Quantum computing will not be replacing supercomputers in 2026, let alone reaching industrial scale. And yet, investor appetite for companies pursuing the elusive quantum advantage hasn’t dwindled — it has increased.
Quantonation Ventures, a venture firm investing in quantum and physics-based startups, has closed its oversubscribed second fund at €220 million, or approximately $260 million. That’s more than twice the size of its inaugural fund, and comes in addition to other signals that the quantum winter isn’t coming yet.
While some warned that too much quantum hype and not enough tangible outcomes would eventually cause funding to collapse, the opposite has happened. Take the prediction that quantum will eventually crack modern encryption: that moment has no clear timeline, and yet governments have joined Big Tech in the race.
In the years since Quantonation’s launch in 2018, the quantum technology sector has become less incipient, with both technological breakthroughs and early demand from academic and industrial labs. As a result, there has also been “a shift in the types of investment opportunities that are available” to its second fund, Quantonation partner Will Zeng told TechCrunch.
One example is what Zeng describes as the “picks and shovels” opportunity, with companies developing technologies that support the quantum industry. He cited the example of Dutch startup Qblox, a long-boostrapped company that was selling quantum control hardware and software to Quantonation portfolio companies before the VC firm co-led its Series A.
This growing ecosystem also explains why backers are doubling down on Quantonation, and why other dedicated quantum funds such as QDNL and 55 North have emerged.
“VCs recognize that this is not an easy area to invest in at the early stage. The technology is very specific and complex, the markets are often new, and the teams as well,” Zeng said.
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The firm’s thesis is to invest early to capture more value; but a handful of quantum companies have already gone public, and their shares have surged in recent months. According to Bloomberg, this “quantum frenzy” is partly stocked by Nvidia, whose CEO Jensen Huang declared in June 2025 that “quantum computing is reaching an inflection point.”
Despite the fact that quantum chips have yet to outperform classical computers outside of purpose-built benchmarks, consensus is growing that real-life applications are only a few years away, from life sciences to new materials. That’s in part thanks to advancements in error correction — the ability to fix the mistakes that quantum systems are prone to.
Google’s Willow chip was a landmark for error correction in 2024, but no architecture has won yet, and smaller players are still in the race. Zeng noted that a surprising number of companies have entered DARPA’s Quantum Benchmarking Initiative. He also believes that beyond the public market excitement, “there are more exciting technologies that are currently private.”
For Quantonation, those private opportunities span a wider canvas than quantum chips alone. Fund two has already invested in 12 startups, with a target portfolio of around 25, covering not just the software and industrial layers needed to make quantum advantage real, but also adjacent physics-based technologies such as photonics and lasers.
This expanded thesis is backed by investors old and new. According to the firm, major investors from its first vintage, including Singapore’s Vertex Holdings and Bpifrance’s Fonds National d’Amorçage 2, have returned for the second fund, with new limited partners including the European Investment Fund, Grupo ACS, Novo Holdings, Planet First Partners, and Toshiba.
Quantonation’s geographic scope is equally international. With dual headquarters in Paris and New York City, the firm has backed French quantum companies including Pasqal and Quandela, but also placed bets in Asia and North America — and will continue doing so.
“In a lot of the areas we invest in, there’s not yet a clear regional winner, […] and a lot of the research has come from universities in many places,” Zeng said.
Quantum computing has grabbed the attention of many investors over the past few years as they seek new tech trends beyond artificial intelligence (AI). The possibility of a quantum computing market that could be worth as much as $170 billion by 2040, as consulting firm BCG projects, certainly sounds promising.
That type of optimism has helped lift IonQ(NYSE: IONQ) stock 503% higher over the past three years. But lately, things haven’t been as rosy for IonQ shareholders, as the stock has fallen about 9% over the past 12 months.
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So, where is IonQ headed over the next year? If you’re a shareholder, I don’t think things look too good.
Image source: Getty Images.
In the first nine months of 2025, IonQ’s losses increased tenfold year over year, from just $129 million to nearly $1.3 billion. The biggest culprits were its general and administration costs, which tripled, and its research and development expenses, which more than doubled.
Building a quantum computing company at this early stage of the industry is expensive. But such a rapid increase in costs and significantly widening losses are still problematic because IonQ is also having a difficult time generating organic revenue.
Yes, the company’s sales rose by 117% in the first nine months of 2025 to $68.1 million. But the majority of those added revenues derived from the five companies it acquired last year, rather than from organic growth in its quantum computing revenue. And those acquisitions were paid for, in part, by IonQ issuing new shares, which resulted in significant shareholder dilution.
With the company’s losses expanding, its sales growing mainly via acquisitions, and the company funding its purchases by issuing new shares, IonQ doesn’t exactly have a recipe for financial success in place.
Making matters worse for IonQ shareholders is the fact that many investors are beginning to rotate out of riskier assets in search of safer investments.
Software stocks, cryptocurrencies, and quantum computing stocks are just some of the areas that are feeling this pinch right now — and it’s likely to continue. Artificial intelligence has the potential to disrupt so many companies and industries that some investors are second-guessing the thesis for tech investments.
That’s not IonQ’s fault, of course, but it is a problem for the company nonetheless. And it comes at a time when its stock trades at an expensive premium. IonQ has a price-to-sales (P/S) ratio of 106, compared to the tech sector’s average of just 8.
When you add all this up, there’s little to get excited about regarding IonQ over the next year.
