Drivers in 3 Stolen Teslas Lead Police on Chase Through Northern Virginia – NBC4 Washington

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Police officers chased three Tesla vehicles likely stolen from a Virginia dealership overnight Friday, ending with two drivers fleeing and another driver getting caught, police say.

Two suspects in the chase fled police and are still at-large, Fairfax County Police say.

A Fairfax County Police officer noticed a Tesla driving on Route 7 near the Beltway about 3 a.m. The lights were on and the car was sporting dealer tags, police say.

Officers tried to pull over the Tesla and a pursuit began, police say. Eventually, one of the drivers crashed on Leesburg Pike near the Beltway and ran away, police said.

The drivers of two other Teslas continued southbound on the highway and eventually left the cars near Route 236 and tried to outrun officers, police say.

A third suspect got away. Fairfax County Police say there were an unknown number of passengers in two of the cars.

One of the accused drivers, a man from Maryland, was caught, police say. That suspect allegedly lied about their age, telling police they were actually a juvenile.

Police believe the Teslas were taken from a dealership in the Tyson's Corner area, but didn't say how they could have been taken. The investigation is ongoing.

Editor's Note (Friday, May 1, 2020 at 6:51 a.m.): This story was updated after police released new information on one of the driver's ages.

Stay with News4 for more on this developing story.

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Drivers in 3 Stolen Teslas Lead Police on Chase Through Northern Virginia - NBC4 Washington

Tesla Banked On Emission Credits For Q1 Beat, But Outlook Is Tough – Trefis

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Tesla (NASDAQ:TSLA) posted a stronger than expected set of Q1 2020 results, despite the coronavirus pandemic, with revenues growing by ~32% year-over-year and adjusted profits coming in at $227 million, versus a loss of about $494 million a year ago. While the company benefited from strong deliveries of the Model 3 and a production ramp at its Shanghai factory, much of the improved profitability came from higher sales of emission credits which soared to about $354 million from an average of about $150 million over the last four quarters. If not for the spike in regulatory credit sales, Tesla would likely have barely broken even. Below, we take a look at how sales of regulatory credits have helped Tesla and why we believe the near-term outlook for the company looks quite challenging.

For more details on the outlook for Teslas revenues, view our dashboard analysisTesla Revenues: How Does TSLA Make Money?

What Are Regulatory Credits And How Do They Help Tesla?

Several U.S. states and countries have Zero Emissions Vehicle (ZEV) regulations that require that clean vehicles account for a certain mix of auto manufacturers sales each year. If automotive companies, which still largely sell internal combustion engine-based vehicles, dont meet these standards, they can buy credits from the likes of Tesla that earn credits, as they only sell electric vehicles. Although the revenues from these credits are quite volatile they are very lucrative for Tesla, as it likely incurs no direct costs to earn them. The bump in these regulatory credit sales is likely to be partly responsible for the companys automotive gross margins expanding 300 bps sequentially to 25.5%. While its possible that such credits could become more valuable in the medium term, as new emissions regulations come into play in Europe and states in the U.S. look to enforce stricter norms, the current collapse in global auto sales could hurt revenues from ZEV credits in the near-term for Tesla.

Outlook Remains Tough For Tesla In The Near-term

Tesla is likely to face significant near-term revenue pressure and the company has put its 2020 guidance on hold, due to uncertainty surrounding the coronavirus pandemic and the broader economic recovery. There is little reason for people to buy expensive cars right now and Teslas production at its Fremont facility, which accounts for about three-quarters of its annual capacity, remains suspended and theres no clarity as to when it could resume.

However, despite significant near-term headwinds, the companys stock has continued to rally, almost doubling year-to-date. The company trades at a P/S multiple of about 6x, compared to GM which trades at about 0.3x, based on trailing revenues. This means that the stock has significant valuation risk, making it react more strongly to negative news compared to its peers.

Our theme Autos Fight COVID-19 contrasts the performance of Tesla stock, which is up almost 90% YTD, with mainstream automakers, who have seen their stocks fall by about 40%.

See allTrefis Price EstimatesandDownloadTrefis Datahere

Whats behind Trefis? See How Its Powering New Collaboration and What-Ifs ForCFOs and Finance Teams|Product, R&D, and Marketing Teams

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Tesla Banked On Emission Credits For Q1 Beat, But Outlook Is Tough - Trefis

Former Tesla and Lyft exec Jon McNeill just launched a fund that plans to spin out its own companies – TechCrunch

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Lyfts former COO Jon McNeill has had a fairly storied career as an operator. A Northwestern University economics major who worked at Bain & Co. out of college, he went on to start and sell five companies before being introduced in 2015 to Elon Musk by Sheryl Sandberg and spending 2.5 years as Teslas president of global sales and service.

He was apparently so good at his job that Lyfts investors asked him to join the car-share company to assist it. There, he helped build up the companys management team, got it through its public offering, then decamped last year roughly four months after its IPO and just 18 months after hed joined.

At the time, the move left some shareholders scratching their heads. It also drove down the price of Lyfts shares. Now, McNeill says he had too many ideas percolating to stay. He has so many, in fact, that he just cofounded a business that will launch other businesses.

Its called DeltaV an engineering term for a change in velocity and the idea is to formulate startup ideas, get them up and running, then when theyre at the Series B phase of life, seek outside funding, while hanging on to roughly 80 percent of each company.

Its a tall order, but McNeill thinks he has the team to do it.

Along with McNeill, DeltaV was founded by Karim Bousta, who spent eight years with GE before joining Symantec as a vice president, where McNeill lured him away to Tesla, then brought him to Lyft as its VP and head of operations. (Bousta has also been working in recent months as an operating partner with SoftBank Investment Advisors.)

DeltaV also counts as a cofounder Sami Shalabi, who spent nearly a dozen years as a top engineer at Google after it acquired a company he cofounded called Zingku; Michael Rossiter, a business operations exec who, like Bousta, worked with McNeill at both Tesla and Lyft; and Henry Vogel, who has cofounded a number of companies and was among the first partners at BCG Digital Ventures, the corporate investment firm. (Vogel was also McNeills roommate when the two were college freshmen.)

As important, McNeill also thinks DeltaV has the structure needed to pursue the founders collective vision of investing in fewer companies that they themselves start and grow. Specifically, the five have rounded up $40 million from a dozen investors mostly family offices for an evergreen fund. What that means: investors are committing to allow them to recycle capital, rather than aim to return it after a certain window of time. (Most traditional venture funds, for example, have a 10-year-long investment period.)

Evergreen funds have never gained much traction in the venture world, even while or because they alleviate expensive management fees. Still, there are precedents for what DeltaV is trying to do and, in fact, McNeil volunteers that they largely inspired what the team has built. Indeed, after spending time with tens of accelerators, incubators, and startup studios, McNeil says he walked away the most impressed with what two firms have created: Sutter Hill Ventures in the Bay Area and Flagship Pioneering in Cambridge, Mass.

Both operate evergreen funds, and both have enviable track records. Since its 2000 founding, Flagship Pioneering has formed and spun out 75 companies and 22 of them have gone public since 2013 alone, McNeill notes. Meanwhile, Sutter Hilll a much older outfit that also sources ideas internally, then tests them against the marketplace with the help of roughly 40 in-house engineers has founded 50 companies, at least 18 of which have gone public. (The cloud-based data warehouse company Snowflake may be Sutter Hills next big win. It was valued at $12.4 billion when it most recently raised a round in February, and its CEO, Frank Slootman, suggested then that the companys next financing event would likely be an IPO.)

We dont know the ins and outs of how Flagship or Sutter Hill are structured, and it wasnt McNeills place to tell us.

But for its part, DeltaV doesnt collect fees. Instead, its investors own a stake of the company, alongside the founders.

Further, while evergreen funds often provide limited partners with the ability to exit or change their investment in the fund every four years or so, DeltaV doesnt restrict them at all. Investors instead have board representation and will have a say in how much is recycled versus distributed, and can distribute or shares driven by their needs, without any set windows.

Whether the arrangement proves lucrative for everyone will take years to know, of course. Our sense of things is that DeltaV itself aims to become a public company at some point.

In the meantime, it already has four startups in the works, including one that should be out of stealth mode by early summer and another that the firm hopes to introduce to the world this fall.

The first is a pricing and profit optimization service that aims to help e-commerce players better compete with Amazon. The other is an automotive service business. McNeill wouldnt share more than that right now, though he adds that a separate idea one that revolved around the gig economy and the future of work has been shelved for the time being, given the impacts of the coronavirus

It begs the question of why McNeill thinks right now is a good time to start DeltaV. He laughed when we asked about this earlier today, acknowledging that our national state of affairs wasnt something that many anticipated. In fact, he and his cofounders firmed up their plans just in January and hit the fundraising trail roughly five weeks ago, just as the United States began to come apart at the seams.

Even so, while the coronavirus has forced the team to change some of their priorities in terms of the companies that Delta V eventually hopes to launch, McNeill believes in the old adage that theres no time to start a company like during a major downturn. As he told us on a call, Were actually accelerating a bit in terms of making much more forward progress, particularly where it concerns the firms profit-optimization startup.

