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#431155 What It Will Take for Quantum Computers ...
Quantum computers could give the machine learning algorithms at the heart of modern artificial intelligence a dramatic speed up, but how far off are we? An international group of researchers has outlined the barriers that still need to be overcome.
This year has seen a surge of interest in quantum computing, driven in part by Google’s announcement that it will demonstrate “quantum supremacy” by the end of 2017. That means solving a problem beyond the capabilities of normal computers, which the company predicts will take 49 qubits—the quantum computing equivalent of bits.
As impressive as such a feat would be, the demonstration is likely to be on an esoteric problem that stacks the odds heavily in the quantum processor’s favor, and getting quantum computers to carry out practically useful calculations will take a lot more work.
But these devices hold great promise for solving problems in fields as diverse as cryptography or weather forecasting. One application people are particularly excited about is whether they could be used to supercharge the machine learning algorithms already transforming the modern world.
The potential is summarized in a recent review paper in the journal Nature written by a group of experts from the emerging field of quantum machine learning.
“Classical machine learning methods such as deep neural networks frequently have the feature that they can both recognize statistical patterns in data and produce data that possess the same statistical patterns: they recognize the patterns that they produce,” they write.
“This observation suggests the following hope. If small quantum information processors can produce statistical patterns that are computationally difficult for a classical computer to produce, then perhaps they can also recognize patterns that are equally difficult to recognize classically.”
Because of the way quantum computers work—taking advantage of strange quantum mechanical effects like entanglement and superposition—algorithms running on them should in principle be able to solve problems much faster than the best known classical algorithms, a phenomenon known as quantum speedup.
Designing these algorithms is tricky work, but the authors of the review note that there has been significant progress in recent years. They highlight multiple quantum algorithms exhibiting quantum speedup that could act as subroutines, or building blocks, for quantum machine learning programs.
We still don’t have the hardware to implement these algorithms, but according to the researchers the challenge is a technical one and clear paths to overcoming them exist. More challenging, they say, are four fundamental conceptual problems that could limit the applicability of quantum machine learning.
The first two are the input and output problems. Quantum computers, unsurprisingly, deal with quantum data, but the majority of the problems humans want to solve relate to the classical world. Translating significant amounts of classical data into the quantum systems can take so much time it can cancel out the benefits of the faster processing speeds, and the same is true of reading out the solution at the end.
The input problem could be mitigated to some extent by the development of quantum random access memory (qRAM)—the equivalent to RAM in a conventional computer used to provide the machine with quick access to its working memory. A qRAM can be configured to store classical data but allow the quantum computers to access all that information simultaneously as a superposition, which is required for a variety of quantum algorithms. But the authors note this is still a considerable engineering challenge and may not be sustainable for big data problems.
Closely related to the input/output problem is the costing problem. At present, the authors say very little is known about how many gates—or operations—a quantum machine learning algorithm will require to solve a given problem when operated on real-world devices. It’s expected that on highly complex problems they will offer considerable improvements over classical computers, but it’s not clear how big problems have to be before this becomes apparent.
Finally, whether or when these advantages kick in may be hard to prove, something the authors call the benchmarking problem. Claiming that a quantum algorithm can outperform any classical machine learning approach requires extensive testing against these other techniques that may not be feasible.
They suggest that this could be sidestepped by lowering the standards quantum machine learning algorithms are currently held to. This makes sense, as it doesn’t really matter whether an algorithm is intrinsically faster than all possible classical ones, as long as it’s faster than all the existing ones.
Another way of avoiding some of these problems is to apply these techniques directly to quantum data, the actual states generated by quantum systems and processes. The authors say this is probably the most promising near-term application for quantum machine learning and has the added benefit that any insights can be fed back into the design of better hardware.
“This would enable a virtuous cycle of innovation similar to that which occurred in classical computing, wherein each generation of processors is then leveraged to design the next-generation processors,” they conclude.
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Posted in Human Robots
#431023 Finish Him! MegaBots’ Giant Robot Duel ...
It began two years ago when MegaBots co-founders Matt Oehrlein and Gui Cavalcanti donned American flags as capes and challenged Suidobashi Heavy Industries to a giant robot duel in a YouTube video that immediately went viral.
