Microsoft may have finally made quantum computing useful

The dream of quantum computing has always been exciting: What if we could build a machine working at the quantum level that could tackle complex calculations exponentially faster than a computer limited by classical physics? But despite seeing IBM, Google and others announce iterative quantum computing hardware, they're still not being used for any practical purposes. That might change with today's announcement from Microsoft and Quantinuum, who say they've developed the most error-free quantum computing system yet.

While classical computers and electronics rely on binary bits as their basic unit of information (they can be either on or off), quantum computers work with qubits, which can exist in a superposition of two states at the same time. The trouble with qubits is that they're prone to error, which is the main reason today's quantum computers (known as Noisy Intermediate Scale Quantum [NISQ] computers) are just used for research and experimentation.

Microsoft's solution was to group physical qubits into virtual qubits, which allows it to apply error diagnostics and correction without destroying them, and run it all over Quantinuum's hardware. The result was an error rate that was 800 times better than relying on physical qubits alone. Microsoft claims it was able to run more than 14,000 experiments without any errors.

According to Jason Zander, EVP of Microsoft's Strategic Missions and Technologies division, this achievement could finally bring us to "Level 2 Resilient" quantum computing, which would be reliable enough for practical applications.

"The task at hand for the entire quantum ecosystem is to increase the fidelity of qubits and enable fault-tolerant quantum computing so that we can use a quantum machine to unlock solutions to previously intractable problems," Zander wrote in a blog post today. "In short, we need to transition to reliable logical qubits — created by combining multiple physical qubits together into logical ones to protect against noise and sustain a long (i.e., resilient) computation."

Microsoft's announcement is a "strong result," according to Aram Harrow, a professor of physics at MIT focusing on quantum information and computing. "The Quantinuum system has impressive error rates and control, so it was plausible that they could do an experiment like this, but it's encouraging to see that it worked," he said in an e-mail to Engadget. "Hopefully they'll be able to keep maintaining or even improving the error rate as they scale up."

Microsoft Quantum Computing
Microsoft

Researchers will be able to get a taste of Microsoft's reliable quantum computing via Azure Quantum Elements in the next few months, where it will be available as a private preview. The goal is to push even further to Level 3 quantum supercomputing, which will theoretically be able to tackle incredibly complex issues like climate change and exotic drug research. It's unclear how long it'll take to actually reach that point, but for now, at least we're moving one step closer towards practical quantum computing.

"Getting to a large-scale fault-tolerant quantum computer is still going to be a long road," Professor Harrow wrote. "This is an important step for this hardware platform. Along with the progress on neutral atoms, it means that the cold atom platforms are doing very well relative to their superconducting qubit competitors."

This article originally appeared on Engadget at https://www.engadget.com/microsoft-may-have-finally-made-quantum-computing-useful-164501302.html?src=rss

Microsoft may have finally made quantum computing useful

The dream of quantum computing has always been exciting: What if we could build a machine working at the quantum level that could tackle complex calculations exponentially faster than a computer limited by classical physics? But despite seeing IBM, Google and others announce iterative quantum computing hardware, they're still not being used for any practical purposes. That might change with today's announcement from Microsoft and Quantinuum, who say they've developed the most error-free quantum computing system yet.

While classical computers and electronics rely on binary bits as their basic unit of information (they can be either on or off), quantum computers work with qubits, which can exist in a superposition of two states at the same time. The trouble with qubits is that they're prone to error, which is the main reason today's quantum computers (known as Noisy Intermediate Scale Quantum [NISQ] computers) are just used for research and experimentation.

Microsoft's solution was to group physical qubits into virtual qubits, which allows it to apply error diagnostics and correction without destroying them, and run it all over Quantinuum's hardware. The result was an error rate that was 800 times better than relying on physical qubits alone. Microsoft claims it was able to run more than 14,000 experiments without any errors.

According to Jason Zander, EVP of Microsoft's Strategic Missions and Technologies division, this achievement could finally bring us to "Level 2 Resilient" quantum computing, which would be reliable enough for practical applications.

"The task at hand for the entire quantum ecosystem is to increase the fidelity of qubits and enable fault-tolerant quantum computing so that we can use a quantum machine to unlock solutions to previously intractable problems," Zander wrote in a blog post today. "In short, we need to transition to reliable logical qubits — created by combining multiple physical qubits together into logical ones to protect against noise and sustain a long (i.e., resilient) computation."