As McNeill explained it, he and his cofounders want to make this a very long-term, durable business. We want to create dozens of companies over time. Theyre all operators who know a thing or two about repeatable processes, he added. Now, he said, theyve just codified what theyve been doing all along.

If youre curious to learn more, McNeill has just written a bit more about starting DeltaV here.

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Former Tesla and Lyft exec Jon McNeill just launched a fund that plans to spin out its own companies - TechCrunch

Tesla Posts a 1Q Profit for the First Time – Morningstar.com

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Tesla (TSLA) reported a record first quarter, and we calculate adjusted diluted EPS of $1.14 compared with first-quarter 2019 EPS of negative $2.90. We expect large upward stock moves for Tesla in May as results crushed the Refinitiv EPS consensus of a loss of $0.36. We also expect second quarter will suffer from the firms main plant in California being shutdown since late March, but once COVID-19 restrictions are lifted, we expect Tesla to fill a large number of orders which are still coming in online. We understand given COVID-19 uncertainty that management cannot give 2020 delivery guidance, but we like that Tesla continues to invest without slowing as evidenced by the Shanghai Model Y plant and Gigafactory Berlin both due to start production next year.

We regret nearly halving our fair value estimate on March 18, partly based on a higher weighted average cost of capital due to Teslas 2025 bond yield exceeding 10%, because, in hindsight, that is the same time the bond yield peaked. Even a pandemic causes no fear for the market with this stock, and we're lowering our WACC to about 8.8% from 12%. We're also raising our midcycle operating margin back to 11% and raising deliveries over our 10-year forecast period because we think Tesla will continue to provide formidable competition to premium automakers and have a million units of capacity by the end of 2021. These changes mean we are increasing our fair value estimate to about $731 from $239. If a recession cant stop Tesla then virtually nothing will, and we expect the company to remain a leader in autonomous technology and range. Tesla is also gaining scale and its ability to make desirable vehicles while generating free cash flow and net profit is far better than its ever been. For the quarter, free cash flow was negative $895 million but this was mostly for inventory increases which we expect will become a free cash flow benefit once vehicles being held at the end of first quarter get delivered next quarter.

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Nio Is Looking to Catch Up With Tesla in China – Investorplace.com

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When regulators halted trading on China-based firm Luckin Coffee (NASDAQ:LK), investors sent Nio (NYSE:NIO) stock lower. Yet the fraud by Luckin is a company-specific problem. Nio is in far better shape.

The company posted March delivery numbers that showed a rebound of demand for its vehicles in China. The improving fundamentals suggest that Nio stock may start building on its uptrend that started in early April.

Source: THINK A / Shutterstock.com

Nio posted a 117% month-over-month increase in vehicle deliveries in March. The companys production capacity rebounded, helping its deliveries top 1,533 vehicles in March. That consisted of 1,479 5-seater ES6 SUVs and 54 of the 7-seater ES8s SUVs.

In April, Nio will start delivering an all-new ES8 that has over 180 improvements. Nios CEO, chairman and founder William Bin Li said that in parallel with our continued online sales efforts, our in-store visits have also witnessed a gradual pickup. With the continuous support from our loyal user community, we have seen increasing order backlog since February.

China is still slowly re-opening businesses and returning to normal life after the shutdown caused by the Covid-19 outbreak. As consumers become more upbeat and they become comfortable with buying either online or in offline sales channels, expect Nios growth to accelerate.

China has the largest electric vehicle market in the world and is looking to support Nio. But the company has plenty of work ahead of it.

On April 7, Nio reported that it had delivered a combined 3,838 ES6 and ES8 vehicles in Q1, about 10% above the midpoint of its prior guidance.

But Nio has said it expected many challenges to confront China and the global economy, which will have an impact on the auto industry in the country. Nio, however, believes it will stand out from the competition.

Teslas (NASDAQ:TSLA) 11,280 vehicle sales easily outpaced Nios ES6 sales. So, to catch up, Nio will need to offer features that are on par with that of Tesla. Nio announced two driver assistance features for the ES6 and ES8 models. Navigation On Pilot will allow the vehicle to drive on and off ramp, overtake, merge lanes and cruise according to planned routes.

Self Automatic Parking Assist with Fusion uses surround-view cameras and ultrasonic radars. When active, it will detect parking spots by seeing parking space lines. It will then search for, detect, and choose parking spots.

Nio said it would increase the ES8s range. And in September, it will start delivering the EC6, a smart electric Coupe SUV.

Nio has focused on two growth drivers. First, it will continue seeking to expand its sales network. Having more dealerships will weigh on its costs. But the 200 dealerships it plans to add by the end of 2020 will support its sales growth. Second, Nio relies on users referrals to support its sales growth. As long as customers are satisfied and Nio keeps adding features they need, management expects users referrals to increase.

Nios minimal gross margin increase, despite higher sequential sales volume, is a concern. Sales of the base version of its ES6 vehicle lowered its average selling price. Since its ES8 sales did not increase, its gross margin did not rise by much. If the companys sales mix changes for the better, so will Nios margins.

Investors who forecast a perpetuity growth rate of only 1.5% and use a five-year discounted cash flow growth exit model will assign Nio stock a value of $3.40 (click on this link to test different assumptions on finbox.io). That is in-line with the average analyst price target of $3.50 per share.

ChrisLau is acontributing author for InvestorPlace.com and numerous other financial sites. Chris has over 20 years of investing experience in the stock market and runs the Do-It-Yourself Value Investing Marketplace on Seeking Alpha. He shares his stock picks so readers get original insight that helps improve investment returns.As of this writing, the author did not hold a position in any of the aforementioned securities.

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Nio Is Looking to Catch Up With Tesla in China - Investorplace.com

Why Tesla Stock Bulls Are About to Get Absolutely Wrecked – CCN.com

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Tesla stock (NASDAQ:TSLA) was tops in the NASDAQ on Monday. Shares in the electric carmaker soared 10.15% to close the session at $798.75.

The reason for the surge? Over the weekend, Bloomberg reported Tesla will reopen its Fremont factory as soon as this week. (Those plans were canceled after todays closing bell.)

Tesla bulls are also anticipating a glowing first-quarter earnings report.

Tesla stock charted a remarkable rally since announcing first-quarter deliveries on April 2. The company delivered 88,400 vehicles in the quarter ending March 31.

It was a record-breaking first quarter for the company. By contrast, Teslas second-best Q1 saw 63,000 deliveries in 2019.

That is impressive year-over-year quarterly growth amid the coronavirus pandemic and worst economic crash in living memory. Especially so considering how hard coronavirus hit China and the importance of the Chinese market to Teslas growth.

This growth sent the companys shares soaring an incredible 79% from an April 2 low of $446.40 to Mondays high of $799.49.

But Tesla stock bulls are about to bust their faces when this bubble pops.

Among investors, there is a persistent impression of Tesla as a Silicon Valley software company disguised as a car company. In February, CNBCs Jim Cramer joined Squawk Box to say:

I just think its a technology company. You gotta value it as a technology company now that it has earnings.

It was hardly a new way to look at Tesla. At this point, its a trope.

In May last year, Forbes ran the headline:

Why Tesla is Not a Car Company and What You Can Learn From Elon Musk

That explains its wild valuations. Tech companies often trade at high P/E ratios and price-to-book ratios. Thats because they burn through an enormous amount of capital to reach scale.

Once they do, the successful ones reap enormous, monopolistic profits from total market dominance and softwares negligible cost of distribution.

But Tesla is not a software company.

Tesla stock is perilously overvalued. Unlike tech companies that create and distribute software applications, Tesla sells automobiles. Theres no way around that fact. Its revenue comes almost exclusively from vehicle sales.

Its cost structure is essentially different from that of tech companies. Tesla must burn through an enormous amount of cash to make cars. And it always will to operate its business.

That includes both massive fixed cost overlays and marginal costs per car that are fundamentally different from the software business.

While its easy to get confused because Teslas are innovative all-electric vehicles and do use cutting-edge, proprietary software present valuations arent on the money.

Before the coronavirus pandemic tanked Tesla stock with the rest of equities, it was already dangerously overvalued. In January, its earnings to value ratio was nearly 10 times that of other carmakers. But TSLA just kept rallying into the stratosphere.

By February, Barclays auto analyst Brian Johnson told investors:

Not to sound like an Ok, Boomer to the younger investors rushing into TSLA share, but the recent price action brings to mind NASDAQ c. 1999 We continue to believe TSLA is fundamentally overvalued

This side of the global economy crashing, TSLA is trading nearly as high as it was the day Johnson issued his warning about Tesla to investors.

When this stock reverts to its mean long-run value, itll be a feast for the notorious short-sellers and famine for Tesla bulls.

Disclaimer: The opinions expressed in this article do not necessarily reflect the views of CCN.com. The above should not be considered investment advice from CCN.com. The author holds no investment position in TSLA as of the time of writing.

This article was edited by Josiah Wilmoth.