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Chris Neiger has no position in any of the stocks mentioned. The Motley Fool has positions in and recommends IonQ. The Motley Fool has a disclosure policy.
Fans of quantum computing stocks are no doubt familiar with quantum computing unit (QCU) maker Rigetti Computing (NASDAQ: RGTI). The quantum chipmaker has won several fans and seen its share price soar over the past year. But Rigetti’s stock is now trading more than 60% off its 2025 high, and it’s even given back all of the gains it’s made so far in 2026.
So is now a good time to buy this up-and-coming quantum computing stock?
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The quantum computing industry is still in its infancy. But that hasn’t stopped companies from jumping into it. Start-ups like Rigetti are competing with tech giants like Alphabet‘s Google and IBM to develop the tech that could become a commercially viable product.
Image source: Getty Images.
Essentially, all these companies are trying to optimize their quantum computers on three separate metrics: speed, accuracy, and scale. Speed refers to the amount of time it takes a quantum system to manipulate a quantum particle at a “quantum gate,” and then to move it to the next gate and prepare it for its next computation.
Accuracy is commonly measured by “two-qubit gate fidelity,” and refers to the percentage of computations that are error-free within the system. Scale is the number of physical qubits in a quantum system. The difficulty for all quantum companies is that as scale and speed increase, accuracy tends to decrease.
It seems likely that the companies able to maximize their systems’ performance through a combination of speed, accuracy, and scale are most likely to be among quantum computing’s big winners. How does Rigetti compare to its rivals in this regard?
The speed of Rigetti’s systems is quite impressive. It claims that its 108-qubit system — roughly the largest-scale system available today — has achieved gate speeds of 50-70 nanoseconds. That’s incredibly fast.
But the median accuracy of that 108-qubit system is only 99% as measured by two-qubit gate fidelity. That may sound like a great rate, but in the world of quantum computing, differences of even 0.01% are significant.
The company’s smaller systems are more accurate, though. Its 36-qubit system has achieved two-qubit gate fidelity of 99.6%, and its 9-qubit system has reached 99.7%. The problem here is that rival IonQ (NYSE: IONQ) boasts that it has achieved 99.99% fidelity in a 100-qubit system. To be fair, though, IonQ’s systems, although much more accurate than Rigetti’s, are much slower.
Rigetti CEO Dr. Subodh Kulkarni said last month in a press release that the company has “a clear understanding of what we need to do to achieve 99.5% median two-qubit gate fidelity” in its Cepheus-1-108Q system, which is set to be released this quarter. But even if it can achieve that benchmark, there’s still a long way to go.
Image source: Getty Images.
For a quantum computer to be commercially viable, it’s estimated to need at least 1 million physical qubits and 99.99% two-qubit gate fidelity (and probably closer to 99.99999%). So we’re still a long way from quantum computing becoming mainstream.
Rigetti believes it’s on track to develop a system with 1,000 qubits by 2027 with 99.7% two-qubit gate fidelity, but hasn’t given longer-term estimates. Rival IonQ is targeting a 10,000-qubit system by 2027 and a 2 million-qubit system by 2030. If Rigetti scaled up on a similar trajectory, it would achieve a 200,000-qubit system by 2030 and surpass the 1 million-qubit threshold by 2031.
But there’s no way to know how accurate such a massive system would be, nor whether Rigetti can beat IonQ to the punch as well as deep-pocketed rivals like Google and IBM.
So, is Rigetti a buy now? Nobody but the most risk-tolerant investors should even consider it: The company is too speculative, and a lot can change between now and 2030.
Image source: Getty Images.
On the bright side, according to data from McKinsey & Company, the quantum computing market could be as large as $72 billion by 2030. If Rigetti can control a large enough piece of that pie, it could be a huge winner from here. But a lot would have to go Rigetti’s way for that to happen, and right now there’s no way to know how things will shake out in this rapidly developing field.
For investors who want to buy into the quantum computing trend early, Rigetti isn’t a bad choice, but it’s probably not a good idea to put all your eggs in one (quantum) basket. I would rather take a small stake in Rigetti alongside other quantum computing companies, or invest in a quantum computing ETF so I could give myself the best odds of picking a winner. And I definitely wouldn’t invest money I couldn’t afford to lose.
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John Bromels has positions in Alphabet. The Motley Fool has positions in and recommends Alphabet, International Business Machines, and IonQ. The Motley Fool has a disclosure policy.
From ransomware to quantum disruption, Canada must take urgent steps to defend its institutions and build long-term cyber capacity. Observer Labs
This Q&A is part of Observer’s Expert Insights series, where industry leaders, innovators and strategists distill years of experience into direct, practical takeaways and deliver clarity on the issues shaping their industries. At a moment when cyber threats are escalating alongside geopolitical tensions, Canada finds itself at a crossroads: how to defend its digital infrastructure, protect its economy and maintain global competitiveness while preserving the values of an open, democratic society.
Judith Borts, senior director of the Rogers Cybersecure Catalyst at Toronto Metropolitan University,sits at the intersection of policy, security and economic strategy. With a career spanning provincial economic development, national innovation policy and cross-sector collaboration, Borts has become one of Canada’s most vocal advocates for treating cybersecurity not as a niche technical specialty but as a shared societal responsibility—one that will determine the country’s digital sovereignty in the years ahead.
