Daily Archives: February 29, 2020

The marathon to achieve the promise of quantum computers hasedged a few steps forward as Intel unveils a new chip capable, it believes, of accelerating the process.

Called Horse Ridgeand named after one of the coldest places in Oregon, the system-on-chip can control a total of 128 qubits (quantum bits) which is more than double the number of qubits Intel heralded in its Tangle Lake test chip in early 2018.

While companies like IBM and Microsoft have been leapfrogging each other with systems capable of handling ever greater qubits the breakthrough in this case appears to be an ability to lead to more efficient quantum computers by allowing one chip to handle more tasks. It is therefore a step toward moving quantum computing from the lab and into real commercial viability.

Applying quantum computing to practical problems hinges on the ability to scale, and control, thousands of qubits at the same time with high levels of fidelity. Intel suggests Horse Ridge greatly simplifies current complex electronics required to operate a quantum system.

To recap why this is important lets take it for read that Quantum computing has the potential to tackle problems conventional computers cant by leveraging a phenomena of quantum physics: that Qubits can exist in multiple states simultaneously. As a result, they are able to conduct a large number of calculations at the same time.

This can dramatically speed up complex problem-solving from years to a matter of minutes. But in order for these qubits to do their jobs, hundreds of connective wires have to be strung into and out of the cryogenic refrigerator where quantum computing occurs (at temperatures colder than deep space).

The extensive control cabling for each qubit drastically hinders the ability to control the hundreds or thousands of qubits that will be required to demonstrate quantum practicality in the lab not to mention the millions of qubits that will be required for a commercially viable quantum solution in the real world.

Researchers outlined the capability of Horse Ridge in a paper presented at the 2020 International Solid-State Circuits Conference in San Francisco and co-written by collaborators at Dutch institute QuTech.

The integrated SoC design is described as being implemented using Intels 22nm FFL (FinFET Low Power) CMOS technology and integrates four radio frequency channels into a single device. Each channel is able to control up to 32 qubits leveraging frequency multiplexing a technique that divides the total bandwidth available into a series of non-overlapping frequency bands, each of which is used to carry a separate signal.

With these four channels, Horse Ridge can potentially control up to 128 qubits with a single device, substantially reducing the number of cables and rack instrumentations previously required.

The paper goes on to argue that increases in qubit count trigger other issues that challenge the capacity and operation of the quantum system. One such potential impact is a decline in qubit fidelity and performance. In developing Horse Ridge, Intel optimised the multiplexing technology that enables the system to scale and reduce errors from crosstalk among qubits.

While developing control systems isnt, evidently, as hype-worthy as the increase in qubit count has been, it is a necessity, says Jim Clarke, director of quantum hardware, Intel Labs. Horse Ridge could take quantum practicality to the finish line much faster than is currently possible. By systematically working to scale to thousands of qubits required for quantum practicality, were continuing to make steady progress toward making commercially viable quantum computing a reality in our future.

Intels own research suggests it will most likely take at least thousands of qubits working reliably together before the first practical problems can be solved via quantum computing. Other estimates suggest it will require at least one million qubits.

Intel is exploring silicon spin qubits, which have the potential to operate at temperatures as high as 1 kelvin. This research paves the way for integrating silicon spin qubit devices and the cryogenic controls of Horse Ridge to create a solution that delivers the qubits and controls in one package.

Quantum computer applications are thought to include drug development high on the worlds list of priorities just now, logistics optimisation (that is, finding the most efficient way from any number of possible travel routes) and natural disaster prediction.

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New Intel chip could accelerate the advent of quantum computing - RedShark News

Aravind Ajad Yarra and Saji Thoppil, fellows at Wipro Limited, answer frequently asked questions about quantum computing

What should be kept in mind when implementing quantum technology?

Todays leaders are inundated with the disruptive power of quantum computing and its potential applications in AI, machine learning and data science. Gartner data reveals that by 2023, 95% of organisations researching it will utilise quantum-computing-as-a-service (QCaaS) to minimize risk and contain costs. Also, 20% of organisations will be seen budgeting for quantum computing projects, compared to less than 1% today.

We, Aravind Ajad Yarra, fellow, Wipro Limited and Saji Thoppil, fellow and chief technologist cloud and infrastructure Services, Wipro Limited, bring you the basics of quantum computing and demystify some of its unknown facets in todays evolving scenario.