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Why Tesla Stock Bulls Are About to Get Absolutely Wrecked - CCN.com

Teslas Salvaged Vehicles: The Red-Headed Stepchild – Teslarati

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Teslas salvaged vehicles make for an excellent project for rebuilders, or a chance to have an industry-leading electric car for a discounted price. Some members of the community have even made the act of rebuilding wrecked or damaged Teslas a career, like Rich Rebuilds, who runs a prominent YouTube channel. However, Tesla stopped allowing Supercharging on their salvaged vehicles in February 2020. This move ended fast charging capabilities for the owners of wrecked and refurbished Teslas, but now rebuilders are reporting that the electric vehicle company is taking away more functions.

We received a tip from a Tesla salvager who says the company is now refusing to update ownership records, nor will it activate the smartphone application, which enables some functions for the electric vehicle in question. However, Tesla has a reason for doing this, and it has to do with revenue and passenger safety, which is something the company is under a microscope for from its harshest critics.

But the real reason we are talking about it this week is because there is a valid argument for both points of view, and both should be examined in an open platform. When you decide which side you are on, please e-mail me and let me know your thoughts.

First, lets look at the side of the salvagers. They have a few main points on why taking away vehicle privileges is wrong. One issue is the fact that salvaged Teslas, if not repaired and resold, will end up sitting in a landfill for basically the remainder of the time.

It is a shame that a car that is capable of repair could end up in a landfill to sit and rot away for the rest of time. Not only is it a waste of space, but its a waste of a perfectly good high-performance vehicle. Not to mention, project cars are a hobby and a career for some. Eliminating the possibility of preparing or working on a Tesla electric vehicle to bring it back to life reduces the industry of bringing the cars back to life.

Next, the revitalization of these salvaged vehicles creates an opportunity for a more affordable Tesla ownership experience for some. Rebuilding vehicles creates profit for the person responsible for bringing the car back to a driveable state. At the same time, the owner can sometimes receive a discounted price on a perfectly drivable vehicle that could have low miles.

The industry of rebuilding crashed, or damaged cars are advantageous for multiple parties financially. The issue is the cars are not always repaired by mechanics properly, which can lead to quality and safety issues down the line. However, this could be another opportunity for Tesla to train salvagers, mechanics, and collision repair technicians across the world. The idea of making repair seminars or courses available for those who plan to revitalize a Tesla vehicle could lead to an influx of people who are familiar with the cars inside and out.

To the flip side, Teslas arguments are just as reliable as those of the rebuilders. Tesla has maintained a reputation for having extremely safe vehicles that are capable of saving people from severe injuries when they are involved in scary and violent accidents. When cars are damaged and end up in salvage yards, ending up in the hands of those who are interested in repairing them, they are never really the same. The most severely damaged cars can have chassis and build issues that can never be fixed fully, only masked, and pushed as close to perfect as possible. Theyll never be factory issue, and theyll never drive precisely how they would when they rolled out of a production facility. However, they can be fabricated, rewelded, and adjusted to specifications that are incredibly close to how Tesla intended them to be. But this is a case that would require the individual inspection of each repaired vehicle by a Tesla representative. With 1,000,000 Tesla vehicles manufactured in the companys history, this would be near impossible, even if .01% of them were salvaged and repaired.

The likelihood of a Tesla rep traveling to the location of a rebuilt vehicle and going through hours of inspection: making sure all parts of the car are correctly installed, properly connected, and aligned safely would not be cost-effective, smart, or worth Teslas time. However, it would be necessary. Like I said before, this company has a reputation for building safe cars. When someone in a Tesla gets in an accident, the short sellers and the Elon haters come out of the woodwork looking for answers. Why? So if someone got hurt, or heaven forbid, killed in an accident, they could use it as justification that the cars are not as safe as Tesla advertises, and somehow that means Elon is a fraud.

It is a ridiculous train of thought. Ill never understand Teslas short-sellers celebrating other peoples injuries. Instead of rooting for someone to get hurt, why not root for the company to make safer cars? It would only make other automakers want to match Teslas quality, and it wouldnt be such a horrible thing to have more safe vehicles on the road.

Regardless, Tesla has to account for the fact that if someone gets hurt in a revitalized vehicle that was formerly a salvage, it will be a never-ending storm of media harassment. I can see the misleading headlines nowDriver killed in Tesla proving cars arent so safe after all, or something to that effect. It is a risk that they simply cannot take, and it is not worth the companys future.

Additionally, Tesla makes money when they sell new cars, not when people buy wrecked ones and decide to rebuild them. Lets not forget, this is a car company, and ultimately a business. While Teslas mission is to provide people with safe and affordable electric vehicles that benefit our environment and our well-being, they need to make money.

In the end, Teslas decision, while financial, is also a safety issue. Sure, Elon would love to see some custom projects. Id bet he would like to see his cars developed into something different than what Tesla builds in their factories. But I also bet that he wouldnt want someone to get hurt or killed as a result of negligence while refurbishing a vehicle. Ultimately, it would end up being blood on his hands, and this risk makes it entirely too risky from a business standpoint.

While people are still free to rebuild the cars, they will undoubtedly run into roadblocksno Supercharging, issues with transferring ownership titles, so on and so forth. Tesla is doing it for money, but it is also doing it for safety. In the big picture, thats why I think what they are doing is okay, even though I feel for the rebuilders.

Welcome to a FREE preview of our weekly newsletter. Each week I go Beyond the News and handcraft a special edition that includes my thoughts on the biggest stories, why it matters, and how it could impact the future.

A big thanks to our long-time supporters andnew subscribers! Thank you.

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VW CEO Worried About Teslas Industry Lead In Autonomous Tech And Software – InsideEVs

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Information was obtained from a leaked internal conversation.

Its plainly obvious just by looking at what it has to offer compared to the established automakers that Tesla is ahead of them in so many fields. It not only provides the some of the quickest and longest range EVs around, but its Autopilot semi-autonomous driving tech and over the air updates have other manufacturers worried.

According to an internal document that was supposed to be secret but was obtained by Automobilwoche, none other than Herbert Diess,Volkswagens CEO, said he was worried about Teslas lead in the aforementioned fields.

The source quotes him as saying:

What worries me the most is the capabilities in the assistance systems. 500,000 Teslas work as a neural network that continuously collects data and offers the customer a new driving experience every 14 days, with improved properties. No other automobile manufacturer can do that today.

The article also says Diess wants to implement a plan to try to catch up to Tesla and minimize its lead. He is aware that VW has a long way to go before even coming close, though, not only in terms of tech but also when it comes to valuation.

Even with all its premium brands (Bentley, Porsche, Lamborghini, Audi), the VW group is still only worth about half of what Tesla is worth, according to graphs that Diess passed along to Volkswagens top tier executives.

Volkswagen is clearly not going to let this continue at the same rate and the first step is to get the ID.3 out when its supposed to be out. And it would appear that even with the reported software issues, the manufacturer has now restarted ID.3 production and it still says it wont postpone the start of deliveries.

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How Quantum Computers Work | HowStuffWorks

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The massive amount of processing power generated by computer manufacturers has not yet been able to quench our thirst for speed and computing capacity. In 1947, American computer engineer Howard Aiken said that just six electronic digital computers would satisfy the computing needs of the United States. Others have made similar errant predictions about the amount of computing power that would support our growing technological needs. Of course, Aiken didn't count on the large amounts of data generated by scientific research, the proliferation of personal computers or the emergence of the Internet, which have only fueled our need for more, more and more computing power.

Will we ever have the amount of computing power we need or want? If, as Moore's Law states, the number of transistors on a microprocessor continues to double every 18 months, the year 2020 or 2030 will find the circuits on a microprocessor measured on an atomic scale. And the logical next step will be to create quantum computers, which will harness the power of atoms and molecules to perform memory and processing tasks. Quantum computers have the potential to perform certain calculations significantly faster than any silicon-based computer.

Scientists have already built basic quantum computers that can perform certain calculations; but a practical quantum computer is still years away. In this article, you'll learn what a quantum computer is and just what it'll be used for in the next era of computing.

You don't have to go back too far to find the origins of quantum computing. While computers have been around for the majority of the 20th century, quantum computing was first theorized less than 30 years ago, by a physicist at the Argonne National Laboratory. Paul Benioff is credited with first applying quantum theory to computers in 1981. Benioff theorized about creating a quantum Turing machine. Most digital computers, like the one you are using to read this article, are based on the Turing Theory. Learn what this is in the next section.

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What Is Quantum Computing? The Next Era of Computational …

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When you first stumble across the term quantum computer, you might pass it off as some far-flung science fiction concept rather than a serious current news item.

But with the phrase being thrown around with increasing frequency, its understandable to wonder exactly what quantum computers are, and just as understandable to be at a loss as to where to dive in. Heres the rundown on what quantum computers are, why theres so much buzz around them, and what they might mean for you.

All computing relies on bits, the smallest unit of information that is encoded as an on state or an off state, more commonly referred to as a 1 or a 0, in some physical medium or another.

Most of the time, a bit takes the physical form of an electrical signal traveling over the circuits in the computers motherboard. By stringing multiple bits together, we can represent more complex and useful things like text, music, and more.