Her work at the Catalyst focuses on building the talent, partnerships and operational capacity Canada needs to withstand increasingly sophisticated attacks. But it’s her policy background that gives her a panoramic view of what’s at stake. Canada, she argues, can no longer afford a reactive approach to cyber risk. Nation-state adversaries, criminal networks and A.I.-accelerated threats are moving faster than traditional governance models can respond, and the downstream costs to Canadians are already enormous.
Borts outlines where Canada is falling behind global peers, what a truly unified national cyber strategy would require and why talent development may ultimately matter more than any single technological breakthrough. She also offers a candid look at the sectors most vulnerable today, the policies needed to strengthen resilience and how emerging technologies like A.I. and quantum computing will reshape the country’s digital future. Canada’s prosperity increasingly depends on something once viewed as purely defensive: a secure and trusted digital ecosystem.
With global alliances shifting and the U.S. pulling back from international cooperation, how are these geopolitical tensions directly reshaping Canada’s cybersecurity priorities and its role in intelligence-sharing networks?
Even as global alliances shift, intelligence sharing through networks like the Five Eyes, G7 and NATO remains strong. That’s not really where Canada’s biggest challenge is. What we really need to zero in on is building our own sovereign defence and resilience—including in the cyber and digital domains—so we can protect ourselves, respond quickly when threats come up and recover safely and securely.
Cyberattacks today can come from anywhere (foreign governments, organized groups or even individuals), and they pose real risks to Canadian institutions, businesses and citizens. Our national security and defence strategies need to reflect that reality. We need to invest more in homegrown talent and innovation, from cybersecurity research to advances in A.I. and quantum technologies, so that Canada can stay ahead of the curve. It’s not about losing trust in our allies; it’s about maintaining our strong relationships while also making sure we have the strength and resilience to stand on our own when it matters most.
Which Canadian sectors are most exposed to cyber risk, and how prepared are they to defend against the sophisticated attacks we’re seeing today?
Every sector in Canada, as well as around the world, is exposed to cyber risk. Healthcare continues to face some of the most visible and alarming threats. Ransomware attacks have forced hospitals to cancel surgeries and even shut down emergency systems, putting patient safety directly at risk. The energy sector is another major target. And what used to be mainly about stealing data has now shifted to attempts to interfere with the systems that keep our power grid running. As our digital and physical infrastructure becomes more connected, those risks multiply and even a single successful attack can throw essential services across the country into chaos.
Canada’s economy is powered by small and medium-sized businesses, which make up about 99 percent of all companiesin the country and account for more than half of the country’s GDP. These companies are increasingly being targeted but often lack the specialized staff, training and resources to respond effectively. Plus, the impacts of a ransomware attack on an SMB’s bottom line can be massive.
We’re seeing progress in some areas, but these are still isolated efforts. Real national cybersecurity and resilience mean a coordinated approach, one that brings strong security standards together with real investment in education, innovation and long-term capacity building. That’s how we keep Canada’s economy secure and competitive in the years ahead.
What specific policy mechanisms are needed to create a unified national cyber strategy that also respects Canada’s diverse regional priorities?
A top-down approach alone won’t keep up with how fast threats evolve or be able to address the practical needs of all regions. Real resilience comes from bringing federal, provincial and local efforts together so we can build safe and secure communities, share information faster, respond in real time and build trust across sectors.
We also need to make it easier for Canadian businesses to operate securely, both at home and abroad. That means creating a more harmonized and less fragmented set of cyber standards and compliance requirements, so companies aren’t forced to navigate a maze of conflicting rules across jurisdictions. Taking a more unified approach that integrates leading global approaches and consistent standards would help Canada stay internationally competitive while keeping our digital ecosystem strong and secure.
In a nutshell, the federal government should set the national vision and provide the framework and tools while empowering local governments, organizations and innovators to adapt that framework to their realities. When everyone works from the same playbook, security can become part of how we do business—not a barrier to it.
As cyber threats evolve, is Canada keeping pace with peers like the U.S. and the E.U. in building defensive capabilities, or are governance gaps holding it back?
It’s an exciting time for cybersecurity in Canada, but the truth is we’re not yet keeping pace with our peers. The United States invests close to $800 billion or 3.5 percent of GDP annually in research and development, while Canada spends less than 2 percent of ours, and only a fraction of that goes toward cyber and defense innovation. That gap matters. The European Union, meanwhile, approaches cybersecurity not just as a security issue but as a pillar of economic resilience, seeing digital protection and competitiveness as two sides of the same coin.
Canada has world-leading talent in cybersecurity, A.I. and quantum. We are also building a strong foundation with proposed legislation like the Critical Cyber Systems Protection Act (Bill C-8) and a growing base of innovation, but we need to move faster—connecting our federal, provincial and municipal strategies, strengthening our talent pipeline and investing in homegrown technology. If we treat cybersecurity as both national defence and economic opportunity, we can close the gap and position Canada as a real leader in the digital future.
What are the most critical lessons from recent high-profile cyberattacks, and how should they guide efforts to build systemic resilience?
If there’s one thing recent cyberattacks have taught us, it’s that we need to wake up. No one is really paying attention to how serious this has become. We’re seeing massive fraud and data theft happening quietly, every day, and too often the response is weak at best. The impacts are not only felt at the victim’s level; the burden of the costs to Canadians is enormous, and we’re all paying for this.
And still, people aren’t changing their passwords, companies still skip basic protections like multi-factor authentication, and we’ve normalized the idea that our data will be stolen eventually. That has to change.
There’s a common mantra in the cyber community that when it comes to cyber threats: ‘it’s not if, but when.’ But the lesson isn’t that attacks are inevitable. It’s that we need to take preventative action and prepare for potential threats. Complacency is our biggest weakness.