Lets look at the commonly asked questions:

A: Most of us would have read quantum mechanics at high-school level physics and probably been baffled by its strange characteristics. Quantum mechanics is the physics that applies at atomic and subatomic levels. Thought of using the physics of quantum mechanics to computing is what has led to quantum computing.

Our present-day computing is largely based on Boolean logic, represented using binary bits, which assume the value of either 0 or 1. Quantum computing, on the other hand, uses quantum bits (qubits), which behave differently from classic bits and use quantum superposition state where each qubit can assume both 0 and 1 at the same time.

To get better clarity, I suggest reading this short article on quantum computing.

A: Quantum computing is one of the most exciting developments in recent computing history. For years, Moores law has been helping us to keep the innovation cycle in computing going and push the boundaries of what computing can offer to business, so much so that software is what is driving digital businesses. With Moores law reaching its saturation point, everyone is eagerly looking for whats next in computing. This is seen as something that can keep the computing innovation cycle going, hence this buzz.

If you hear the general hype, you might believe quantum computing might replace classic computing soon. However, that is far from reality. The superposition property that we mentioned earlier gives quantum computing some unique capability that traditional computing doesnt have. Simply put, qubit superposition allows quantum computing to solve certain classes of problems promptly, which might otherwise take years for classical computers.

IBM has established a roadmap for reaching quantum advantage and concluded that: for significant improvement over classical systems, the power of quantum computers must double every year. Read here

A: Quantum computers are not bigger or faster versions of existing computers. Quantum computing is fundamentally different from existing computing. The problems for which quantum computers are most useful are problems that classical computers are not good at.

Some of the classes of problems that quantum computers currently look at are optimisation problems, for example, addressing the classic travelling salesman problem. As the number of cities that have this problem increases, classic computers find it exponentially hard to find an optimum solution. Quantum computers proved very useful for these classes of problems. Solving such problems make quantum computers super useful in areas like gene analysis, drug discovery, chemical synthesis, weather simulations, newer types of encryption, unstructured search, and better deep neural networks, to name a few.

What is AI? Information Age has created a simple guide to AI, machine learning, neural networks, deep learning and random forests. Read here

A: There are two major approaches to quantum computing that are currently in use: circuit-based computers (aka universal quantum computers), and adiabatic computers.

Universal quantum computers are based on logical gates and work similar to the underlying logic foundations of classical computers. Hence, universal quantum computers are extremely useful for computing problems improving on our current knowledge base of solutions. However, qubits required for universal quantum computers are extremely difficult to realise physically because qubit instability makes it hard to produce universal quantum computers.

Adiabatic computers are analog, but are easier to produce. These are more relaxed with respect to qubit state stability. Hence, it is easier to produce 1000s of qubits on adiabatic computers. However, adiabatic computers can be used for limited use cases such as optimisation problems.

A: While most platform companies that are working to build quantum computers are taking bets on one or the other, enterprises can probably explore both of the models. While adiabatic computing is limited, there are production-ready adiabatic computers using real quantum bits (such as those from DWave), as well as digital annealers, which use digital qubits (from Atos and Fujitsu).

Its emerging technologies month on Information Age, that means augmented and virtual reality, quantum computing and blockchain. Read here

Circuit-based quantum computers are much more general purpose. While these have more utility for enterprises, no production-grade problems can be currently solved with the current state of these machines. I would suggest exploring both classes of computers, based on the case that one is trying to solve.

A: The best way to start with identification of use cases for quantum computing is to explore areas where classic computers are currently not good at. Optimisation problems are the best starting point for most enterprises. Based on the industry, different kinds of optimisation use cases can be considered for exploring quantum computers. These could be risk modelling, inventory or asset optimisation, among others.

Cryptography is another area where robust use cases can be identified by enterprises. Quantum computers, when production-ready, can potentially break current methods of encryption, leading to exposure of sensitive data. Identifying data that is very sensitive and has longer term value, and considering safe encryption methods using quantum key generation and distribution are other ways in which it can be used.

Machine learning is also a very promising use case. Quantum machine learning, as it is called, can use special purpose quantum circuits that can significantly boost the efficiency of machine learning algorithms.

A: Industries that are process-centric, such as pharmaceuticals and oil & gas exploration, are the early adopters. These industries can benefit from quantum computing in complex optimisation problems they need solve from time to time.

Apart from these asset-heavy industries, the manufacturing industry is also actively exploring quantum computing. Banks and other financial services companies, which have risk modelling needs, also rely a lot on quantum computing.