The two key differences between quantum bits and classical bits (from the computers we use today) are the physical form the bits take and, correspondingly, the nature of data encoded in them. The electrical bits of a classical computer can only exist in one state at a time, either 1 or 0.

Quantum bits (or qubits) are made of subatomic particles, namely individual photons or electrons. Because these subatomic particles conform more to the rules of quantum mechanics than classical mechanics, they exhibit the bizarre properties of quantum particles. The most salient of these properties for computer scientists is superposition. This is the idea that a particle can exist in multiple states simultaneously, at least until that state is measured and collapses into a single state. By harnessing this superposition property, computer scientists can make qubits encode a 1 and a 0 at the same time.

The other quantum mechanical quirk that makes quantum computers tick is entanglement, a linking of two quantum particles or, in this case, two qubits. When the two particles are entangled, the change in state of one particle will alter the state of its partner in a predictable way, which comes in handy when it comes time to get a quantum computer to calculate the answer to the problem you feed it.

A quantum computers qubits start in their 1-and-0 hybrid state as the computer initially starts crunching through a problem. When the solution is found, the qubits in superposition collapse to the correct orientation of stable 1s and 0s for returning the solution.

Aside from the fact that they are far beyond the reach of all but the most elite research teams (and will likely stay that way for a while), most of us dont have much use for quantum computers. They dont offer any real advantage over classical computers for the kinds of tasks we do most of the time.

However, even the most formidable classical supercomputers have a hard time cracking certain problems due to their inherent computational complexity. This is because some calculations can only be achieved by brute force, guessing until the answer is found. They end up with so many possible solutions that it would take thousands of years for all the worlds supercomputers combined to find the correct one.

The superposition property exhibited by qubits can allow supercomputers to cut this guessing time down precipitously. Classical computings laborious trial-and-error computations can only ever make one guess at a time, while the dual 1-and-0 state of a quantum computers qubits lets it make multiple guesses at the same time.

So, what kind of problems require all this time-consuming guesswork calculation? One example is simulating atomic structures, especially when they interact chemically with those of other atoms. With a quantum computer powering the atomic modeling, researchers in material science could create new compounds for use in engineering and manufacturing. Quantum computers are well suited to simulating similarly intricate systems like economic market forces, astrophysical dynamics, or genetic mutation patterns in organisms, to name only a few.

Amidst all these generally inoffensive applications of this emerging technology, though, there are also some uses of quantum computers that raise serious concerns. By far the most frequently cited harm is the potential for quantum computers to break some of the strongest encryption algorithms currently in use.

In the hands of an aggressive foreign government adversary, quantum computers could compromise a broad swath of otherwise secure internet traffic, leaving sensitive communications susceptible to widespread surveillance. Work is currently being undertaken to mature encryption ciphers based on calculations that are still hard for even quantum computers to do, but they are not all ready for prime-time, or widely adopted at present.

A little over a decade ago, actual fabrication of quantum computers was barely in its incipient stages. Starting in the 2010s, though, development of functioning prototype quantum computers took off. A number of companies have assembled working quantum computers as of a few years ago, with IBM going so far as to allow researchers and hobbyists to run their own programs on it via the cloud.

Despite the strides that companies like IBM have undoubtedly made to build functioning prototypes, quantum computers are still in their infancy. Currently, the quantum computers that research teams have constructed so far require a lot of overhead for executing error correction. For every qubit that actually performs a calculation, there are several dozen whose job it is to compensate for the ones mistake. The aggregate of all these qubits make what is called a logical qubit.

Long story short, industry and academic titans have gotten quantum computers to work, but they do so very inefficiently.

Fierce competition between quantum computer researchers is still raging, between big and small players alike. Among those who have working quantum computers are the traditionally dominant tech companies one would expect: IBM, Intel, Microsoft, and Google.

As exacting and costly of a venture as creating a quantum computer is, there are a surprising number of smaller companies and even startups that are rising to the challenge.

The comparatively lean D-Wave Systems has spurred many advances in the fieldand proved it was not out of contention by answering Googles momentous announcement with news of a huge deal with Los Alamos National Labs. Still, smaller competitors like Rigetti Computing are also in the running for establishing themselves as quantum computing innovators.

Depending on who you ask, youll get a different frontrunner for the most powerful quantum computer. Google certainly made its case recently with its achievement of quantum supremacy, a metric that itself Google more or less devised. Quantum supremacy is the point at which a quantum computer is first able to outperform a classical computer at some computation. Googles Sycamore prototype equipped with 54 qubits was able to break that barrier by zipping through a problem in just under three-and-a-half minutes that would take the mightiest classical supercomputer 10,000 years to churn through.

Not to be outdone, D-Wave boasts that the devices it will soon be supplying to Los Alamos weigh in at 5000 qubits apiece, although it should be noted that the quality of D-Waves qubits has been called into question before. IBM hasnt made the same kind of splash as Google and D-Wave in the last couple of years, but they shouldnt be counted out yet, either, especially considering their track record of slow and steady accomplishments.

Put simply, the race for the worlds most powerful quantum computer is as wide open as it ever was.

The short answer to this is not really, at least for the near-term future. Quantum computers require an immense volume of equipment, and finely tuned environments to operate. The leading architecture requires cooling to mere degrees above absolute zero, meaning they are nowhere near practical for ordinary consumers to ever own.

But as the explosion of cloud computing has proven, you dont need to own a specialized computer to harness its capabilities. As mentioned above, IBM is already offering daring technophiles the chance to run programs on a small subset of its Q System Ones qubits. In time, IBM and its competitors will likely sell compute time on more robust quantum computers for those interested in applying them to otherwise inscrutable problems.

But if you arent researching the kinds of exceptionally tricky problems that quantum computers aim to solve, you probably wont interact with them much. In fact, quantum computers are in some cases worse at the sort of tasks we use computers for every day, purely because quantum computers are so hyper-specialized. Unless you are an academic running the kind of modeling where quantum computing thrives, youll likely never get your hands on one, and never need to.

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When quantum computing and AI collide – Raconteur

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Machine-learning and quantum computing are two technologies that have incredible potential in their own right. Now researchers are bringing them together. The main goal is to achieve a so-called quantum advantage, where complex algorithms can be calculated significantly faster than with the best classical computer. This would be a game-changer in the field of AI.

Such a breakthrough could lead to new drug discoveries, advances in chemistry, as well as better data science, weather predictions and natural-language processing. We could be as little as three years away from achieving a quantum advantage in AI if the largest players in the quantum computing space meet their goals, says Ilyas Khan, chief executive of Cambridge Quantum Computing.

This comes after Google announced late last year that it had achieved quantum supremacy, claiming their quantum computer had cracked a problem that would take even the fastest conventional machine thousands of years to solve.

Developing quantum machine-learning algorithms could allow us to solve complex problems much more quickly. To realise the full potential of quantum computing for AI, we need to increase the number of qubits that make up these systems, says Dr Jay Gambetta, vice president of quantum computing at IBM Research.

Quantum devices exploit the strange properties of quantum physics and mechanics to speed up calculations. Classical computers store data in bits, as zeros or ones. Quantum computers use qubits, where data can exist in two different states simultaneously. This gives them more computational fire power. Were talking up to a million times faster than some classical computers.

And when you add a single qubit, you double the quantum computers processing power. To meet Moores Law [the number of transistors on a computer chip is doubled about every two years while the cost falls], you would need to add a single qubit every year, says Peter Chapman, chief executive of IonQ.

Our goal is to double the number of qubits every year. We expect quantum computers to be able to routinely solve problems that supercomputers cannot, within two years.

Already industrial behemoths, such as IBM, Honeywell, Google, Microsoft and Amazon, are active in the quantum computing sector. Their investments will have a major impact on acceleratingdevelopments.

We expect algorithm development to accelerate considerably. The quantum community has recognised economic opportunities in solving complex optimisation problems that permeate many aspects of the business world. These range from how do you assemble a Boeing 777 with millions of parts in the correct order? to challenges in resource distribution, explains Dr David Awschalom, professor of quantum information at the University of Chicago.

The quantum community has recognised economic opportunities in solving complex optimisation problems that permeate many aspects of the business world

Many of the computational tasks that underlie machine-learning, used currently for everything from image recognition to spam detection, have the correct form to allow a quantum speed up. Not only would this lead to faster calculations and more resource-efficient algorithms, it could also allow AI to tackle problems that are currently unfeasible because of their complexity and size.

Quantum computers arent a panacea for all humankinds informatic problems. They are best suited to very specific tasks, where there are a huge number of variables and permutations, such as calculating the best delivery route for rubbish trucks or the optimal path through traffic congestion. Mitsubishi in Japan and Volkswagen in Germany have deployed quantum computing with AI to explore solutions to these issues.

There will come a time when quantum AI could be used to help us with meaningful tasks from industrial scheduling to logistics. Financial optimisation for portfolio management could also be routinely handled by quantum computers.

This sounds like it might have limited use, but it turns out that many business problems can be expressed as an optimisation problem. This includes machine-learning problems, says Chapman.

