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Interview: Researching quantum algorithms for today’s devices | Computer Weekly

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Interview: Researching quantum algorithms for today’s devices | Computer Weekly


While the billion-dollar question is about when quantum computing will become commercially viable, among the problems being tackled at the moment is how to make the most of current technology, where quantum devices experience a high error rate.

Although the industry can produce machines with hundreds of physical qubits, the actual number of logical, error-free qubits available in the latest quantum computers remains very small.

As the technology improves, researchers are investigating how to get the best out of today’s noisy quantum computers and considering the types of problems that quantum devices with large numbers of logical qubits could solve. 

Simulations for drug discovery

Lucy Robson is a quantum algorithm scientist at Universal Quantum. She is part of a team looking at how quantum computing could be applied in drug discovery.

Speaking to Computer Weekly about her work, Robson says: “Our focus is not just about looking at quantum algorithms, which can implement real-world use cases, but it’s also about understanding how we can build high-performance quantum error correction, and in particular, how we can get advantages for Universal Quantum’s scalable trapped ion quantum computing hardware through clever design of error correction protocols.”

Considering the challenges of quantum simulations for drug discovery, Robson says a large-scale fault-tolerant quantum computer is needed: “This is something which is many orders of magnitude larger than the hardware that we currently have at the moment.

“We’re talking about needing hundreds of thousands or millions of qubits to be able to support the overhead of quantum error correction at the scale that we would need to execute very large algorithms, and what we’re seeing broadly is a real push to try to understand how far away we are from fault tolerant quantum computing.” 

Robson says this problem is not solely a hardware issue. “It is also about considering what application developers need – the middleware and software tools that will be needed for people who are domain experts in computational chemistry to be able to make use of these quantum devices themselves,” she adds.

Rather than a treating a quantum computer as an esoteric and specialised device that can only be operated by people with a very specific skill set, Robson hopes such tooling will open up quantum computing to software engineers who are not experts in quantum computing. 

Robson’s work is currently focused on a specific use case for quantum computing that looks at how quantum algorithms can accelerate the simulation of chemical properties – specifically, quantum chemistry for the drug discovery process.

Last year, Universal Quantum announced it was collaborating with the Open Quantum Institute (OQI) on using quantum computing in drug discovery. The team has been investigating how quantum simulations might accelerate the discovery of novel, non-hormonal treatments for endometriosis, a disabling and progressive condition that affects around 10% of women globally.
 
According to Robson, the average time to diagnosis in the UK is between seven and 10 years: “This is really symptomatic of systemic underfunding for women’s health in general. While we originally started out on quantum algorithms, one of the great use cases for this is simulation of physical systems and quantum chemistry, and one of the main applications of quantum chemistry is in pharmaceuticals and drug discovery.”

Understanding quantum

For people who have not encountered quantum mechanics – the phenomenon that enables quantum computers to run computation beyond the realms of the most powerful supercomputers – the concepts it embodies such as superposition are mindboggling. “It’s certainly counterintuitive,” Robson adds.

She recalls the advice Nobel laureate and physicist Roger Penrose gave in the foreword of a book she was reading about learning difficult concepts: “I remember picking up one of his books when I was about 16 years old, just about to start A-level maths, so I was quite unfamiliar with a lot of the notation and the terminology that was being used.

“In the short time that I’ve been involved in the field, I’ve seen things I had read about as a theory paper now being published experimentally”

Lucy Robson, Universal Quantum

“His advice for dealing with any sort of new or strange formula that you haven’t seen before is to try to get an intuitive understanding. That may not be about reading the equation or understanding the terminology, but reading a description, looking at a diagram and trying to get some concept in your mind of what this thing is actually trying to describe, and then go back and learn the notation and learn the formula.”

She says this approach has always served her well: “It is a thing that I always do when I find something new and unfamiliar.”

Her advice to software developers who want to get into quantum algorithms is to understand linear algebra: “Many of the concepts seem strange and alien. But I had the benefit of coming from a degree where we did a lot of linear algebra, so I would argue that one of the strongest prerequisites that you do need for quantum algorithms, in particular, is to feel comfortable with linear algebra.”

Robson’s journey to quantum computer began when she started exploring the subject. “There was this wealth of new material that was available, so I started trying to understand what on Earth is quantum, and I discovered that there’s an enormous crossover between quantum computing and theoretical computer science. That’s really what really got me hooked,” she says, recalling her experience as a self-taught programmer, reading RFCs (request for comments), and her work in cyber security after studying computer science.

Robson then had the opportunity to work on a small scale project looking at applications of quantum computing for the defence sector. 