Microsoft's announcement is a "strong result," according to Aram Harrow, a professor of physics at MIT focusing on quantum information and computing. "The Quantinuum system has impressive error rates and control, so it was plausible that they could do an experiment like this, but it's encouraging to see that it worked," he said in an e-mail to Engadget. "Hopefully they'll be able to keep maintaining or even improving the error rate as they scale up."

Microsoft Quantum Computing
Microsoft

Researchers will be able to get a taste of Microsoft's reliable quantum computing via Azure Quantum Elements in the next few months, where it will be available as a private preview. The goal is to push even further to Level 3 quantum supercomputing, which will theoretically be able to tackle incredibly complex issues like climate change and exotic drug research. It's unclear how long it'll take to actually reach that point, but for now, at least we're moving one step closer towards practical quantum computing.

"Getting to a large-scale fault-tolerant quantum computer is still going to be a long road," Professor Harrow wrote. "This is an important step for this hardware platform. Along with the progress on neutral atoms, it means that the cold atom platforms are doing very well relative to their superconducting qubit competitors."

This article originally appeared on Engadget at https://www.engadget.com/microsoft-may-have-finally-made-quantum-computing-useful-164501302.html?src=rss

Instagram is working on new Reels feed that combines two users’ interests

Instagram is working on a feature that would recommend Reels to you and a friend based on videos you've shared with each other and your individual interests. Reverse engineer Alessandro Paluzzi unearthed the feature, which is called Blend. Instagram confirmed to TechCrunch that it's testing Blend internally and it hasn't started trialing it publicly. It may be the case that Blend never sees the light of day, though it's always intriguing to find out about the ideas Instagram is toying with.

The platform hasn't revealed more details about how Blend will work, though the idea seems to be that Instagram users and one of their besties will discover new Reels together instead of one of them finding a video they like and DMing it to the other. It would make sense for Blend to have an indicator that the other person has already seen a particular Reel so that the two people who have access to the feed can start chatting about it. 

TikTok doesn't have a feature along these lines, as TechCrunch notes, so Blend could give Instagram an advantage when it comes to folks who like to check out short-form videos together. As with many of the other features platforms of this ilk introduce, Blend fundamentally seems to be about increasing engagement.

This article originally appeared on Engadget at https://www.engadget.com/instagram-is-working-on-new-reels-feed-that-combines-two-users-interests-192018928.html?src=rss

Instagram is working on new Reels feed that combines two users’ interests

Instagram is working on a feature that would recommend Reels to you and a friend based on videos you've shared with each other and your individual interests. Reverse engineer Alessandro Paluzzi unearthed the feature, which is called Blend. Instagram confirmed to TechCrunch that it's testing Blend internally and it hasn't started trialing it publicly. It may be the case that Blend never sees the light of day, though it's always intriguing to find out about the ideas Instagram is toying with.

The platform hasn't revealed more details about how Blend will work, though the idea seems to be that Instagram users and one of their besties will discover new Reels together instead of one of them finding a video they like and DMing it to the other. It would make sense for Blend to have an indicator that the other person has already seen a particular Reel so that the two people who have access to the feed can start chatting about it. 

TikTok doesn't have a feature along these lines, as TechCrunch notes, so Blend could give Instagram an advantage when it comes to folks who like to check out short-form videos together. As with many of the other features platforms of this ilk introduce, Blend fundamentally seems to be about increasing engagement.

This article originally appeared on Engadget at https://www.engadget.com/instagram-is-working-on-new-reels-feed-that-combines-two-users-interests-192018928.html?src=rss

How Uber and the gig economy changed the way we live and work

Gig work predates the internet. Besides traditional forms of self-employment, like plumbing, offers for ad-hoc services have long been found in the Yellow Pages and newspaper classified ads, and later Craigslist and Backpage which supplanted them. Low-cost broadband internet allowed for the proliferation of computer-based gig platforms like Mechanical Turk, Fiverr and Elance, which offered just about anyone some extra pocket change. But once smartphones took off, everywhere could be an office, and everything could be a gig — and thus the gig economy was born.

