Explosives Command.

Wireless remote brain interfaces

Wireless remote brain interfaces

Dr. Polina Anikeeva is an assistant professor of Materials Science and Engineering at MIT and a principle investigator of the Bioelectronics group. Her research lies in the field of neuroprosthetics and brain-machine interfaces. Together with her group she explores optoelectronic, fiber-based and magnetic approaches to minimally invasive neural interrogation. Her group was first to demonstrate multifunctional flexible fibers for simultaneous optical stimulation, electrical recording and drug delivery in the brain and spinal cord, as well as magnetic nanomaterials for wireless magnetic deep brain stimulation.

Science - Magnetic 'rust' controls brain activity

A study in mice points to a less invasive way to massage neuronal activity, by injecting metal nanoparticles into the brain and controlling them with magnetic fields. The technique could eventually provide a wireless, nonsurgical alternative to traditional deep brain stimulation surgery.

Optogenetics has revolutionized how neuroscientists study the brain by allowing them to directly manipulate specific neural circuits. But it isn’t practical for human deep brain stimulation. The technique requires that animals be genetically modified so that their neurons respond to light. Light also scatters in brain tissue. So rodents in optogenetics experiments must remain tethered to a surgically implanted, fiber optic cable that delivers laser beams directly to the brain region of interest.

Unlike light, low-frequency magnetic fields pass straight through brain tissue as if it were "transparent," Anikeeva says. That makes those types of magnetic fields an ideal vehicle for delivering energy into the brain without damaging it. Clinicians have long tried to do just that by placing magnetic field coils near a patient’s head. This so-called transcranial magnetic stimulation (TMS) triggers the flow of small electrical currents in neural circuits beneath the coils. But the magnetic fields used in TMS affect only brain tissue near the brain’s surface. Anikeeva, who is now at the Massachusetts Institute of Technology (MIT) in Cambridge, decided to see if she could use magnetic nanoparticles to go deeper.

Previous cancer studies had shown that by injecting tumors with magnetic nanoparticles made of iron oxide—“essentially rust, with well-tuned magnetic properties," Anikeeva says—then exposing them to rapidly alternating magnetic fields, excited nanoparticles can be used to heat and destroy cancer tumors while leaving surrounding, healthy tissue intact. Anikeeva wondered if a similar method could be used to merely stimulate select groups of neurons deep within the brain.

To find out, she and her MIT colleagues targeted a class of proteins called TRPV1 channels, which are found in neurons that respond to heat and certain chemicals in food. Every time you touch a hot iron or eat a spicy pepper, TRPV1-containing neurons fire. Anikeeva and her colleagues injected custom-made, 20-nanometer iron oxide particles into a region of the rodents' brains called the ventral tegmental area (VTA), a well-studied deep brain structure essential to the experience of reward, which plays a central role in disorders such as addiction and depression in people.

TRPV1-containing neurons are abundant in this region in humans, but sparse in mice. So the team also injected the rodents with a virus that increased cell expression of the channel just within that brain area. Such an approach would not be feasible in people, but made the experiment easier to evaluate, Anikeeva says.

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