A: It is probably too early to talk about real-world scenarios where quantum computers have made an impact. While there are demonstrations by research labs to use quantum communication methods to send instant data transfer from satellite and breaking various encryption methods, these still look good in labs.

The reason for this is the current state of reliability in quantum computers. Qubits are highly sensitive, and they are prone to errors. Error correction methods that we currently use reduce the effective working qubits, but early results have been seen with digital annealers, which simulate adiabatic quantum computing using traditional digital computers.

Wipros Topcoder, for example, is currently working with Fujitsu to run crowdsourced challenging using Fujitsus digital annealer to solve real-world problems. Additionally, Airbus has been running open innovation challenges to solve some of its problems using quantum computing.

Quantum technologies also has appeal in the areas of communication, cryptography, sensors and measurements. Unlike quantum computing, where practical use cases are still in exploratory stages, these areas have industry-ready products that enterprises can put to use.

Quantum communication takes advantage of the nature of photons in flight and is able to detect if a photon has reached the recipient uninterrupted; this can ensure secure communications.

While quantum key generation (QKG) is used to generate truly random keys, quantum key distribution (QKD) is used for securely distributing keys. Both of these are essential for using a one-time pad cryptography technique, which is considered the holy grail in encryption.

Generating true random numbers for the quantum computing era, or indeed the pre-quantum era, is the aim. Crypta Labs reckon they have cracked it. Read here

Additionally, quantum sensors have niche applications where there is a need for highly accurate measurements of gravity, electric fields, time, position and magnetic field. In a fiercely competitive world, we can expect more enterprises wanting to leverage these to create unique offerings.

Given the nature of its evolution, it is hard to make an upfront business case for quantum computing. However, given the potential, I suggest that the business case be made in two parts.

The first part is to focus on near-term (1-2 years) use cases such as optimisation and encryption by using digital annealers for optimisation and photon-based ASICS for key generation. Digital annealers, or even simulators running on cloud, can solve several practical optimisation problems.

On the other hand, centres of excellence can be set up, leading to building expertise and solving relevant problems. Returns from these investments would set the stage for the second part, focusing on mid & longer term (2+ years) use cases, such as exploring machine learning and unstructured data search as part of centres of innovation and open innovation communities with small investments, but with longer period on returns.

Written by Aravind Ajad Yarra, fellow at Wipro Limited, and Saji Thoppil, fellow and chief technologist cloud and infrastructure Services at Wipro Limited

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Cracking the uncertainty around quantum computing - Information Age

According to Moore's law, since the introduction of the first semiconductors, the number of transistors on an integrated circuit has doubled approximately once every 18 months.

However, now that transistors are starting to reach near-atomic sizes, their reduction is becoming increasingly problematic, and as such, this doubling effect is beginning to plateau.

One technology research institute, CEA-Leti, is developing techniques to increase the power of semiconductors.

But what are these new technologies and how will they affect modern electronics?

Developers are increasingly searching for efficient ways toreplace portable power sources that require charging or replacement.

However, such a feat is only possible if power can be extracted from the local environment, like in the instance of a device from the University of Massachusetts Amherst that powers small electronics from moisture in the air.

A more conventionalmethod for energy extraction is using the Peltier effect, which requires a heat differential (such as cold air on a warm wrist), but these are often cumbersome and require heat sinks.

Another method is the use of vibration energy from motion, whereby a cantilever vibrates a piezo element, converting the mechanical energy to electrical energy.

Butthese systems are problematic because they are often tuned for one frequency of vibration. This means that their efficiency is only maximized when external mechanical energy is of the same frequency.

This is where CEA-Letis energy harvesting system comes in.

The energy harvesting systemconverts mechanical energy into electrical energy to power an IC. While similar to a cantilever system, which converts mechanical motion into electrical energy using a piezo effect, the cantilever is electrically tunable, allowingit to match its resonant frequency to the peak frequency of the external mechanical force.

Using an adjustable resonant system increases the harvesting bandwidth by 446%from typical cantilever systems and increases energy efficiency by 94%. The energy needed to control the system is two orders of magnitude lower than what the system harvests; the system requires around 1 W while the energy harvested is between 100 W and 1 mW.

While quantum computing will bring some major changes to the field of computation, they are far from becoming commercialized.

Many hurdles, such as low-temperature requirements, make them difficult to put into everyday applications. But one area, in particular, that is problematic is their integration into standard circuitry.

In a study on energy-efficient quantum computing, researchers explain thatqubits, which are bits in superposition states,must be kept well away from external sources of energy. This is becauseany exposure to external energy puts the qubits at risk ofcollapsing their wavefunction. Such sources of energy can include magnetic field fluctuations, electromagnetic energy, and heat (mechanical vibration).