We can’t treat cybersecurity as background noise while we rush to adopt new technologies like A.I. A.I. can make systems smarter, but it also makes cyber threats faster, more targeted and harder to detect. At the same time, many organizations are adopting A.I. without fully addressing the very real risks that come with it. Every organization embracing A.I. should be asking: Are we doing this in a way that keeps us secure and our clients/customers safe?
True resilience isn’t about specific actions by a cyber team; it’s about how fast and effectively we respond and how seriously we take the responsibility to protect ourselves in the first place.
What role should partnerships between universities, public institutions, government, private industry and Canadian tech companies play in building national cyber resilience?
No single group can solve Canada’s cybersecurity challenges on its own—the threats are too complex, the digital infrastructure is too vast and diverse and the stakes are too high. True resilience depends on everyone working together: universities driving research and developing talent, government providing intelligence, guidance and coordination, industry building secure systems and helping to generate specialized talent and Canadian tech companies pushing innovation forward.
But collaboration can’t just happen in boardrooms or policy papers: we also have to meet Canadians where they are. Digital resilience and cyber awareness are no longer specialized skills; they are now basic workplace essentials. Everyone, regardless of their role, needs to understand how to protect information, manage digital tools responsibly, and remain vigilant to evolving threats. If we’re going to reach everyone, it means finding more creative and practical ways to weave cyber awareness and digital resilience into everyday life, whether that’s through local community programs, small business training or more accessible education.
When universities, public institutions, government, and industry connect directly with Canadians, cybersecurity stops being an abstract concept and becomes something everyone can take part in.
That whole-of-society approach is no longer optional. It’s literally the foundation of our national resilience.
How does developing a skilled and diverse cybersecurity workforce contribute to Canada’s digital sovereignty and long-term competitiveness?
When we talk about securing Canada’s digital future, the real advantage isn’t just in technology; it’s in people. We need Canadians to protect what matters to Canada and build a robust digital infrastructure that we can rely on to keep our economy and country growing in the face of mounting threats. This requires a trustworthy and capable workforce. At the Catalyst, we have no delusions about the impacts of A.I. on cybersecurity work. The key question is: what does a skilled cybersecurity workforce look like in the age of A.I.?
We are hyper-focused on creating not only skilled cybersecurity professionals, but also helping those in other organizational roles across different sectors to better understand the cybersecurity challenges they are facing while maintaining a keen eye on emerging technologies such as A.I. and quantum computing. Through our programs, we’re building job-ready professionals who can address the human, organizational and technical issues of cybersecurity.
But in an era where A.I. can automate certain technical functions, the real challenge—and opportunity—is in ensuring that we have an agile workforce and that we educate and support individuals in exercising judgment, creativity, critical thinking, contextual understanding and ethical reasoning that machines can’t replicate.
It’s like asking how you maintain a community of great writers when A.I. can draft a paragraph for you: the value shifts to insight, empathy, strategy and human perspective.
How can Canada’s cyber strategy link security, innovation and economic growth?
For too long, we’ve talked about cybersecurity as a purely defensive measure. Many still view it as just the cost of doing business. The truth is, in the modern economy, cybersecurity is an investment, and resilience is one of our biggest competitive advantages. It’s the bedrock of national prosperity and our ticket to maintaining our position as a serious player on the global stage.
Think about it: when we create an environment built on digital trust, with infrastructure that is both robust and secure, everything else follows. It’s what gives international partners the confidence to invest here, and it’s what gives our own innovators in critical sectors like finance, healthcare and technology the secure launchpad they need to bring their best ideas to life.
So, the critical question is, how do you intentionally build that kind of environment? It doesn’t happen by accident, and it can’t rest solely on a policy or a plan. It only comes about through action.
By combining smart government policies and strong intellectual property and patent protections with real incentives for our businesses, we stop treating cybersecurity as a problem to be solved and start seeing it for what it is: a massive opportunity to build our next generation of tech leaders and secure Canada’s role as an innovator.
How will emerging technologies such as A.I. and quantum computing reshape Canada’s cybersecurity landscape, and what must be done now to ensure a secure, sovereign, and competitive digital ecosystem by 2030?
A.I. is rewriting the cybersecurity landscape, and quantum computing won’t be far behind. Each one presents both huge opportunities and serious threats. As these technologies start to converge, we will see incredible new possibilities and potential, but also significant power to cause real damage if we’re not prepared.
A.I. is now an arms race. For every advanced risk detection model we create, our adversaries are using A.I. to launch attacks. And quantum computing is the horizon. This will threaten most of the common encryption used today.
This new reality demands a strategic change, including what the industry calls the “shift-left approach.” Traditionally, security testing happened at the end of a project, just before the software was released. Shift-left flips that model by pushing security earlier in the development cycle—essentially “shifting” it to the left on the project timeline.
For example, instead of waiting until a new system is fully built to check for vulnerabilities, developers should build security into the design on day one, and then test for risks at each step. This approach comes from modern software engineering, but it’s now essential for cybersecurity: if emerging technologies like A.I. aren’t built with security-by-design, we’re already behind.
Ultimately, by investing in talent, targeting the best in R&D, and investing in an innovative ecosystem, Canada can make sure we’re not just reacting to technological change but we are leading the change.