The battle proposed: MegaBots’ 15-foot tall, 1,200-pound MK2 robot vs. Suidobashi’s 9,000-pound robot, KURATAS. Oehrlein and Cavalcanti first discovered the KURATAS robot in a listing on Amazon with a million-dollar price tag.
In an equally flamboyant response video, Suidobashi CEO and founder Kogoro Kurata accepted the challenge. (Yes, he named his robot after himself.) Both parties planned to take a year to prepare their robots for combat.
In the end, it took twice the amount of time. Nonetheless, the battle is going down this September in an undisclosed location.
Oehrlein shared more about the much-anticipated showdown during our interview at Singularity University’s Global Summit.
Two years since the initial video, MegaBots has now completed the combat-capable MK3 robot, named Eagle Prime. This new 12-ton, 16-foot-tall robot is powered by a 430-horsepower Corvette engine and requires two human pilots.
It’s also the robot they recently shipped to take on KURATAS.
Building Eagle Prime has been no small feat. With arms and legs that each weigh as much as a car, assembling the robot takes forklifts, cranes, and a lot of caution. Fortress One, MegaBots’ headquarters in Hayward, California is where the magic happens.
In terms of “weaponry,” Eagle Prime features a giant pneumatic cannon that shoots huge paint cannonballs. Oehrlein warns, “They can shatter all the windows in a car. It’s very powerful.” A logging grapple, which looks like a giant claw and exerts 3,000 pounds of steel-crushing force, has also been added to the robot.
“It’s a combination of range combat, using the paint balls to maybe blind cameras on the other robot or take out sensitive electronics, and then closing in with the claw and trying to disable their systems at close range,” Oehrlein explains.
Safety systems include a cockpit roll cage for the two pilots, five-point safety seatbelt harnesses, neck restraints, helmets, and flame retardant suits.
Co-founder, Matt Oehrlein, inside the cockpit of MegaBots’ Eagle Prime giant robot.
Oehrlein and Cavalcanti have also spent considerable time inside Eagle Prime practicing battlefield tactics and maneuvering the robot through obstacle courses.
Suidobashi’s robot is a bit shorter and lighter, but also a little faster, so the battle dynamics should be interesting.
You may be thinking, “Why giant dueling robots?”
MegaBots’ grand vision is a full-blown international sports league of giant fighting robots on the scale of Formula One racing. Picture a nostalgic evening sipping a beer (or three) and watching Pacific Rim- and Power Rangers-inspired robots battle—only in real life.
Eagle Prime is, in good humor, a proudly patriotic robot.
“Japan is known as a robotic powerhouse,” says Oehrlein, “I think there’s something interesting about the slightly overconfident American trying to get a foothold in the robotics space and doing it by building a bigger, louder, heavier robot, in true American fashion.”
For safety reasons, no fans will be admitted during the time of the fight. The battle will be posted after the fact on MegaBots’ YouTube channel and Facebook page.
We’ll soon find out whether this becomes another American underdog story.
In the meantime, I give my loyalty to MegaBots, and in the words of Mortal Kombat, say, “Finish him!”
via GIPHY
Image Credit: MegaBots Continue reading
Posted in Human Robots
#431015 Finish Him! MegaBots’ Giant Robot Duel ...
It began two years ago when MegaBots co-founders Matt Oehrlein and Gui Cavalcanti donned American flags as capes and challenged Suidobashi Heavy Industries to a giant robot duel in a YouTube video that immediately went viral.
The battle proposed: MegaBots’ 15-foot tall, 1,200-pound MK2 robot vs. Suidobashi’s 9,000-pound robot, KURATAS. Oehrlein and Cavalcanti first discovered the KURATAS robot in a listing on Amazon with a million-dollar price tag.
In an equally flamboyant response video, Suidobashi CEO and founder Kogoro Kurata accepted the challenge. (Yes, he named his robot after himself.) Both parties planned to take a year to prepare their robots for combat.
In the end, it took twice the amount of time. Nonetheless, the battle is going down this September in an undisclosed location in Japan.
Oehrlein shared more about the much-anticipated showdown during our interview at Singularity University’s Global Summit.
Two years since the initial video, MegaBots has now completed the combat-capable MK3 robot, named Eagle Prime. This new 12-ton, 16-foot-tall robot is powered by a 430-horsepower Corvette engine and requires two human pilots.