To make things more complicated, quantum computer circuitry is at some point required to interface with traditional electronic circuitry, such as analog and digital circuits. If these circuits are external to the quantum circuitry, then the issue of space and speed become an issue; remote circuitry takes more room, and the distance reduces the speed at which information can be accessed.

To address these issues, CEA-Leti hasdeveloped a quantum computing technology that combines qubits with traditional digital and analog circuitry on the same piece of silicon using standard manufacturing techniques.

The 28 nm FD-SOI process combines nA current-sensing analog circuitry, buffers, multiplexers, oscillators, and signal amplifiers with an on-chip double quantum dot whose operation is not affectedeven when using the traditional circuitry at digital frequencies up to 7 GHz and analog frequencies up to 3 GHz.

The IC, which operates at 110 mK, is able to provide nA current-sensing while operating on a power budget to prevent interference with the quantum dots, which is 40 times lower than competing technologies.

As the number of transistors on a chip increases, the chances of one failing also increases, thusdecreasingthe yield of wafers. One workaround is to make chips smaller and include fewer transistorswhile also connecting multiple chips together, thus increasingthe overall transistor count.

However, PCBs have issues with connecting multiple dies together. These issues may involve limited bandwidth and the inability to integrate other active circuitry required by the dies, such as power regulation.

CEA-Leti hasmade a breakthrough in IC technology with its active interposer layer and 3D stacked chips.

Namely, the team has developed a 96-core processor on six chiplets, 3D stacked on an active interposer.

Just like the PCB topology, CEA-Leti uses a layer with metal interconnects that connect different dies on a single base. Butunlike a PCB, the interconnection layer is a piece of semiconductor only 100 m thick.

What makes the interposer more impressive is that it isactive. It alsohas integrated circuitry, including transistors. Therefore, the interposer can integrate power regulators, multiplexers, and digital processors, meaningthat the diesdirectly attached to the imposers operate at high-speeds. They alsohave all their needed handling circuitry next to them.

The use of the active imposer also means that smaller ICs with reduced transistor counts can be combined to produce complex circuitry.This improves wafer yields, reduces their overall cost, and expands their capabilities.

These three technologies coming out of CEA-Leti give us a glimpse intoa future where ICs may generate their own power oreven be able to integrate quantum circuitry.

The energy harvesting technology may struggle to find its way into modern designs because most portable applications require relatively large amounts of power (compared to 1 mW) and these devices are often stationary.

The use of quantum circuitry with traditional construction techniques means that quantum security (which may become essential) can be integrated into everyday devicessuch as smartphones, tablets, and computers. Until quantum computing becomes commercial, though, this technology will likely remain niche.

Technologies such as the active imposer may be the first technology of the three discussed here to become widespread as it easily solves modern transistor reduction-related issues.

Is there a specific functionality you can't seem to find in an IC? What limitations do you feel are keeping researchers from making your "dream" IC breakthrough? Share your thoughts in the comments below.

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IC Breakthroughs: Energy Harvesting, Quantum Computing, and a 96-Core Processor in Six Chiplets - News - All About Circuits

MIT is no stranger to technology. It's one of the world's most productive and forward-facing tech research organizations. So when MIT gets excited looking forward, it only makes sense to sneak a peak at what they're seeing. MIT recently just published their top 10 technological breakthroughs for 2020 and just beyond. Below are the first five on their list. Each one is an advance that MIT sees as genuinely changing our lives.

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MIT says: Later this year, Dutch researchers will complete a quantum internet between Delft and the Hague.

Think of a coin. Lay it flat on a table, and it's either heads and tails. This is more or less how things work in the world at larger scales. To see what things are like at a much smaller, quantum size, spin the coin on the table and observe it from above. From our perspective, the coin's state could then be described as being both head and tails at the same time since it's neither one exactly. Being in this rapidly changing condition is like being in "superposition" in quantum physics.

To see, or measure, the coin's head/tails state at any given moment, you'd have to stop it spinning, perhaps flattening it down to the table, where it would be stopped as either head or tails. Thus measured, the coin would be taken it out of superposition. Just like entangled quantum particles.

In classical computing system, data objects are represented by bits, strings of data comprised of zeros and ones, AKA heads or tails. In the quantum world, however, what needs to be represented is that "spinning coin"of superposition in its as-yet-unresolved state. So quantum computing uses "qubits" instead of bits.