Maybe it was a confluence of technological advancement and broad financial anxiety from the 2008 recession, but prospects were bad, people needed money and many had no freedom to be picky about how. This was the same era in which the phrase "the sharing economy" proliferated — at once sold as an antidote to overconsumption, but that freedom from ownership belied the more worrying commoditization of any skill or asset. Of all the companies to take advantage of this climate, none went further or have held on harder than Uber.

Uber became infamous for railroading its way into new markets without getting approval from regulators. It cemented its reputation as a corporate ne'er-do-well through a byzantine scandal to avoid regulatory scrutiny, several smaller ones over user privacy and minimally-beneficial surcharges as well as, in its infancy, an internal reputation for sexual harassment and discrimination. Early on, the company used its deep reserves of venture capital to subsidize its own rides, eating away at the traditional cab industry in a given market, only to eventually increase prices and try to minimize driver pay once it reached a dominant position. Those same reserves were spent aggressively recruiting drivers with signup bonuses and convincing them they could be their own boss.

Self-employment has a whiff of something liberatory, but Uber effectively turned a traditionally employee-based industry into one that was contractor-based. This meant that one of the first casualties of the ride-sharing boom were taxi medallions. For decades, cab drivers in many locales effectively saw these licenses as retirement plans, as they'd be able to sell them on to newcomers when it was time to hang up their flat cap. But in large part due to the influx of ride-sharing services, the value of medallions has plummeted over the last decade or so — in New York, for instance, the value of a medallion dropped from around $1 million in 2014 to $100,000 in 2021. That's in tandem with a drop in earnings, leaving many struggling to pay off enormous loans they took out to buy a medallion.

Some jurisdictions have sought to offset that collapse in medallion value. Quebec pledged $250 million CAD in 2018 to compensate cab drivers. Other regulators, particularly in Australia, applied a per-ride fee to ride-sharing services as part of efforts to replace taxi licenses and compensate medallion holders. In each of those cases, taxpayers and riders, not rideshare companies, bore the brunt of the impact on medallion holders.

At first it was just cab drivers that were hurting, but over the years, compensation for this new class of non-employee app drivers dried up too. In 2017, Uber paid $20 million to settle allegations from the Federal Trade Commission that it used false promises about potential earnings to entice drivers to join its platform. Late last year, Uber and Lyft agreed to pay $328 million to New York drivers after the state conducted a wage theft investigation. The settlement also guaranteed a minimum hourly rate for drivers outside of New York City, where drivers were already subject to minimum rates under Taxi & Limousine Commission rules.

Many rideshare drivers have also sought recognition as employees rather than contractors, so they can have a consistent hourly wage, overtime pay and benefits — efforts that the likes of Uber and rival Lyft have been fighting against. In January, the Department of Labor issued a final rule that aims to make it more difficult for gig economy companies to classify workers as independent contractors rather than employees. The EU is also weighing a provisional deal to reclassify millions of app workers as employees.

Of course, the partial erosion of an entire industry's labor market wasn't always the end goal. At one point, Uber wanted to zero out labor costs by getting rid of drivers entirely. It planned to do so by rolling out a fleet of self-driving vehicles and flying taxis.

"The reason Uber could be expensive is because you're not just paying for the car — you're paying for the other dude in the car," former CEO Travis Kalanick said in 2014, a day after Uber suggested drivers could make $90,000 per year on the platform. "When there's no other dude in the car, the cost of taking an Uber anywhere becomes cheaper than owning a vehicle. So the magic there is, you basically bring the cost below the cost of ownership for everybody, and then car ownership goes away."

Uber's grand automation plans didn't work out as intended, however. The company, under current CEO Dara Khosrowshahi, sold its self-driving car and flying taxi units in late 2020.

Uber's success had second-order effects too: despite a business model best described as "set money on fire until (fingers crossed!) a monopoly is established" a whole slew of startups were born, taking their cues from Uber or explicitly pitching themselves as "Uber for X." Sure, you might find a place to stay on Airbnb or Vrbo that's nicer and less expensive than a hotel room. But studies have shown that such companies have harmed the affordability and availability of housing in some markets, as many landlords and real-estate developers opt for more profitable short-term rentals instead of offering units for long-term rentals or sale. Airbnb has faced plenty of other issues over the years, from a string of lawsuits to a mass shooting at a rental home.