Robson is confident the technology will eventually work commercially. “In the short time that I’ve been involved in the field, I’ve seen things I had read about as a theory paper now being published experimentally,” she says, adding that this shows how much has been achieved in the past decade.

Specifically, Robson says she is extremely pleased to see there is now sustained long-term investment coming from the UK government. The company she works for, Universal Quantum, was spun out of Sussex university and received a grant of £7.5m as part of Innovate UK’s Strategy Challenge Fund in 2021.

“In the UK, we have a phenomenal National Quantum Technologies programme,” she adds, pointing out that progress is being made not only on quantum computing hardware but also software and tooling. “One of the things that’s quite encouraging for me is seeing how the ecosystem is growing at pace alongside the developments in hardware and theory.”

Listen to the podcast with Lucy Robson here >>



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Get Peace of Mind With This GPS and Activity Tracker for Pets

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Get Peace of Mind With This GPS and Activity Tracker for Pets


Within the app, you can add safe zones, more pets with Fi trackers, and other users who can also track and monitor the pet. There’s a Health tab where you can add and store things like vet records, receipts, and insurance information, and add vets to easily share your pet’s documents and get appointment reminders. You can also set up the Fi app on your Apple Watch to have even quicker access to monitor your pet’s location, activity, and safety (including Lost Mode) without needing a phone.

When you open the app, you’ll see a map with live tracking showing where your pet is currently, as well as a notification of the last time they were outside and where they were. With the latter, you can pull up stats like location timeline, showing where they were and when. If you dive into any day when the tracker left the home, it will recreate the route, following the path and calculating the distance the pet traveled.

There’s also health-monitoring data from activity and sleep tracking, which is most useful for an indoor-only pet like mine. Like other health-tracking collars, stats for sleep and activity aren’t 100 percent accurate, as the app uses GPS to track movement, categorizing “activity” when the animal is moving and “sleep” when the pet is still for a prolonged period. This means that if Basil was awake but stationary, the app may inaccurately categorize this as sleep.

Fi Mini App source Molly Higgins

In the Rest tab, you can see sleep metrics, including a daily summary of deep sleep, naps, and interruptions during nightly sleep. You can compare this over time, and the app notes how much more or less Basil slept than the night before. It also compares stats historically, by week, month, and year, so you can track trends and better understand your pet’s normal sleep schedule.

The Activity tab is similar, tracking activity by day, week, and month, noting in the day’s timeline when the pet was most active and for how long. This also compares activity to the day before. I liked looking at the weekly report, comparing days during the week to see which he was most active during and if any patterns in activity popped up.

For example, I noticed that his sleep-versus-activity schedule was similar to mine, except he was active between 4:45 and 6:30 am (while I was still asleep), because that’s when his automatic feeder goes off for breakfast and my roommate is getting ready to leave for work. He was most active in the evenings, when I feed him dinner, have dedicated playtime, and my roommates are home, so there’s more activity to keep him awake. Historical comparison is also a super helpful way to track whether your pet is sleeping more or becoming more lethargic—an early warning sign of a bigger health problem.

Not Without Its Quirks

Since my cat is indoor-only, I ran some experiments to track location, using GPS on both the Fi Mini tracker and my phone. I also had a friend take the tracker out without my phone nearby to see whether I’d get pinged that “Basil” had left the safe zone.

Although it is better than not being alerted at all, the Fi’s GPS has limitations (as did the Tractive tracker I tested). It needs a strong signal to communicate with cell towers for accurate location. If your phone is close to the smart collar (via Bluetooth), it uses that instead of the Fi’s GPS, making it more accurate and alerting quicker. If the pet gets loose and is out of range of your phone, it uses the collar’s cellular antenna (in this case, Verizon cell towers). But because the Fi’s antenna isn’t as strong as a phone’s, location accuracy is lower, and the connection can be very spotty, especially if your pet is in the country or on acreage where cell towers are farther away.



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This AI Button Wearable From Ex-Apple Engineers Looks Like an iPod Shuffle

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This AI Button Wearable From Ex-Apple Engineers Looks Like an iPod Shuffle


The other goal of the Button is rapid response time. Unlike the Humane Ai pin, which got lots of criticism for taking a painfully long time to reply to queries, the Button is designed to be nearly instantaneous. In a demo via Zoom call, I watched Nolet ask the Button for a recommendation for the best sandwich shops in my neighborhood. While the Button didn’t choose my idea of the best sandwich place around, it did at least answer all the questions within a second. It can also be immediately interrupted by pressing the button, which is a great feature for people like me who cannot tell a chatbot to shut up fast enough.

Nolet is unapologetic about the very clear Apple ethos you might be able to suss out in the design.