It’s also the robot they recently shipped to Japan to take on KURATAS.
Building Eagle Prime has been no small feat. With arms and legs that each weigh as much as a car, assembling the robot takes forklifts, cranes, and a lot of caution. Fortress One, MegaBots’ headquarters in Hayward, California is where the magic happens.
In terms of “weaponry,” Eagle Prime features a giant pneumatic cannon that shoots huge paint cannonballs. Oehrlein warns, “They can shatter all the windows in a car. It’s very powerful.” A logging grapple, which looks like a giant claw and exerts 3,000 pounds of steel-crushing force, has also been added to the robot.
“It’s a combination of range combat, using the paint balls to maybe blind cameras on the other robot or take out sensitive electronics, and then closing in with the claw and trying to disable their systems at close range,” Oehrlein explains.
Safety systems include a cockpit roll cage for the two pilots, five-point safety seatbelt harnesses, neck restraints, helmets, and flame retardant suits.
Co-founder, Matt Oehrlein, inside the cockpit of MegaBots’ Eagle Prime giant robot.
Oehrlein and Cavalcanti have also spent considerable time inside Eagle Prime practicing battlefield tactics and maneuvering the robot through obstacle courses.
Suidobashi’s robot is a bit shorter and lighter, but also a little faster, so the battle dynamics should be interesting.
You may be thinking, “Why giant dueling robots?”
MegaBots’ grand vision is a full-blown international sports league of giant fighting robots on the scale of Formula One racing. Picture a nostalgic evening sipping a beer (or three) and watching Pacific Rim- and Power Rangers-inspired robots battle—only in real life.
Eagle Prime is, in good humor, a proudly patriotic robot.
“Japan is known as a robotic powerhouse,” says Oehrlein, “I think there’s something interesting about the slightly overconfident American trying to get a foothold in the robotics space and doing it by building a bigger, louder, heavier robot, in true American fashion.”
For safety reasons, no fans will be admitted during the time of the fight. The battle will be posted after the fact on MegaBots’ YouTube channel and Facebook page.
We’ll soon find out whether this becomes another American underdog story.
In the meantime, I give my loyalty to MegaBots, and in the words of Mortal Kombat, say, “Finish him!”
via GIPHY
Image Credit: MegaBots Continue reading
Posted in Human Robots
#431000 Japan’s SoftBank Is Investing Billions ...
Remember the 1980s movie Brewster’s Millions, in which a minor league baseball pitcher (played by Richard Pryor) must spend $30 million in 30 days to inherit $300 million? Pryor goes on an epic spending spree for a bigger payoff down the road.
One of the world’s biggest public companies is making that film look like a weekend in the Hamptons. Japan’s SoftBank Group, led by its indefatigable CEO Masayoshi Son, is shooting to invest $100 billion over the next five years toward what the company calls the information revolution.
The newly-created SoftBank Vision Fund, with a handful of key investors, appears ready to almost single-handedly hack the technology revolution. Announced only last year, the fund had its first major close in May with $93 billion in committed capital. The rest of the money is expected to be raised this year.
The fund is unprecedented. Data firm CB Insights notes that the SoftBank Vision Fund, if and when it hits the $100 billion mark, will equal the total amount that VC-backed companies received in all of 2016—$100.8 billion across 8,372 deals globally.
The money will go toward both billion-dollar corporations and startups, with a minimum $100 million buy-in. The focus is on core technologies like artificial intelligence, robotics and the Internet of Things.
Aside from being Japan’s richest man, Son is also a futurist who has predicted the singularity, the moment in time when machines will become smarter than humans and technology will progress exponentially. Son pegs the date as 2047. He appears to be hedging that bet in the biggest way possible.
Show Me the Money
Ostensibly a telecommunications company, SoftBank Group was founded in 1981 and started investing in internet technologies by the mid-1990s. Son infamously lost about $70 billion of his own fortune after the dot-com bubble burst around 2001. The company itself has a market cap of nearly $90 billion today, about half of where it was during the heydays of the internet boom.