Increasingly, this is becoming the blueprint. Goods and services are exchanged by third parties, facilitated by a semi-automated platform rather than a human being. The platform's algorithm creates the thinnest veneer between choice and control for the workers who perform identical labor to the industry that platform came to replace, but that veneer allows the platform to avoid traditionally pesky things like legal liability and labor laws. Meanwhile, customers with fewer alternative options find themselves held captive by these once-cheap platforms that are now coming to collect their dues. Dazzled by the promise of innovation, regulators rolled over or signed a deal with the devil. It's everyone else who's paying the cost.


Engadget 20th anniversary banner

To celebrate Engadget's 20th anniversary, we're taking a look back at the products and services that have changed the industry since March 2, 2004.

This article originally appeared on Engadget at https://www.engadget.com/how-uber-and-the-gig-economy-changed-the-way-we-live-and-work-164528738.html?src=rss

How Uber and the gig economy changed the way we live and work

Gig work predates the internet. Besides traditional forms of self-employment, like plumbing, offers for ad-hoc services have long been found in the Yellow Pages and newspaper classified ads, and later Craigslist and Backpage which supplanted them. Low-cost broadband internet allowed for the proliferation of computer-based gig platforms like Mechanical Turk, Fiverr and Elance, which offered just about anyone some extra pocket change. But once smartphones took off, everywhere could be an office, and everything could be a gig — and thus the gig economy was born.

Maybe it was a confluence of technological advancement and broad financial anxiety from the 2008 recession, but prospects were bad, people needed money and many had no freedom to be picky about how. This was the same era in which the phrase "the sharing economy" proliferated — at once sold as an antidote to overconsumption, but that freedom from ownership belied the more worrying commoditization of any skill or asset. Of all the companies to take advantage of this climate, none went further or have held on harder than Uber.

Uber became infamous for railroading its way into new markets without getting approval from regulators. It cemented its reputation as a corporate ne'er-do-well through a byzantine scandal to avoid regulatory scrutiny, several smaller ones over user privacy and minimally-beneficial surcharges as well as, in its infancy, an internal reputation for sexual harassment and discrimination. Early on, the company used its deep reserves of venture capital to subsidize its own rides, eating away at the traditional cab industry in a given market, only to eventually increase prices and try to minimize driver pay once it reached a dominant position. Those same reserves were spent aggressively recruiting drivers with signup bonuses and convincing them they could be their own boss.

Self-employment has a whiff of something liberatory, but Uber effectively turned a traditionally employee-based industry into one that was contractor-based. This meant that one of the first casualties of the ride-sharing boom were taxi medallions. For decades, cab drivers in many locales effectively saw these licenses as retirement plans, as they'd be able to sell them on to newcomers when it was time to hang up their flat cap. But in large part due to the influx of ride-sharing services, the value of medallions has plummeted over the last decade or so — in New York, for instance, the value of a medallion dropped from around $1 million in 2014 to $100,000 in 2021. That's in tandem with a drop in earnings, leaving many struggling to pay off enormous loans they took out to buy a medallion.

Some jurisdictions have sought to offset that collapse in medallion value. Quebec pledged $250 million CAD in 2018 to compensate cab drivers. Other regulators, particularly in Australia, applied a per-ride fee to ride-sharing services as part of efforts to replace taxi licenses and compensate medallion holders. In each of those cases, taxpayers and riders, not rideshare companies, bore the brunt of the impact on medallion holders.

At first it was just cab drivers that were hurting, but over the years, compensation for this new class of non-employee app drivers dried up too. In 2017, Uber paid $20 million to settle allegations from the Federal Trade Commission that it used false promises about potential earnings to entice drivers to join its platform. Late last year, Uber and Lyft agreed to pay $328 million to New York drivers after the state conducted a wage theft investigation. The settlement also guaranteed a minimum hourly rate for drivers outside of New York City, where drivers were already subject to minimum rates under Taxi & Limousine Commission rules.

Many rideshare drivers have also sought recognition as employees rather than contractors, so they can have a consistent hourly wage, overtime pay and benefits — efforts that the likes of Uber and rival Lyft have been fighting against. In January, the Department of Labor issued a final rule that aims to make it more difficult for gig economy companies to classify workers as independent contractors rather than employees. The EU is also weighing a provisional deal to reclassify millions of app workers as employees.