“The Humane pin felt a little geeky to wear, right?” Nolet says. “But the iPod shuffle? Really cool. That’s where the idea started, and then we just put all of our Apple-esque expertise into it and tried to refine it into something that we thought would actually be useful.”

Nearly all their product images and videos show the Button being used as a wearable, but Nolet insists the device can also be kept in a pocket, bag, or car glove box as well.

“My cofounder says we can’t tell people it looks cool; they have to decide,” Nolet says. “Our intention is to build something that is kind of fashionable, but it’s up to you guys to tell us if it’s cool.”

Though Apple has long been a leader in technological coolness, it has struggled in the virtual reality space, specifically with its too expensive, too heavy Vision Pro and that devices complicated rollout. Apple is not alone on that front. Meta is actively rejiggering support for its VR efforts. Nolet posits that part of the reason for that instability is that VR has required building hardware and the software ecosystems to support it at the same time.

“There was no software innovation that we were anchored to as an industry, so I think it’s quite a hard pitch,” Nolet says. “It’s much, much easier to stand on the shoulders of giants.”

Courtesy of Button



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Conflicting Rulings Leave Anthropic in ‘Supply-Chain Risk’ Limbo

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Conflicting Rulings Leave Anthropic in ‘Supply-Chain Risk’ Limbo


Anthropic “has not satisfied the stringent requirements” to temporarily lose the supply-chain-risk designation imposed by the Pentagon, a US appeals court in Washington, DC, ruled on Wednesday. The decision is at odds with one issued last month by a lower court judge in San Francisco, and it wasn’t immediately clear how the conflicting preliminary judgments would be resolved.

The government sanctioned Anthropic under two different supply-chain laws with similar effects, and the San Francisco and Washington, DC, courts are each ruling on only one of them. Anthropic has said it is the first US company to be designated under the two laws, which are typically used to punish foreign businesses that pose a risk to national security.

“Granting a stay would force the United States military to prolong its dealings with an unwanted vendor of critical AI services in the middle of a significant ongoing military conflict,” the three-judge appellate panel wrote on Wednesday in what they described as an unprecedented case. The panel said that while Anthropic may suffer financial harm from the ongoing designation, they did not want to risk “a substantial judicial imposition on military operations” or “lightly override” the military’s judgments on national security.

The San Francisco judge had found that the Department of Defense likely acted in bad faith against Anthropic, driven by frustration over the AI company’s proposed limits on how its technology could be used and its public criticism of those restrictions. The judge ordered the supply-chain risk label removed last week, and the Trump administration complied by restoring access to Anthropic AI tools inside the Pentagon and throughout the rest of the federal government.

Anthropic spokesperson Danielle Cohen says the company is grateful the Washington, DC, court “recognized these issues need to be resolved quickly” and remains confident “the courts will ultimately agree that these supply chain designations were unlawful.”

The Department of Defense did not immediately respond to a request for comment, but acting attorney general Todd Blanche posted a statement on X. “Today’s DC Circuit stay allowing the government to designate Anthropic as a supply-chain risk is a resounding victory for military readiness,” he wrote.
“Our position has been clear from the start—our military needs full access to Anthropic’s models if its technology is integrated into our sensitive systems.

Military authority and operational control belong to the Commander-in-Chief and Department of War, not a tech company.”

The cases are testing how much power the executive branch has over the conduct of tech companies. The battle between Anthropic and the Trump administration is also playing out as the Pentagon deploys AI in its war against Iran. The company has argued it is being illegally punished for insisting that its AI tool Claude lacks the accuracy needed for certain sensitive operations such as carrying out deadly drone strikes without human supervision.

Several experts in government contracting and corporate rights have told WIRED that Anthropic has a strong case against the government, but the courts sometimes refuse to overrule the White House on matters related to national security. Some AI researchers have said the Pentagon’s actions against Anthropic “chills professional debate” about the performance of AI systems.

Anthropic has claimed in court that it lost business because of the designation, which government lawyers contend bars the Pentagon and its contractors from using the company’s Claude AI as part of military projects. And as long as Trump remains in power, Anthropic may not be able to regain the significant foothold it held in the federal government.

Final decisions in the company’s two lawsuits could be months away. The Washington court is scheduled to hear oral arguments on May 19.

The parties have revealed minimal details so far about how exactly the Department of Defense has used Claude or how much progress it has made in transitioning staff to other AI tools from Google DeepMind, OpenAI, or others. The military, which under President Trump calls itself the Department of War, has said it has taken steps to ensure Anthropic can’t purposely try to sabotage its AI tools during the transition.

Update 4/8/26 7:27 EDT: This story has been updated to include a statement form acting attorney general Todd Blanche.



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