Within a few short years we will enter the start of the quantum era. Its important for people to be excited about quantum computing; it allows government funding to increase and aids in recruitment. We need to continue to push the technology and also to support early adopters to explore how they can apply quantum computing to their businesses.

However, its still early days. The next decade is a more accurate time frame in terms of seeing quantum computing and AI coalesce and really make a difference. The need to scale to larger and more complex problems with real-world impact is one area of innovation, as is creating quantum computers that have greater precision and performance.

The limitation of quantum technology, particularly when it comes to AI, is summarised by the term decoherence. This is caused by vibrations, changes in temperature, noise and interfacing with the external environment. This causes computers to lose their quantum state and prevents them from completing computational tasks in a timely manner or at all, says Khan.

The industrys immediate priority has shifted from sheer processing power, measured by qubits, to performance, better measured by quantum volume. Rightly so the industry is channelling its energy into reducing errors to break down this major barrier and unlock the true power of machine-learning.

Over time it is the ease of access to these computers that will lead to impactful business applications and the development of successful quantum machine-learning. IBM has opened its doors to its quantum computers via the cloud since 2016 for anyone to test ideas. In the process it has fostered a vibrant community with more than 200,000 users from over 100 organisations.

The more developers and companies that get involved in first solving optimisation problems related to AI and then over time building quantum machine-learning and AI development, the sooner well see even more scalable and robust applications with business value, explains Murray Thom, vice president of software at D-Wave Systems.

Most importantly, we need a greater number of smart people identifying and developing applications. That way we will be able to overcome limitations much faster, and expand the tools and platform so they are easier to use. Bringing in more startups and forward-thinking enterprise organisations to step into quantum computing and identify potential applications for their fields is also crucial.

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Amazon, IBM and Microsoft race to bring global access to quantum computing – CNET

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  1. Amazon, IBM and Microsoft race to bring global access to quantum computing  CNET
  2. IBM Issues A Public Challenge To Program Its Quantum Computers  Forbes
  3. Quantum Computer of the Future: A Novel 2D Build With Existing Technology  SciTechDaily
  4. AI and Quantum Computing Can Enable Much Anticipated Advancements  Analytics Insight
  5. IBM Quantum Celebrates Milestone with a Contest to Pump Up Momentum  HPCwire
  6. View Full Coverage on Google News

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Amazon, IBM and Microsoft race to bring global access to quantum computing - CNET

How Do Quantum Computers Work? – ScienceAlert

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Quantum computers perform calculations based on the probability of an object's state before it is measured - instead of just 1s or 0s - which means they have the potential to process exponentially more data compared to classical computers.

Classical computers carry out logical operations using the definite position of a physical state. These are usually binary, meaning its operations are based on one of two positions. A single state - such as on or off, up or down, 1 or 0 - is called a bit.

In quantum computing, operations instead use the quantum state of an object to produce what's known as a qubit. These states are the undefined properties of an object before they've been detected, such as the spin of an electron or the polarisation of a photon.

Rather than having a clear position, unmeasured quantum states occur in a mixed 'superposition', not unlike a coin spinning through the air before it lands in your hand.

These superpositions can be entangled with those of other objects, meaning their final outcomes will be mathematically related even if we don't know yet what they are.

The complex mathematics behind these unsettled states of entangled 'spinning coins' can be plugged into special algorithms to make short work of problems that would take a classical computer a long time to work out... if they could ever calculate them at all.

Such algorithms would be useful in solving complex mathematical problems, producing hard-to-break security codes, or predicting multiple particle interactions in chemical reactions.

Building a functional quantum computer requires holding an object in a superposition state long enough to carry out various processes on them.

Unfortunately, once a superposition meets with materials that are part of a measured system, it loses its in-between state in what's known as decoherence and becomes a boring old classical bit.

Devices need to be able to shield quantum states from decoherence, while still making them easy to read.

Different processes are tackling this challenge from different angles, whether it's to use more robust quantum processes or to find better ways to check for errors.

For the time being, classical technology can manage any task thrown at a quantum computer. Quantum supremacy describes the ability of a quantum computer to outperform their classical counterparts.

Some companies, such as IBM and Google, claim we might be close, as they continue to cram more qubits together and build more accurate devices.

Not everybody is convinced that quantum computers are worth the effort. Some mathematicians believe there are obstacles that are practically impossible to overcome, putting quantum computing forever out of reach.

Time will tell who is right.

All topic-based articles are determined by fact checkers to be correct and relevant at the time of publishing. Text and images may be altered, removed, or added to as an editorial decision to keep information current.

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How Do Quantum Computers Work? - ScienceAlert

Announcing the IBM Quantum Challenge – Quantaneo, the Quantum Computing Source

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Today, we have 18 quantum systems and counting available to our clients and community. Over 200,000 users, including more than 100 IBM Q Network client partners, have joined us to conduct fundamental research on quantum information science, develop the applications of quantum computing in various industries, and educate the future quantum workforce. Additionally, 175 billion quantum circuits have been executed using our hardware, resulting in more than 200 publications by researchers around the world.

In addition to developing quantum hardware, we have also been driving the development of powerful open source quantum software. Qiskit, written primarily in Python, has grown to be a popular quantum computing software development kit with several novel features, many of which were contributed by dedicated Qiskitters.

Thank you to everyone who has joined us on this exciting journey building the largest and most diverse global quantum computing community.

The IBM Quantum Challenge As we approach the fourth anniversary of the IBM Quantum Experience, we invite you to celebrate with us by completing a challenge with four exercises. Whether you are already a member of the community, or this challenge is your first quantum experiment, these four exercises will improve your understanding of quantum circuits. We hope you also have fun as you put your skills to test.

The IBM Quantum Challenge begins at 9:00 a.m. US Eastern on May 4, and ends 8:59:59 a.m. US Eastern on May 8. To take the challenge, visit https://quantum-computing.ibm.com/challenges.

In recognition of everyones participation, we are awarding digital badges and providing additional sponsorship to the Python Software Foundation.

Continued investment in quantum education Trying to explain quantum computing without resorting to incorrect analogies has always been a goal for our team. As a result, we have continuously invested in education, starting with opening access to quantum computers, and continuing to create tools that enable anyone to program them. Notably, we created the first interactive open source textbook in the field.

As developers program quantum computers, what they are really doing is building and running quantum circuits. To support your learning about quantum circuits:

Read the Qiskit textbook chapter where we define quantum circuits as we understand them today. Dive in to explore quantum computing principles and learn how to implement quantum algorithms on your own. Watch our newly launched livelectures called Circuit Sessions, or get started programming a quantum computer by watching Coding with Qiskit. Subscribe to the Qiskit YouTube channel to watch these two series and more. The future of quantum is in open source software and access to real quantum hardwarelets keep building together.

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Announcing the IBM Quantum Challenge - Quantaneo, the Quantum Computing Source

Trump betting millions to lay the groundwork for quantum internet in the US – CNBC

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In the 1960s the U.S. government funded a series of experiments developing techniques to shuttle information from one computer to another. Devices in single labs sprouted connections, then neighboring labs linked up. Soon the network had blossomed between research institutions across the country, setting down the roots of what would become the internet and transforming forever how people use information. Now, 60 years later, the Department of Energy is aiming to do it again.

The Trump administration's 2021 budget request currently under consideration by Congress proposes slashing the overall funding for scientific research by nearly 10% but boosts spending on quantum information science by about 20%, to $237 million. Of that, the DOE has requested $25 million to accelerate the development of a quantum internet. Such a network would leverage the counterintuitive behavior of nature's particles to manipulate and share information in entirely new ways, with the potential to reinvent fields including cybersecurity and material science.

Whilethetraditional internet for general useisn't going anywhere, a quantum networkwouldoffer decisive advantages for certain applications: Researchers could use it to develop drugs and materials by simulating atomic behavior onnetworked quantum computers, for instance, and financial institutions and governments would benefit from next-level cybersecurity. Many countries are pursuing quantum research programs, and with the 2021 budget proposal, the Trumpadministration seeks to ramp up thateffort.

"That level of funding will enable us to begin to develop the groundwork for sophisticated, practical and high-impact quantum networks," says David Awschalom, a quantum engineer at the University of Chicago. "It's significant and extremely important."

A quantum internet will develop in fits and starts, much like the traditional internet did and continues to do. China has already realized an early application, quantum encryption, between certain cities, but fully quantum networks spanning entire countries will take decades, experts say. Building it willrequire re-engineering the quantum equivalent of routers, hard drives, and computers from the ground up foundational work already under way today.

Where the modern internet traffics in bits streaming between classical computers (a category that now includes smart phones, tablets, speakers and thermostats), a quantum internet would carry a fundamentally different unit of information known as the quantum bit, or qubit.

Bits all boil down to instances of nature's simplest eventsquestions with yes or no answers. Computer chips process cat videos by stopping some electric currents while letting others flow. Hard drives store documents by locking magnets in either the up or down position.