Earlier this month, researchers claimed a major breakthrough had occurred for quantum computing in terms of proving a verifiable advantage over traditional computers. This was then followed up by Google last week, who claimed to show the first practical application of their quantum technology through the combination of its Willow chip with the Quantum Echoes algorithm.
Quantum computing is something that can be difficult to grasp, but a key area of importance in terms of this technology’s potential impact on the world is its theoretical ability to break much of the encryption that secures basically everything on the internet today. And yes, that includes Bitcoin.
In fact, Bitcoin has enabled a massive financial incentive to develop the first sufficiently-powerful quantum computer. Many of the early addresses (basically the equivalent of an account) on the Bitcoin network are secured via encryption that is vulnerable to attack from a quantum computer that is powerful enough, which is why there have already been discussions around how the Bitcoin network more generally can be upgraded to guard against this sort of threat.
Satoshi was an AI from the future that wanted to accelerate development in quantum computing
These early Bitcoin addresses, including many that have been connected to Bitcoin creator Satoshi Nakamoto, may also be associated with private keys (passwords to the Bitcoin accounts basically) that are lost or otherwise not accessible to anyone. In other words, they’re sort of like lost digital treasure chests that a quantum computer could potentially unlock at some point in the future.
Someone with a sufficiently-powerful quantum computer could be able to find the private keys for these addresses by breaking the encryption associated with them. And at current prices, we’re talking about a $460 billion treasure chest of vulnerable bitcoin, according to a previous report from Deloitte.
Bitcoin itself is not yet vulnerable to quantum computing attacks today, as those computers simply do not yet exist. Additionally, there is already at least one Bitcoin Improvement Proposal (BIP) associated with the quantum threat that would allow bitcoin wallets to preemptively upgrade their software and then quickly push for a soft fork in the case of a security crisis.
While there is no set-in-stone plan to upgrade Bitcoin to quantum-resistant or completely quantum-secure addresses quite yet, it’s also unclear if or when such an upgrade will actually be necessary. That said, plans and proposals are already being put together to deal with this threat that is still, at this point, strictly theoretical. However, this would be a rare instance where a change to the Bitcoin network’s ruleset is not optional, at least practically speaking, as users would be leaving their coins open to theft by not upgrading.
In terms of a timeline of when this could become an issue for Bitcoin, experts have generally come to consensus around a timeline of some point in the 2030s.
For now, the early Bitcoin addresses that are most vulnerable to the quantum threat are referred to as “Satoshi’s Shield” because they could operate as a canary in the coalmine of sorts in terms of the development of a sufficiently powerful quantum computer to break the encryption in Bitcoin and many other online systems.
Of course, based on bitcoin’s past performance, the current treasure of $460 billion worth of bitcoin could easily grow to more than $1 trillion by the time a sufficiently-powerful quantum computer is built. That said, the way this process would likely unfold would be a large number of smaller treasure chests being unlocked over time rather than a single attacker gaining access to one large chest holding all of that bitcoin. In other words, the cracked bitcoin wouldn’t necessarily all be found at once by the same entity.
Obviously, it should also be noted that some of this vulnerable bitcoin could be moved to less-vulnerable, already-available address types or yet-to-be-enabled, quantum-resistant addresses by the time the clock strikes midnight on the quantum threat. But again, it’s also likely that the private keys associated with a large amount of early bitcoin are simply forever lost.
Existing quantum computing startups and projects are obvious candidates for being the ones to crack Satoshi’s early Bitcoin addresses, and some Bitcoin users have even claimed that this is something the U.S. government should get involved with as a sort of new Manhattan Project for the digital age. Notably, the Trump administration is currently in talks related to U.S. government investment in a few quantum computing companies, according to The Wall Street Journal.
Cybercrime losses surged to $16 billion in 2024, a one-third jump from the previous year, according to the FBI.
AI-driven phishing, deepfakes, and voice cloning are fueling new waves of cyberattacks against businesses.
Experts warn supply-chain vulnerabilities and the rise of quantum computing pose long-term cybersecurity challenges.
Organizations are urged to adopt stronger governance, MFA, vendor oversight, and event logging for proactive defense.
October is Cybersecurity Awareness Month. Established in 2004 by the U.S. Department of Homeland Security (DHS) and the National Cyber Security Alliance (NCSA), Cybersecurity Awareness Month aims to educate the public and businesses about cyber threats and equip them with the knowledge and tools needed to stay secure.
The 21st Annual Cybersecurity Awareness Month comes at a particularly crucial time. First and foremost, cybercrime is on the rise. In fact, the Federal Bureau of Investigation (FBI) reported that cybercrime costs rose to $16 billion in 2024—a one-third increase from 2023.
Furthermore, the Cybersecurity and Infrastructure Security Agency recently furloughed the majority of its already-downsized staff at the start of the ongoing government shutdown. Many fear this will leave Americans more vulnerable to escalating cyber threats. Additionally, the 2015 Cybersecurity Information Sharing Act expired at the start of the month, raising concerns about diminished collaboration between the public and private sectors.
As a result, the need for organizations to remain vigilant and informed about cybersecurity risks is greater than ever. Among the top threats businesses should be aware of are:
AI-driven attacks
While artificial intelligence (AI) has improved efficiency and productivity for many, it has also introduced new risks related to privacy and information security. However, businesses aren’t the only ones using AI. Cybercriminals are, too.
According to a 2025 KnowBe4 report, more than 80% of phishing emails analyzed showed evidence of AI usage. AI is also behind increasingly convincing deepfakes, which led to one company losing $25 million after an employee was tricked into sending funds to fraudsters posing as the CFO. Similarly, AI-powered voice cloning is on the rise, forcing 91% of surveyed banks to reconsider their voice authentication systems.