Of course, the partial erosion of an entire industry's labor market wasn't always the end goal. At one point, Uber wanted to zero out labor costs by getting rid of drivers entirely. It planned to do so by rolling out a fleet of self-driving vehicles and flying taxis.

"The reason Uber could be expensive is because you're not just paying for the car — you're paying for the other dude in the car," former CEO Travis Kalanick said in 2014, a day after Uber suggested drivers could make $90,000 per year on the platform. "When there's no other dude in the car, the cost of taking an Uber anywhere becomes cheaper than owning a vehicle. So the magic there is, you basically bring the cost below the cost of ownership for everybody, and then car ownership goes away."

Uber's grand automation plans didn't work out as intended, however. The company, under current CEO Dara Khosrowshahi, sold its self-driving car and flying taxi units in late 2020.

Uber's success had second-order effects too: despite a business model best described as "set money on fire until (fingers crossed!) a monopoly is established" a whole slew of startups were born, taking their cues from Uber or explicitly pitching themselves as "Uber for X." Sure, you might find a place to stay on Airbnb or Vrbo that's nicer and less expensive than a hotel room. But studies have shown that such companies have harmed the affordability and availability of housing in some markets, as many landlords and real-estate developers opt for more profitable short-term rentals instead of offering units for long-term rentals or sale. Airbnb has faced plenty of other issues over the years, from a string of lawsuits to a mass shooting at a rental home.

Increasingly, this is becoming the blueprint. Goods and services are exchanged by third parties, facilitated by a semi-automated platform rather than a human being. The platform's algorithm creates the thinnest veneer between choice and control for the workers who perform identical labor to the industry that platform came to replace, but that veneer allows the platform to avoid traditionally pesky things like legal liability and labor laws. Meanwhile, customers with fewer alternative options find themselves held captive by these once-cheap platforms that are now coming to collect their dues. Dazzled by the promise of innovation, regulators rolled over or signed a deal with the devil. It's everyone else who's paying the cost.


Engadget 20th anniversary banner

To celebrate Engadget's 20th anniversary, we're taking a look back at the products and services that have changed the industry since March 2, 2004.

This article originally appeared on Engadget at https://www.engadget.com/how-uber-and-the-gig-economy-changed-the-way-we-live-and-work-164528738.html?src=rss

Snapchat’s latest paid perk is an AI Bitmoji of your pet

Snapchat has a new AI-powered perk for subscribers: Bitmoji versions of your pet. The feature, which is unfortunately not called “petmoji,” allows users to snap a photo of their four-legged friend to create a cartoon-like avatar to accompany their Bitmoji in the Snap Map.

Based on screenshots shared by the company, it seems users will be able to choose from a few different variations of the AI-generated images after sharing a photo of their pet. That’s considerably less customization than what you can do with your own human-inspired Bitmoji,though it should allow users to create something that looks similar to their IRL pet. (No word on if Snap could one day introduce branded pet accessories for animal avatars like they do for human Bitmoji.)

The addition is also the latest example of how Snap has embraced AI features in its subscription offering. Since debuting Snapchat+ in 2022, the company has used the premium service to experiment with generative AI features, including its MyAI assistant as well as camera-powered features like Dreams and AI-generated snaps. Snapchat+ has more than 7 million subscribers, the company announced in December.

Elsewhere, Snap added some updates for non-subscribers, too. The app is adding a new template feature to make it easier to edit clips, and new swipe-based gestures to send and edit snaps more quickly. Snapchat will also support longer video uploads for Stories and Spotlight. In-app captures can now be three minutes long, while the app will support uploads of up to five minutes.

This article originally appeared on Engadget at https://www.engadget.com/snapchats-latest-paid-perk-is-an-ai-bitmoji-of-your-pet-235027028.html?src=rss

Snapchat’s latest paid perk is an AI Bitmoji of your pet

Snapchat has a new AI-powered perk for subscribers: Bitmoji versions of your pet. The feature, which is unfortunately not called “petmoji,” allows users to snap a photo of their four-legged friend to create a cartoon-like avatar to accompany their Bitmoji in the Snap Map.