Obviously, being able to represent data with qubits objects that collapse out of superposition if they're intercepted or tampered with is an attractive prospect for an increasingly security-conscious world, a natural foundation on which to build a super-secure quantum internet.

Still, qubits are far more complex than bits, and thus harder to process and exchange. Even worse, as our spinning coin will eventually stop spinning and resolve as heads or tails (Inception aside), qubits lose their superimposition after a while, making retaining and exchanging them in a superimposed a serious challenge. While there are various combinations of classical and quantum internets and encryption keys under consideration and construction, they all share a need for the robust, accurate transmission of qubits over long distances.

Now scientists of the Quantum Internet Alliance initiative have announced that they're in the process of building the world's first purely quantum network. It incorporates new quantum repeaters that allow qubits to be passed along long distances without being corrupted or losing their superposition. The group published a paper last October laying out their vision for an Arpanet-type quantum prototype stretching between Delft and the Hague by the end of this decade. (Here's a great explainer.)

Stephanie Wehner of QuTech, a quantum computing and internet center at Delft University of Technology, is coordinator of the project:

"With this very extensive simulation platform we've recently built, which is now running on a supercomputer, we can explore different quantum network configurations and gain an understanding of properties which are very difficult to predict analytically. This way we hope to find a scalable design that can enable quantum communication across all of Europe."

Image source: National Cancer Institute/unsplash

MIT says: Novel drugs are being designed to treat unique genetic mutations.

Developing treatments for any condition can be difficult and expensive, and it behooves researchers to get the most bang for their buck by concentrating on formulating solutions for diseases that afflict large groups of people. Hand in hand with this is a need for generalized remedies that address characteristics the whole group shares.

This is changing, says MIT, with gene editing offering the potential for transforming medicine from the traditional "one size fits all" approach to a more effective, personalized, or "n-of-1," approach. This new form of medicine involves targeting and manipulation of an individual patient's genes, with the application of rapidly maturing technologies for gene replacement including gene editing, and antisensing that removes or corrects problem-causing genetic messages. "What the treatments have in common," says MIT, "is that they can be programmed, in digital fashion and with digital speed, to correct or compensate for inherited diseases, letter for DNA letter." Treatments may also individually be optimized to avoid contemporary medicine's often harsh side effects.

If gene editing lives up to its promise, medicine is about to become radically more successful and humane.

Image source: Artwell/Shutterstock

MIT says: The rise of digital currency has massive ramifications for financial privacy.

While Bitcoin is, as of this writing, collapsing, it's nonetheless clear that purely digital monetary systems have considerable appeal: No more germ-encrusted metal and paper money, and, perhaps more importantly, an opportunity for governments and their central banks to more closely control currency and to instantly execute monetary policy changes.

The truth is we've been halfway there for a long time, currencies such as Bitcoin and Libra notwithstanding. The money in our bank accounts is virtual we personally possess no plies of physical cash at our local bank. Electronic purchasing with credit and debit cards is the norm for most of us, and when large movements of cash occur between banks, they do so in the digital domain. It's all been mostly bytes and bits for some time. What we currently have is a mish-mash of physical and digital money, and MIT predicts the imminent arrival of purely digital monetary systems. (Buh-bye, folding money and pocket change.)

In 2014, China began quietly exploring and building their Digital Currency/Electronic Payments system, or DC/EP. According to OZY, they've already applied for 84 patents for various innovations their new system requires.

One of China's goals is to construct an on-ramp making it easy for citizens to switch to an all-digital system. "Virtually all of these patent applications," Marc Kaufman of Rimon Law, tells OZY, "relate to integrating a system of digital currency into the existing banking infrastructure." The country's developing systems that allow people to swap traditional money for digital currency, as well chip card and digital wallets from which the currency may be spent.

Clearly, an all-digital monetary system presents privacy issues, since all of one's money would presumably be visible to governmental agencies unless adequate privacy protections are implemented. Developing that protection is going to require a deeper exploration of privacy itself, a discussion that has been overdue since the dawn of the internet.

Image source: Halfpoint/Shutterstock

MIT says: Drugs that try to treat ailments by targeting a natural aging process in the body have shown promise.

Strides are being made toward the production of new drugs for conditions that commonly accompany getting older. They don't stop the aging process, but the hope is that in the next five years, scientists may be able to delay some of aging's effects.