Qubits represent a different language altogether, one based on the behavior of atoms, electrons, and other particles, objects governed by the bizarre rules of quantum mechanics. These objects lead more fluid and uncertain lives than their strait-laced counterparts in classical computing. A hard drive magnet must always point up or down, for instance, but an electron's direction is unknowable until measured. More precisely, the electron behaves in such a way that describing its orientation requires a more complex concept known as superposition that goes beyond the straightforward labels of "up" or "down."

Quantum particles can also be yoked together in a relationship called entanglement, such as when two photons (light particles) shine from the same source. Pairs of entangled particles share an intimate bond akin to the relationship between the two faces of a coin when one face shows heads the other displays tails. Unlike a coin, however, entangled particles can travel far from each other and maintain their connection.

Quantum information science unites these and other phenomena, promising a novel, richer way to process information analogous to moving from 2-D to 3-D graphics, or learning to calculate with decimals instead of just whole numbers. Quantum devices fluent in nature's native tongue could, for instance, supercharge scientists' ability to design materials and drugs by emulating new atomic structures without having to test their properties in the lab. Entanglement, a delicate link destroyed by external tampering, could guarantee that connections between devices remain private.

But such miracles remain years to decades away. Both superposition and entanglement are fragile states most easily maintained at frigid temperatures in machines kept perfectly isolated from the chaos of the outside world. And as quantum computer scientists search for ways to extend their control over greater numbers of finicky particles, quantum internet researchers are developing the technologies required to link those collections of particles together.

The interior of a quantum computer prototype developed by IBM. While various groups race to build quantum computers, Department of Energy researchers seek ways to link them together.

IBM

Just as it did in the 1960s, the DOE is again sowing the seeds for a future network at its national labs. Beneath the suburbs of western Chicago lie 52 miles of optical fiber extending in two loops from Argonne National Laboratory. Early this year, Awschalom oversaw the system's first successful experiments. "We created entangled states of light," he says, "and tried to use that as a vehicle to test how entanglement works in the real world not in a lab going underneath the tollways of Illinois."

Daily temperature swings cause the wires to shrink by dozens of feet, for instance, requiring careful adjustment in the timing of the pulses to compensate. This summer the team plans to extend their network with another node, bringing the neighboring Fermi National Accelerator Laboratory into the quantum fold.

Similar experiments are under way on the East Coast, too, where researchers have sent entangled photons over fiber-optic cables connecting Brookhaven National Laboratory in New York with Stony Brook University, a distance of about 11 miles. Brookhaven scientists are also testing the wireless transmission of entangled photons over a similar distance through the air. While this technique requires fair weather, according to Kerstin Kleese van Dam, the director of Brookhaven's computational science initiative, it could someday complement networks of fiber-optic cables. "We just want to keep our options open," she says.

Such sending and receiving of entangled photons represent the equivalent of quantum routers, but next researchers need a quantum hard drive a way to save the information they're exchanging. "What we're on the cusp of doing," Kleese van Dam says, "is entangled memories over miles."

When photons carry information in from the network, quantum memory will store those qubits in the form of entangled atoms, much as current hard drives use flipped magnets to hold bits. Awschalom expects the Argonne and University of Chicago groups to have working quantum memories this summer, around the same time they expand their network to Fermilab, at which point it will span 100 miles.

But that's about as far as light can travel before growing too dim to read. Before they can grow their networks any larger, researchers will need to invent a quantum repeater a device that boosts an atrophied signal for another 100-mile journey. Classical internet repeaters just copy the information and send out a new pulse of light, but that process breaks entanglement (a feature that makes quantum communications secure from eavesdroppers). Instead, Awschalom says, researchers have come up with a scheme to amplify the quantum signal by shuffling it into other forms without ever reading it directly. "We have some prototype quantum repeaters currently running. They're not good enough," he says, "but we're learning a lot."

Department of Energy Under Secretary for Science Paul M. Dabbar (left) sends a pair of entangled photons along the quantum loop. Also shown are Argonne scientist David Awschalom (center) and Argonne Laboratory Director Paul Kearns.

Argonne National Laboratory

And if Congress approves the quantum information science line in the 2021 budget, researchers like Awschalom and Kleese van Dam will learn a lot more. Additional funding for their experiments could lay the foundations for someday extending their local links into a country-wide network. "There's a long-term vision to connect all the national labs, coast to coast," says Paul Dabbar, the DOE's Under Secretary for Science.

In some senses the U.S. trails other countries in quantum networking. China, for example, has completed a 1,200-mile backbone linking Beijing and Shanghai that banks and other companies are already using for nearly perfectly secure encryption. But the race for a fully featured quantum internet is more marathon than sprint, and China has passed only the first milestone. Kleese van Dam points out that without quantum repeaters, this network relies on a few dozen "trusted" nodes Achilles' heels that temporarily put the quantum magic on pause while the qubits are shoved through bit-based bottlenecks. She's holding out for truly secure end-to-end communication. "What we're planning to do goes way beyond what China is doing," she says.

More from Tech Drivers:With America at home, Facebook, Google make moves to win more of gaming marketThe 87-year-old doctor who invented the rubella vaccine now working to fight the coronavirus

Researchers ultimately envision a whole quantum ecosystem of computers, memories, and repeaters all speaking the same language of superposition and entanglement, with nary a bit in sight. "It's like a big stew where everything has to be kept quantum mechanical," Awschalom says. "You don't want to go to the classical world at all."

After immediate applications such as unbreakable encryptions, he speculates that such a network could also lead to seismic sensors capable of logging the vibration of the planet at the atomic level, but says that the biggest consequences will likely be the ones no one sees coming. He compares the current state of the field to when electrical engineers developed the first transistors and initially used them to improve hearing aids, completely unaware that they were setting off down a path that would someday bring social media and video conferencing.

As researchers at Brookhaven, Argonne, and many other institutions tinker with the quantum equivalent of transistors, but they can't help but wonder what the quantum analog of video chat will be. "It's clear there's a lot of promise. It's going to move quickly," Awschalom says. "But the most exciting part is that we don't know exactly where it's going to go."

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Trump betting millions to lay the groundwork for quantum internet in the US - CNBC

Global Quantum Computing Market : Industry Analysis and Forecast (2020-2027) – MR Invasion

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Global Quantum Computing Marketwas valued US$ 198.31 Mn in 2019 and is expected to reach US$ 890.5 Mn by 2027, at CAGR of 28.44 % during forecast.

The report study has analyzed revenue impact of covid-19 pandemic on the sales revenue of market leaders, market followers and disrupters in the report and same is reflected in our analysis.

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Quantum computing market growth is being driven by factors like increasing incidences of cybercrime, early adoption of quantum computing technology in automotive and defense industry, and growing investments by government entities in quantum computing market. On the other hand, presence of substitute technology and reluctance to accept new technology are factors limiting the growth of quantum computing market.

Quantum computing market in the energy & power industry is projected to witness a CAGR of 40% from 2017 to 2023. This growth is primarily attributed to the beneficial opportunities existing in the nuclear and renewable sector. Applications like energy exploration, seismic survey optimization, and reservoir optimization are estimated to lead this industry in quantum computing market.

North America was holding the largest market share of quantum computing market in 2016. North America is a key market as it is the home ground for some of the major corporations like D-Wave Systems Inc., 1QB Information Technologies, Inc. The increased research and development (R&D) activities in the sector of quantum computing are directed in this region as well as the heavy investments by government activities and technologically advanced players International Business Machines Corporation, Microsoft Corporation, Google Inc., and Intel Corporation are factors driving the growth of quantum computing market in North America. The R&D at industry levels is extending the application areas of the quantum computing market in various industries like energy & power, defense, and chemicals, especially in US.

Owing to the economic interest and decline of Moores law of computational scaling, eighteen of the worlds biggest corporations and dozens of government organizations are working on quantum processor technologies and quantum software or associating with the quantum industry startups like D-Wave. Their determination reflects a wider transition, taking place at start-ups and academic research labs like move from pure science towards engineering.