These attacks exploit vulnerabilities in third-party vendors to gain access to sensitive customer data. Research from the Ponemon Institute and Mastercard’s RiskRecon found that more than half of breaches in the past 12 months were caused by third-party vendors.
Alarmingly, the research also stated that only 34% of organizations are confident their suppliers would notify them of a breach of their sensitive information. Yet, less than half of the organizations regularly review the security and privacy controls of their suppliers.
Quantum computing
Quantum computing leverages quantum mechanics to solve complex problems far beyond the capabilities of traditional computers. The concern is that adversaries may steal encrypted data today with the intent to decrypt it later using advanced quantum technologies.
The National Institute of Standards and Technology (NIST) has already released encryption algorithms resistant to quantum attacks, however, transitioning to post-quantum cryptography could take years and prove especially challenging for smaller institutions.
In light of these and other emerging threats, businesses should adopt the following cybersecurity best practices:
Governance and board oversight
Escalating cyber threats demand informed and active involvement at the board level. Boards and executives should take an active role in cybersecurity oversight by requiring regular updates, ensuring incident response plans exist and treating cybersecurity as a core business risk rather than just a technical issue.
Most regulations require the use of multi-factor authentication for any user accessing an information system. However, not all types of MFA are created equal. Organizations should implement strong, phishing-resistant MFA (such as FIDO/WebAuthn or Public Key Infrastructure) for all users accessing sensitive information and phase out weaker methods like SMS or voice codes.
End of operating life
Unsupported and legacy systems continue to pose significant risk, especially for smaller organizations. Companies should maintain an inventory of systems, track vendor support timelines and proactively plan upgrades or replacements before software and hardware reach EOL to avoid exploitable vulnerabilities.
Vendor management
As aforementioned, third-party vendors pose a significant threat. As a result, organizations should maintain a documented vendor risk management program and regularly conduct due diligence audits.
Event logging and threat detection
Organizations should deploy comprehensive cybersecurity event logging solutions. This can help provide visibility into system performance and security, detect incidents and support response efforts, and enable forensic investigations and threat attributions.
As cyber threats grow in scale and sophistication, Cybersecurity Awareness Month serves as a timely reminder that proactive defense is no longer optional—it’s essential. With rising risks from AI-driven attacks, supply-chain vulnerabilities and the looming impact of quantum computing, organizations must prioritize cybersecurity as a strategic imperative. By embracing strong governance, modern authentication, lifecycle management, vendor oversight, and robust event logging, businesses can better-safeguard their systems, data and stakeholders.
Charlie Wood is a partner and practice lead with the FoxPointe Solutions Information Risk Management Division of The Bonadio Group.
Fighting wildfires is a massive logistical challenge—a high-stakes puzzle where every move counts. At their core, wildfires are optimization problems: How do you allocate limited resources like water, personnel, and aircraft to have the greatest impact? Which areas must be protected first, and how do you predict and stay ahead of a fire’s unpredictable behavior? Add in dynamic factors like shifting weather patterns and road traffic, and the complexity becomes even more staggering.
Following the tragic Los Angeles fires of 2025, many of us find ourselves asking, “How can we prevent this from happening in the future?”
The answer, perhaps, lies in quantum logic: this is exactly the kind of problem that quantum logic was built to solve.
Classical computers can crunch numbers, but they’re limited—they analyze a subset of possibilities and find a “good enough” solution. Quantum computers, however, can evaluate all possibilities simultaneously, calculating optimal strategies in fractions of a second.
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What Could Quantum Do for Firefighting?
Who would you rather have allocating resources during the most critical times, an overtaxed fire chief on the ground, or one that is assisted by an all-seeing quantum computer factoring in every variable, including burning ember trajectory and water resource allocation?
Quantum computing thrives in scenarios with complex, dynamic variables. For wildfire management, its potential is game-changing:
• Fire Spread Prediction: Simulate fire behavior in real time, using live data like wind changes, humidity, and terrain.
• Resource Allocation: Optimize the placement of water, crews, and aircraft/drone for maximum impact.
• Critical Prioritization: Identify choke points or high-risk zones where intervention is most needed.
• Scenario Testing: Instantly model “what-if” scenarios to evaluate the outcomes of different strategies.
This precision could save lives, homes, and communities.
But Are Quantum Computers Ready?
There has been a lot of talk about the potential of quantum computers, and when they will actually be ready. While the computers themselves could still be a decade or more away, the good news is that solving large-scale optimization problems is possible today.
What makes this exciting is that quantum algorithms don’t require fully developed quantum computers—they can run on today’s most sophisticated classical systems, delivering quantum-inspired solutions now. Players in the space such as D-Wave, Microsoft Azure, and Entanglement (full disclosure: I’m an investor in Entanglement) have already made major headway in this field, each bringing their own approaches to tackle optimization challenges.
Their tools, like QUBOs (quadratic unconstrained binary optimization) and other combinatorial optimization solvers can analyze massive data sets and evaluate all possibilities simultaneously, finding the best answer in real time.
Fighting Fire (and insurance companies) with Quantum Logic
Insurance companies are already using math to predict the odds of losing homes, often leaving homeowners and governments scrambling to react.
What if we could flip the script? Leveraging quantum math to improve the odds for homeowners? We can make higher-risk areas safer and re-insurable, helping to rebuild communities and ensure their sustainability for their long-term.