Senolytics are a new form of drugs under development that are designed to clean out unwanted stuff that often accumulates in us as we age. These senescent cells can wind up as plaque on brain cells, and as deposits that cause inflammation inhibiting healthy cell maintenance, and leaving toxins in our bodies.

While trials by San Franciscobased Unity Biotechnology are now underway for a senolytic medication targeting osteoarthritis of the knee, MIT notes that other aging-related ailments are getting a promising fresh look as well. For example, one company, Alkahest, specializing in Parkinson's and dementia, is investigating the extraction of certain components of young people's blood for injection into Alzheimer's patients in the hopes of arresting cognitive and functional decline (Oh, hi, Keith Richards.). And researchers at Drexel University College of Medicine are investigating the use of an existing drug, rapamycin, as an anti-aging skin creme.

Image source: Sharon Pittaway/unsplash

MIT says: Scientists have used AI to discover promising drug-like compounds.

Drugs are built from compounds, combinations of molecules that together produce some sort of medically useful effect. Scientists often find that known compounds can have surprising medical value recent research found that 50 non-cancer drugs can fight cancer in addition to their previously known uses.

But what about new compounds? MIT notes there may be as many as 1060 molecule combinations yet to be discovered, "more than all the atoms in the solar system."

AI can help. It can sift through molecule properties recorded in existing databases to identify combinations that may have promise as drugs. Operating much more quickly and inexpensive than humans can, machine learning techniques may revolutionize the search for new medicines.

Researchers at Hong Kongbased Insilico Medicine and the University of Toronto announced last September that AI algorithms had picked out about 30,000 unexplored molecule combinations, eventually winnowing that list down to six especially promising new medical compounds. Synthesis and subsequent animal testing revealed one of them to be especially interesting as a drug. One out of six out of 30,000 may not seem that impressive, but AI and machine learning are quickly evolving.

MIT predicts that in 3-5 years, such investigations will be regularly bearing fruit.

The other five items on MIT's list are:

6. Satellite mega-constellations7. Quantum supremacy8. Tiny AI9. Differential privacy10. Climate change attribution

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Excerpt from:

MITs Top 5 tech breakthroughs for 2020 - Big Think

COMPUTING

Inside the Race to Build the Best Quantum Computer on EarthGideon Lichfield | MIT Technology ReviewRegardless of whether you agree with Googles position [on quantum supremacy] or IBMs, the next goal is clear, Oliver says: to build a quantum computer that can do something useful. The trouble is that its nearly impossible to predict what the first useful task will be, or how big a computer will be needed to perform it.

Were Not Prepared for the End of Moores LawDavid Rotman | MIT Technology ReviewQuantum computing, carbon nanotube transistors, even spintronics, are enticing possibilitiesbut none are obvious replacements for the promise that Gordon Moore first saw in a simple integrated circuit. We need the research investments now to find out, though. Because one prediction is pretty much certain to come true: were always going to want more computing power.

Flippy the Burger-Flipping Robot Is Changing the Face of Fast Food as We Know ItLuke Dormehl | Digital TrendsFlippy is the result of the Miso teams robotics expertise, coupled with that industry-specific knowledge. Its a burger-flipping robot arm thats equipped with both thermal and regular vision, which grills burgers to order while also advising human collaborators in the kitchen when they need to add cheese or prep buns for serving.

The Next Generation of Batteries Could Be Built by VirusesDaniel Oberhaus | Wired[MIT bioengineering professor Angela Belcher has] made viruses that can work with over 150 different materials and demonstrated that her technique can be used to manufacture other materials like solar cells. Belchers dream of zipping around in a virus-powered car still hasnt come true, but after years of work she and her colleagues at MIT are on the cusp of taking the technology out of the lab and into the real world.

Biggest Cosmic Explosion Ever Detected Left Huge Dent in SpaceHannah Devlin | The GuardianThe biggest cosmic explosion on record has been detectedan event so powerful that it punched a dent the size of 15 Milky Ways in the surrounding space. The eruption is thought to have originated at a supermassive black hole in the Ophiuchus galaxy cluster, which is about 390 million light years from Earth.

Star Treks Warp Speed Would Have Tragic ConsequencesCassidy Ward | SyFyThe various crews ofTreks slate of television shows and movies can get from here to there without much fanfare. Seeking out new worlds and new civilizations is no more difficult than gassing up the car and packing a cooler full of junk food. And they dont even need to do that! The replicators will crank out a bologna sandwich just like mom used to make. All thats left is to go, but what happens then?

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This Week's Awesome Tech Stories From Around the Web (Through February 29) - Singularity Hub