Based on screenshots shared by the company, it seems users will be able to choose from a few different variations of the AI-generated images after sharing a photo of their pet. That’s considerably less customization than what you can do with your own human-inspired Bitmoji,though it should allow users to create something that looks similar to their IRL pet. (No word on if Snap could one day introduce branded pet accessories for animal avatars like they do for human Bitmoji.)

The addition is also the latest example of how Snap has embraced AI features in its subscription offering. Since debuting Snapchat+ in 2022, the company has used the premium service to experiment with generative AI features, including its MyAI assistant as well as camera-powered features like Dreams and AI-generated snaps. Snapchat+ has more than 7 million subscribers, the company announced in December.

Elsewhere, Snap added some updates for non-subscribers, too. The app is adding a new template feature to make it easier to edit clips, and new swipe-based gestures to send and edit snaps more quickly. Snapchat will also support longer video uploads for Stories and Spotlight. In-app captures can now be three minutes long, while the app will support uploads of up to five minutes.

This article originally appeared on Engadget at https://www.engadget.com/snapchats-latest-paid-perk-is-an-ai-bitmoji-of-your-pet-235027028.html?src=rss

You can now use your phone to get started with Amazon’s palm-reading tech

Amazon just launched an app that lets people sign up for its palm recognition service without having to head to an in-store kiosk. The Amazon One app uses a smartphone’s camera to take a photo of a palm print to set up an account. Once signed up, you can pay for stuff by using just your hand, ending the tyranny of having to carry a smartphone, cash or a burdensome plastic card.

The tech uses generative AI to analyze a palm's vein structure, turning the data into a “unique numerical, vector representation” which is recognized by scanning machines at retail locations. You’ll have to add a payment method within the app to get started and upload a photo of your ID for the purpose of age verification.

The app launches today for iOS and Android. Previously, you’d have to go to a physical location to sign up for Amazon One. Beyond payments, the tech is also used as an age verification tool and as a way to enter concerts and sporting events without having to bring along a ticket.

Once you hand over your palm-print to the completely benevolent Amazon corporation, you’ll have unfettered access to each and every Whole Foods grocery store throughout the country. Amazon, after all, owns Whole Foods. Amazon One payments are also accepted at some Panera Bread locations, in addition to certain airports, stadiums and convenience stores.

There are obvious privacy concerns here, as passwords can change but palms cannot. Amazon says that all uploaded palm images are “encrypted and sent to a secure Amazon One domain” in the Amazon Web Service cloud. The company also says the app “includes additional layers of spoof detection,” noting that it’s not possible to save or download palm images to the phone itself.

This article originally appeared on Engadget at https://www.engadget.com/you-can-now-use-your-phone-to-get-started-with-amazons-palm-reading-tech-184814302.html?src=rss

You can now use your phone to get started with Amazon’s palm-reading tech

Amazon just launched an app that lets people sign up for its palm recognition service without having to head to an in-store kiosk. The Amazon One app uses a smartphone’s camera to take a photo of a palm print to set up an account. Once signed up, you can pay for stuff by using just your hand, ending the tyranny of having to carry a smartphone, cash or a burdensome plastic card.

The tech uses generative AI to analyze a palm's vein structure, turning the data into a “unique numerical, vector representation” which is recognized by scanning machines at retail locations. You’ll have to add a payment method within the app to get started and upload a photo of your ID for the purpose of age verification.

The app launches today for iOS and Android. Previously, you’d have to go to a physical location to sign up for Amazon One. Beyond payments, the tech is also used as an age verification tool and as a way to enter concerts and sporting events without having to bring along a ticket.

Once you hand over your palm-print to the completely benevolent Amazon corporation, you’ll have unfettered access to each and every Whole Foods grocery store throughout the country. Amazon, after all, owns Whole Foods. Amazon One payments are also accepted at some Panera Bread locations, in addition to certain airports, stadiums and convenience stores.

There are obvious privacy concerns here, as passwords can change but palms cannot. Amazon says that all uploaded palm images are “encrypted and sent to a secure Amazon One domain” in the Amazon Web Service cloud. The company also says the app “includes additional layers of spoof detection,” noting that it’s not possible to save or download palm images to the phone itself.

This article originally appeared on Engadget at https://www.engadget.com/you-can-now-use-your-phone-to-get-started-with-amazons-palm-reading-tech-184814302.html?src=rss