Early progress has been made in the field of fire prevention. The U.S. Army, according to a report in May, used quantum computing to plan fuel breaks—a brush management technique that stops wildfires from spreading.
Wildfires are devastating, but with the right focus and tools, we can fight back—with precision, strategy, and quantum math on our side.
Quantum computing has emerged as a prime target for investors chasing high-growth tech sectors. Over the past year, some stocks in this space have climbed by thousands of percent, drawing billions in capital from those betting on revolutionary advancements.
Companies like Rigetti Computing (NASDAQ:RGTI), D-Wave Quantum (NYSE:QBTS), and Quantum Computing (NASDAQ:QUBT) have seen share prices skyrocket, fueled by optimism around potential applications in drug design, optimization, and cryptography. Billions have poured into funds and direct investments, pushing market caps higher despite limited revenue streams.
Yet, skeptics point to ongoing technical hurdles and question short-term commercial viability, as most systems remain experimental. Investors, however, keep bidding up valuations, viewing quantum as the next AI-like boom. With such fervor, could IonQ (NYSE:IONQ) have just delivered a breakthrough that sends its stock soaring even further?
Today, IonQ announced a major technical milestone: it achieved 99.99% fidelity in two-qubit gates, setting a new world record. In simple terms, qubits are the building blocks of quantum computers, and two-qubit gates handle interactions between them. These gates are crucial because quantum computations rely on precise entanglements and operations; even minor errors can cascade, rendering results unreliable.
Historically, error rates have been a major bottleneck, forcing engineers to dedicate vast resources to error correction — they often require thousands of physical qubits to simulate just one reliable “logical” qubit. IonQ’s “four nines” fidelity — meaning just one error per 10,000 operations — beats the prior record of 99.97% and marks the first time any company has hit this threshold on mass-producible chips.
By using electronic qubit control (EQC) technology instead of traditional lasers, IonQ integrates all controls onto standard semiconductor chips. This approach, borrowed from classical computing manufacturing, makes systems cheaper to produce, more stable in operation, and far easier to scale up.
Unlike laser-based methods, which are prone to environmental interference and require specialized setups, EQC leverages precision electronics for better reliability. For IonQ, this milestone validates its acquisition of Oxford Ionics and accelerates its roadmap. The company now projects demonstrating 256-qubit systems by 2026, with ambitions for millions of qubits by 2030.
In broader quantum computing terms, it shortens the path to commercial viability. High fidelity reduces the overhead for error correction dramatically — IonQ claims up to a 10 billion times improvement over older 99.9% benchmarks. This means quantum machines can tackle real-world problems without needing impractically large hardware. Industries such as pharmaceuticals, where IonQ has already shown 20x speed-ups in drug discovery, stand to benefit first.
Overall, it signals that quantum computing is transitioning from theoretical promise to engineered reality, potentially compressing industry timelines by years and attracting more enterprise adoption.
But will this spark a breakout for IonQ shares? The stock has risen about 350% over the past year, a strong performance but trailing its peers amid volatile market conditions.
Rigetti’s shares, despite a recent 25% drop from mid-October highs, have still delivered outsized gains of 3,800% in the same timeframe. D-Wave has surged 3,200% — even after yesterday’s 10% tumble — by capitalizing on its focus on annealing quantum systems for optimization tasks, while Quantum Computing has posted 2,170% returns.
IonQ’s announcement could shift this dynamic, showcasing tangible progress in a field often criticized for hype over substance. With partnerships like those with Amazon‘s (NASDAQ:AMZN) AWS and AstraZeneca (NYSE:AZN) already in place, this fidelity breakthrough might draw fresh investment, validating IonQ’s trapped-ion approach over competitors’ superconducting or photonic methods.
If it leads to new contracts or funding, a rally could follow, especially as quantum stocks often move on technical news rather than earnings.
As impressive as IonQ’s achievement is, it won’t land quantum computers in everyday use soon. Systems remain lab-bound, far from consumer shelves, with challenges like maintaining qubit coherence in larger arrays still unresolved. Competition is also fierce, from giants like IBM (NYSE:IBM) and Google to startups, and regulatory hurdles around quantum-safe encryption add uncertainty.
That said, investors have pumped up prices on slimmer news, so a surge isn’t out of the question — quantum enthusiasm often defies fundamentals. Valuations, though, are stretched: IonQ’s price-to-sales ratio hovers around 260, while Rigetti’s exceeds 1,770, D-Wave’s sits at 528, and Quantum Computing’s tops 14,700.
Even with triple-digit revenue growth, normalizing these could take years, as current sales are tiny — often in the low millions annually. Risks abound, including potential tech setbacks or economic downturns that dry up venture capital.
IonQ has advanced meaningfully, potentially extending its edge if you’re optimistic on quantum’s future in solving intractable problems like climate modeling or AI training. A small position makes sense for diversified portfolios, but it’s no cue to go all-in; these remain highly speculative plays with plenty of road ahead, where patience is key amid boom-and-bust cycles.
JPMorgan Chase will directly invest up to $10 billion in U.S. companies with crucial ties to national security.
The investment plan revealed Monday will focus on four areas: supply chain and advanced manufacturing in critical minerals, pharmaceutical precursors and robotics; defense and aerospace; energy independence, with investments in battery storage and grid resilience; and strategic technologies, including artificial intelligence, cybersecurity and quantum computing.