The ups and downs did nothing to slake the company’s thirst for technology. It has made nine acquisitions and more than 130 investments since 1995. In 2017 alone, SoftBank has poured billions into nearly 30 companies and acquired three others. Some of those investments are being transferred to the massive SoftBank Vision Fund.
SoftBank is not going it alone with the new fund. More than half of the money—$60 billion—comes via the Middle East through Saudi Arabia’s Public Investment Fund ($45 billion) and Abu Dhabi’s Mubadala Investment Company ($15 billion). Other players at the table include Apple, Qualcomm, Sharp, Foxconn, and Oracle.
During a company conference in August, Son notes the SoftBank Vision Fund is not just about making money. “We don’t just want to be an investor just for the money game,” he says through a translator. “We want to make the information revolution. To do the information revolution, you can’t do it by yourself; you need a lot of synergy.”
Off to the Races
The fund has wasted little time creating that synergy. In July, its first official investment, not surprisingly, went to a company that specializes in artificial intelligence for robots—Brain Corp. The San Diego-based startup uses AI to turn manual machines into self-driving robots that navigate their environments autonomously. The first commercial application appears to be a really smart commercial-grade version that crosses a Roomba and Zamboni.
A second investment in July was a bit more surprising. SoftBank and its fund partners led a $200 million mega-round for Plenty, an agricultural tech company that promises to reshape farming by going vertical. Using IoT sensors and machine learning, Plenty claims its urban vertical farms can produce 350 times more vegetables than a conventional farm using 1 percent of the water.
Round Two
The spending spree continued into August.
The SoftBank Vision Fund led a $1.1 billion investment into a little-known biotechnology company called Roivant Sciences that goes dumpster diving for abandoned drugs and then creates subsidiaries around each therapy. For example, Axovant Sciences is devoted to neurology while Urovant focuses on urology. TechCrunch reports that Roivant is also creating a tech-focused subsidiary, called Datavant, that will use AI for drug discovery and other healthcare initiatives, such as designing clinical trials.
The AI angle may partly explain SoftBank’s interest in backing the biggest private placement in healthcare to date.
Also in August, SoftBank Vision Fund led a mix of $2.5 billion in primary and secondary capital investments into India’s largest private company in what was touted as the largest single investment in a private Indian company. Flipkart is an e-commerce company in the mold of Amazon.
The fund tacked on a $250 million investment round in August to Kabbage, an Atlanta-based startup in the alt-lending sector for small businesses. It ended big with a $4.4 billion investment into a co-working company called WeWork.
Betterment of Humanity
And those investments only include companies that SoftBank Vision Fund has backed directly.
SoftBank the company will offer—or has already turned over—previous investments to the Vision Fund in more than a half-dozen companies. Those assets include its shares in Nvidia, which produces chips for AI applications, and its first serious foray into autonomous driving with Nauto, a California startup that uses AI and high-tech cameras to retrofit vehicles to improve driving safety. The more miles the AI logs, the more it learns about safe and unsafe driving behaviors.
Other recent acquisitions, such as Boston Dynamics, a well-known US robotics company owned briefly by Google’s parent company Alphabet, will remain under the SoftBank Group umbrella for now.
This spending spree begs the question: What is the overall vision behind the SoftBank’s relentless pursuit of technology companies? A spokesperson for SoftBank told Singularity Hub that the “common thread among all of these companies is that they are creating the foundational platforms for the next stage of the information revolution.All of the companies, he adds, share SoftBank’s criteria of working toward “the betterment of humanity.”
While the SoftBank portfolio is diverse, from agtech to fintech to biotech, it’s obvious that SoftBank is betting on technologies that will connect the world in new and amazing ways. For instance, it wrote a $1 billion check last year in support of OneWeb, which aims to launch 900 satellites to bring internet to everyone on the planet. (It will also be turned over to the SoftBank Vision Fund.)
SoftBank also led a half-billion equity investment round earlier this year in a UK company called Improbable, which employs cloud-based distributed computing to create virtual worlds for gaming. The next step for the company is massive simulations of the real world that supports simultaneous users who can experience the same environment together(and another candidate for the SoftBank Vision Fund.)
Even something as seemingly low-tech as WeWork, which provides a desk or office in locations around the world, points toward a more connected planet.
In the end, the singularity is about bringing humanity together through technology. No one said it would be easy—or cheap.
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