Quantum computing market report evaluates the technology, companies/associations, R&D efforts, and potential solutions assisted by quantum computing. It also estimates the impact of quantum computing on other major technologies and solution areas with AI, chipsets, edge computing, blockchain, IoT, big data analytics, and smart cities. This report offers global and regional forecasts as well the viewpoint for quantum computing impact on hardware, software, applications, and services

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The objective of the report is to present a comprehensive assessment of the market and contains thoughtful insights, facts, historical data, industry-validated market data and projections with a suitable set of assumptions and methodology. The report also helps in understanding Quantum Computing market dynamics, structure by identifying and analyzing the market segments and project the global market size. Further, report also focuses on competitive analysis of key players by product, price, financial position, product portfolio, growth strategies, and regional presence. The report also provides PEST analysis, PORTERs analysis, SWOT analysis to address questions of shareholders to prioritizing the efforts and investment in near future to emerging segment in Quantum Computing market.Scope of Global Quantum Computing Market:

Global Quantum Computing Market, by Technology:

Superconducting loops technology Trapped ion technology Topological qubits technologyGlobal Quantum Computing Market, by Application:

Simulation Optimization SamplingGlobal Quantum Computing Market, by Component:

Hardware Software ServicesGlobal Quantum Computing Market, by Industry:

Defense Banking & Finance Energy & Power Chemicals Healthcare & PharmaceuticalsGlobal Quantum Computing Market, by Region:

North America Asia Pacific Europe Latin America Middle East & AfricaKey Players Operating in Market Include:

D-Wave Systems Inc 1QB Information Technologies Inc. QxBranch LLC QC Ware Corp. and Research at Google-Google Inc. International Business Machines Corporation Lockheed Martin Corporation Intel Corporation Anyon Systems Inc. Cambridge Quantum Computing Limited Rigetti Computing Magiq Technologies Inc. Station Q Microsoft Corporation IonQ Quantum Computing Software Start-ups Qbit Alibaba Ariste-QB.net Atos Q-Ctrl Qu and Co Quantum Benchmark SAP Turing Zapata

MAJOR TOC OF THE REPORT

Chapter One: Quantum Computing Market Overview

Chapter Two: Manufacturers Profiles

Chapter Three: Global Quantum Computing Market Competition, by Players

Chapter Four: Global Quantum Computing Market Size by Regions

Chapter Five: North America Quantum Computing Revenue by Countries

Chapter Six: Europe Quantum Computing Revenue by Countries

Chapter Seven: Asia-Pacific Quantum Computing Revenue by Countries

Chapter Eight: South America Quantum Computing Revenue by Countries

Chapter Nine: Middle East and Africa Revenue Quantum Computing by Countries

Chapter Ten: Global Quantum Computing Market Segment by Type

Chapter Eleven: Global Quantum Computing Market Segment by Application

Chapter Twelve: Global Quantum Computing Market Size Forecast (2019-2026)

Browse Full Report with Facts and Figures of Quantum Computing Market Report at:https://www.maximizemarketresearch.com/market-report/global-quantum-computing-market/27533/

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Global Quantum Computing Market : Industry Analysis and Forecast (2020-2027) - MR Invasion

Defeating Covid-19 monster the digital way – Daily Pioneer

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Different devices and advanced technologies have been developed and implemented to win the war against COVID-19. In this pandemic, advanced technology tools are the monitoring and controlling weapons of corona virus outbreaks, as humans cannot operate at a speed of AI powered machines. Here I have came up with some of the possible technological concepts and their role to fight against COVID-19, which could possibly help to control the outbreak.

Quantum Computers

To win the war against COVID-19 outbreak, quantum computing plays a vital role for providing services to better pandemic control. Supercomputers are used for quickly and carefully mapping the molecular structure of corona virus so that it will be easy for developing medicines and treatments. IBM supercomputer is being deployed by the researchers to find out the chemical compounds to fight against corona virus. This super computer generate results within 1-2 days rather than months which could have taken by standard computing system to produce the same result. Till date, the quantum computer has supported researchers to identify 77 molecule compounds.

Machine learning to find a treatment

By gathering sufficient quality data and implementing artificial intelligence concept, which could be a powerful tool used for predicting the diseases future trend and even searching for possible treatments. Different biotechnology companies are using machine learning concept to develop treatments based on antibodies from patients who have recovered from the COVID-19. These companies have used Artificial Intelligence (AI) concept to analyze more than millions of immune cells as they desire to search for those that are able to produce antibodies which help patients recover.

Facial recognition and Big Data

Different organisations have developed dashboards for accessing the public information to monitor the corona virus using Big Data. Most of the developed cities across the globe have installed infrared temperature detection and face recognition techniques.

Telecom companies of China are providing facility of mobile sent text messages to their State media agencies, informing about the person who have been infected. This message includes the details about the persons travel history. Some companies like Panasonic, Sense Time and FacePro have also developed certain kind of software which can easily identify the people without face masks.

Satellite technology

Satellite technology provides better service in social distancing. Advanced countries are using both macro and micro level satellites for providing information about the social distancing and stay at home information. Satellite imageries systems are used for providing the information about the different activities happening or not-happening across the major cities, crowded places, industrial sites, farming activity, tourist places, and on different high ways during the lockdowns or normal days.

Robots

Robots are the game changers in COVID-19 as they reduce the human-to-human interaction and the potential danger expected for the life of the medical staff members. Robots are being used to disinfect, deliver medicine, measure temperatures, food preparation and communicate among the isolated members. A Danish company in China is providing UVD Robots which can disinfect the patient cabins based on the statement. UVD Robot moves around patient rooms autonomously and emitting right amount of ultraviolet light covering all surface area in order to kill corona viruses and other bacteria. Some hospitals of US are also using robots to communicate among the doctors and patients through a screen and it was equipped with a stethoscope.

Health sensors and mobile apps

Mobile applications are being used for tracking and preventing the spread of corona virus disease. Utilising the proper surveillance network for public goodness, the Government of India has developed a mobile application Aarogya Setu to connect essential health services among people of India to fight against COVID-19.

Australia has developed a mobile APP already used in Singapore for contact tracing by detecting whether the people had spent more than 15 minutes with other peoples who may have been infected by COVID-19.

The Chinese Government in association with Alibaba and Tencent developed a color-coded health rating system which played a vital role in China for tracking millions of people daily. The mobile app was first deployed in Hangzhou in collaboration with Alibaba. It consists of three colors to people yellow, green and red based on their travel and medical histories.

(Dr Senapati is Dean Science, BPUT, and Mallick is Asst Professor in Computer Science and Engineering, Trident Academy of Technology, Bhubaneswar, Email:dr_senapati@yahoo.com, soubhagya.mallick@gmail.com)

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Defeating Covid-19 monster the digital way - Daily Pioneer

Stevens Institute of Technology Leads First NSF Center Devoted to Financial Technology and Science – HPCwire

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HOBOKEN, N.J., April 30, 2020 In one of the strongest acknowledgments that finance has transformed from a low-tech field to one that relies on some of the most sophisticated technology in the world, the National Science Foundation has selected Stevens Institute of Technology to lead the first-ever industry-university cooperative research center, or IUCRC, devoted to financial technology and science.

The five-year award creates a cooperative research center that brings together partners to conduct research that is particularly relevant for industry and has a high potential for commercialization. Stevens was named lead institution for the center, which includes Georgetown University and Rensselaer Polytechnic Institute, and between eight and 25+ companies with the goal of finding innovative solutions for complex challenges facing the fintech industry.

Georgetown and RPI complement our strengths very nicely, said George Calhoun, director of the Hanlon Financial Systems Center at Stevens School of Business and a co-principal investigator on the project. Georgetown is good in traditional finance and the regulatory end of the business what is the Federal Reserve going to do, what is the Treasury going to do in ways that reflect their own location advantage. And RPI brings additional scientific and technological capabilities to the table.

Stevenslocationand existing relationships with financial firms position it well to lead the center. With its proximity to New York City, Stevens has worked closely with financial firms and banks to identify core challenges facing industry and has responded by addressing those needs, further strengthening these relationships while simultaneously shaping its research endeavors and curriculum to align with those needs. The result: the transformation of the School of Business to a tech-infused powerhouse.

The list of firms who provided letters of support as part of Stevens bid included UBS, Bank of America, Citibank and Royal Bank of Canada among the headliners.Chicago Mercantile Exchange Group; PSEG; OneMarketData; and Capco, a global management consultancy, also supported Stevens bid. The reason we were successful is that we showed we would have major industry participation, said Calhoun.

Among the initial areas of focus in the IUCRC will be cybersecurity; high-frequency automated markets; technology risk and regulation; commercialization; and applications of blockchain, quantum computing, natural language processing and A.I. to the finance industry.

That diversity is reflected by the broad expertise of the co-principal investigators, which includ Giuseppe Ateniese (computer science), Jeffrey Nickerson (information systems and networks) and Darinka Dentcheva (mathematics and optimization). Working with such a broad panel of experts in addition to thought leaders at Georgetown, RPI and industry will empower a multidisciplinary approach that should break traditional research silos, said Steve Yang, the principal investigator on the project.

I couldnt be more excited to have Stevens play such an important leadership role in an NSF IUCRC center, said Gregory Prastacos, dean of the Business School at Stevens. The IUCRC will not only help us bring our work to the companies that would benefit from these insights, it also gives us another channel to engage industry and better understand the unique challenges they face.

The NSF IUCRC announcement comes on the heels ofMaCuDE, a global initiative led by Stevens and AACSB, and funded by PwC, to guide more than 100 universities across the world on how to reboot the traditional MBA curriculum to keep pace with the demands of the digital era. Stevens also recently announced their partnership withCapco, a managment consultancy with a strong focus on financial services will leverage Stevens research strengths in quantum, A.I. and blockchain, among other areas, to improve the digital portfolio of their clients.

Stevens is now in the planning phase for the IUCRC project, which will run for one year to identify an agenda of research topics based on industry feedback. Each industry partner will contribute $50,000 per year to contribute toward these research efforts.

There are about 75 NSF-funded industry-university cooperative research centers across the United States.

About Stevens Institute of Technology

Stevens Institute of Technology is a premier, private research university situated in Hoboken, New Jersey. Since our founding in 1870, technological innovation has been the hallmark of Stevens education and research. Within the universitys three schools and one college, 7,300 undergraduate and graduate students collaborate closely with faculty in an interdisciplinary, student-centric, entrepreneurial environment. Academic and research programs spanning business, computing, engineering, the arts and other disciplines actively advance the frontiers of science and leverage technology to confront our most pressing global challenges. As Stevens celebrates its 150th anniversary, the university continues to be consistently ranked among the nations leaders in career services, post-graduation salaries of alumni, and return on tuition investment.

Source: Stevens Institute of Technology

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Stevens Institute of Technology Leads First NSF Center Devoted to Financial Technology and Science - HPCwire

Obama official heading secretive Pentagon office tied to Leaks on Flynn The Tribune Papers- Breaking News & Top Local Stories – Thetribunepapers

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FPI Reports-Email records obtained from the U.S. Department of Defense show extensive communications between the Pentagons Director of the secretive Office of Net Assessment (ONA) , James Baker, and Washington Post reporter David Ignatius.

Lawyers for Lt. Gen. Michael Flynn alleged in a November 1, 2019 court filing that Baker is believed to be the person who illegally leaked to Ignatius the transcript of Flynns Dec. 29, 2016 telephone calls with Russian Ambassador Sergei Kislyak.

The Washington Post published Ignatius account of the calls on Jan. 12, 2017, setting in motion a chain of events that lead to Flynns Feb. 13, 2017 firing as national security adviser and subsequent prosecution for making false statements to the FBI about the calls.

These records confirm that Mr. Baker was an anonymous source for Mr. Ignatius, said Judicial Watch President Tom Fitton. Mr. Baker should be directly questioned about any and all leaks to his friend at the Washington Post.

U.S. Attorney John Durham is reportedly investigating the leak of information targeting Flynn.

Citing the governments bad faith, vindictiveness and breach of the plea agreement, in January 2020 Flynns attorney, Sidney Powell, moved to withdraw Flynns 2017 guilty plea during the Mueller investigation. Flynn claims he felt forced to plead guilty when his son was threatened with prosecution and he exhausted his financial resources. Last week, prosecutors provided Flynns defense team with documentation of this threat, according to additional papers Flynns lawyers filed April 24, 2020, in support of the motion to withdraw.

Judicial Watch obtained the records in a November 2019 Freedom of Information Act (FOIA) lawsuit filed after the DOD failed to respond to a September 2019 request.

The records include an exchange on Feb. 16, 2016, with the subject line Ignatius, in which Baker tells Pentagon colleague Zachary Mears, then-deputy chief of staff to Obama Secretary of Defense Ashton Carter, that he has a long history with David and talks with him regularly.

In an email exchange on October 1, 2018, in a discussion about artificial intelligence, Baker tells Ignatius: David, please, as always, our discussions are completely off the record. If any of my observations strike you as worthy of mixing or folding into your own thinking, that is as usual fine. Ignatius replies, Understood. Thanks for talking with me.

Ignatius and Bakers email exchanges per year are summarized below:

In 2015, Ignatius and Baker had a total of seven email conversations to set up meetings or calls, two simply to compliment one another and one exchange where Ignatius invited Baker to speak at the Aspen Strategy Group conference.

In 2016, Ignatius and Baker had a total of 10 email exchanges to set up meetings or calls and two to compliment each other.

In 2017, Ignatius and Baker had a total of 10 email exchanges to set up meetings, one exchange where Ignatius forwarded one of his articles, and one exchange where Ignatius asks Baker for his thoughts on the JCPOA (the Iran nuclear deal), because Baker wasnt available on the phone.

In 2018, Ignatius and Baker had a total of nine email exchanges to set up meetings, four where Ignatius forwarded articles and one where Ignatius asks Baker for tips on what to say at a quantum computing conference where he was speaking.

In a related case, in October 2018, Judicial Watch filed a FOIA lawsuit against the U.S. Department of Defense seeking information about the September 2016 contract between the DOD and Stefan Halper, the Cambridge University professor identified as a secret FBI informant used by the Obama administration to spy on Trumps presidential campaign. Halper also reportedly had high-level ties to both U.S. and British intelligence.

Government records show that the DODs Office of Net Assessment paid Halper a total of $1,058,161 for four contracts that lasted from May 30, 2012, to March 29, 2018. More than $400,000 of the payments came between July 2016 and September 2017, after Halper reportedly offered Trump campaign volunteer George Papadopoulos work and a trip to London to entice him into disclosing information about alleged collusion between the Russian government and the Trump campaign.

Flynns attorney told the court that Baker was Halpers handler in the ONA.

Free Press International

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Obama official heading secretive Pentagon office tied to Leaks on Flynn The Tribune Papers- Breaking News & Top Local Stories - Thetribunepapers

Biden should campaign on the theme: ‘Is this really the best we can do?’ – Yakima Herald-Republic

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WASHINGTON In speeches during the 1960 presidential campaign, John Kennedy addressed Americans anxiety about national lassitude at the end of eight years under Dwight Eisenhower by mildly saying: I believe we can do better. Joe Biden, responding to national embarrassment about the least presidential president, can campaign on a modest theme: Is this really the best we can do?

This question answers itself, particularly concerning foreign policy. Fortunately for Biden, events and his opponent are making this central to the 2020 election.

It is axiomatic that Americans preference regarding foreign policy is to have as little of it as possible. Hence most of this cycles Democratic presidential aspirants avoided reminding people that the world is a dangerous place. However, in the Feb. 25 debate in Charleston, S.C., Biden called Chinas President Xi Jinping a thug: This is a guy who doesnt have a democratic-with-a-small-d bone in his body.

Economist John Maynard Keynes supposedly said, When the facts change, I change my mind. Biden, citing new facts, including aggression against Hong Kongs freedom and a million Uighurs in concentration camps, has jettisoned his 2016 talk of his enhanced cooperation with Xi. In 34 of Bidens 36 Senate years, he was on the Foreign Relations Committee, which he chaired for four years. Donald Trumps foreign policy judgments have ranged from the contemptible (siding with Vladimir Putin at Helsinki in 2018 against U.S. intelligence officials regarding Russian interference in the 2016 election) to the preposterous (There is no longer a Nuclear Threat from North Korea) to the weird (he and North Koreas Kim Jong Un fell in love after exchanging beautiful letters).

Trump now wants to make relations with China central to this campaign. His rhetorical skills probably honed where they evidently peaked, on grammar school playgrounds are emulated by his campaign in references to Beijing Biden. Biden can, however, turn China to his advantage by showing Trump what a policy of national strength would look like.

Biden served in the Senate for a decade with Sen. Henry Jackson, D-Wash., a liberal Cold Warrior who helped to make the Soviet Unions human-rights abuses costly to the regime. Today, Biden should speak forcefully against Chinas arrests of Martin Lee, 81, Jimmy Lai, 71, Margaret Ng, 72, and other leaders of Hong Kongs democracy movement.

Biden can practice what he preaches about bipartisanship by associating himself with Arkansas Republican Sen. Tom Cottons measured but insistent support for the investigation of the possible role of a Wuhan research laboratory in the coronavirus outbreak. And with former U.S. ambassador to the United Nations Nikki Haleys call to require U.S. universities to disclose Chinas funding of their professors and research. Cotton questions the visas for Chinese to pursue postgraduate studies here in advanced science and technology fields: If Chinese students want to study Shakespeare and the Federalist Papers, thats what they need to learn from America. They dont need to learn quantum computing and artificial intelligence from America.

In February, a senior adviser for the World Health Organizations director-general praised Chinas bold approach that changed the course of the epidemic. Indeed China did: Its first approach was to deny that there is human-to-human transmission. Biden should say that continued U.S. participation in this organization will be contingent upon its granting Taiwan membership. Biden should also promise to discuss Taiwans exemplary response to COVID-19 with Tsai Ing-wen in the Oval Office. She would be the first Taiwanese president welcomed in the United States since the 1979 normalization of relations with China.

By taking such steps, Biden can reconnect his party with its luminous post-1945 achievement. In that golden moment in the history of this nations engagement with the world, the talents of Dean Acheson, George Marshall, George Kennan, Averell Harriman, Robert Lovett, Charles Bohlen, John McCloy and others created the structures of free trade and collective military security that produced the related phenomena of global enrichment and Soviet collapse.

The winners of the past seven presidential elections (1992-2016) have averaged 330 electoral votes. If todays state-by-state polls are correct, and if the election were held today, Biden would win 333 electoral votes: 227 from Hillary Clintons states plus those from Wisconsin, Michigan, Pennsylvania, Florida, Arizona and North Carolina.

More than any particular policy outcome, Americans want a sense that their nation can regain the spring in its step, and can adopt a robust realism regarding the Leninist party-state that is its principal adversary. The first step toward a jauntier, safer America is to make the election a referendum on the right question: Is this really the best we can do?

2020 Washington Post Writers Group

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Biden should campaign on the theme: 'Is this really the best we can do?' - Yakima Herald-Republic