The investment is part of the bank’s Security and Resiliency Initiative, a $1.5 trillion, 10-year plan to facilitate, finance and invest in industries critical to national security.
“It has become painfully clear that the United States has allowed itself to become too reliant on unreliable sources of critical minerals, products and manufacturing – all of which are essential for our national security,” Chairman and CEO Jamie Dimon said in a statement. “Our security is predicated on the strength and resiliency of America’s economy. America needs more speed and investment.”
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This summer, JPMorgan helped put together a deal under which the Defense Department agreed to invest $400 million in U.S. rare earth company MP Materials. The bank is also providing financing for MP Materials’ second magnet producing factory in the U.S.
The nation’s largest bank plans to finance approximately $1 trillion over the next decade in support of clients in these industries. JPMorgan Chase is looking to increase this amount by up to $500 billion, or a 50 percent increase, with additional resources and capital.
“America needs more speed and investment,” Dimon said. “It also needs to remove obstacles that stand in the way: excessive regulations, bureaucratic delay, partisan gridlock and an education system not aligned to the skills we need.”
JPMorgan says that it serves 34,000 mid-sized companies and more than 90 percent of the Fortune 500.
It plans to hire more bankers, investment professionals and other experts to help address its investment plan. It will also create an external advisory council that includes leaders from the public and private sectors to help guide the long-term strategy.
STOCKHOLM (AP) — Three scientists won the Nobel Prize in physics Tuesday for research on the strange behavior of subatomic particles called quantum tunneling that enabled the ultra-sensitive measurements achieved by MRI machines and laid the groundwork for better cellphones and faster computers.
The work by John Clarke, Michel H. Devoret and John M. Martinis, who work at American universities, took the seeming contradictions of the subatomic world — where light can be both a wave and a particle and parts of atoms can tunnel through seemingly impenetrable barriers — and applied them in the more traditional physics of digital devices. The results of their findings are just starting to appear in advanced technology and could pave the way for the development of supercharged computing.
The prizewinning research in the mid-1980s took the subatomic “weirdness of quantum mechanics” and found how those tiny interactions can have real-world applications, said Jonathan Bagger, CEO of the American Physical Society. The experiments were a crucial building block in the fast-developing world of quantum mechanics.
Speaking from his cellphone, Clarke, who spearheaded the research team, said: “One of the underlying reasons that cellphones work is because of all this work.” When quantum mechanics first came to light in 1926, a prominent physicist sought to illustrate its many paradoxes with the example of a cat in a box that was both alive and dead at the same time. The three Nobel winners showed that science can put such principles to work, said Physics Today Editor-in-Chief Richard Fitzgerald, who was in a competing research group in the 1990s.
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“They didn’t take it that far, but they showed that it can be done,” Fitzgerald said. The winning physicists took “the scale of something that we can’t see, we can’t touch, we can’t feel” and brought it “up to the scale of something recognizable” and made it “something you can build upon,” Fitzgerald said.
Clarke, 83, conducted his research at the University of California, Berkeley. Martinis, 67, worked at the University of California, Santa Barbara. Devoret, 72, is at Yale and also at the University of California, Santa Barbara.
How the winners reacted
Martinis’ wife, Jean, told Associated Press reporters who called at his home hours after the announcement that he was still asleep and did not yet know. In the past, she said, they stayed up on the night of the physics award, but at some point they decided that sleep was more important.
When his wife woke him and told him about the journalists seeking an interview, the new Nobel laureate remembered that the prizes were being announced this week. He opened his computer, looked at the announcement and saw his picture along with the other winners.
“So I was kind of in shock,” he said.
Clarke said it never occurred to him that he would win a Nobel Prize. “I practically collapsed,” Clarke told AP. “I was completely stunned. I mean, it’s something that I had never, ever dreamed of in my entire life.”
Why the work matters
Martinis — who was a senior Google scientist working toward quantum computing before co-founding his own company, Qolab — said the big future goal is quantum computing, which would be a giant leap in speed and sophistication by relying on the power of the contradictory states in that subatomic world.
That is still eight to 10 years away. But he said the team’s experiments showed “a computer could be much, much more powerful.”
Devoret is now chief scientist for Google’s quantum computing efforts. Quantum computers are “one very sort of obvious use,” but the research could also help develop sensors that detect and measure faint phenomena, such as magnetic fields, and advance cryptography to encode information, said Mark Pearce, a professor of astrophysics and Nobel physics committee member. And through better understanding of precision chemistry, it could develop better materials for daily living and even give an added boost to artificial intelligence, Martinis said.
Before the work at Berkeley, scientists knew single electrons or pairs of tiny electrons could tunnel through an impenetrable barrier. What Clarke said his team learned was “if you design the circuity properly, you could actually have tunneling” of objects larger and more useful than just a couple of electrons. That discovery “can be used to make very sophisticated things that would not otherwise be able to work out,” Clarke said at a news conference, mentioning his iPhone and quantum computers.
He also criticized the Trump administration for its deep cuts to science funding, saying they would “cripple science.”
“If this continues … it may take a decade to get back to where we were half a year ago,” Clarke said.
Martinis, Bagger and Fitzgerald said it’s a bit of a stretch to say cellphones now use the breakthrough made by Clarke and colleagues. But ultra-sensitive measuring devices rely on the team’s work, including MRI machines, which would be far less useful without their advances, Bagger said.
“Quantum mechanics is everywhere in everything we do, from the cellphone to the satellite communications that are connected to the cellphones, to the screens on which we watch our videos on our cellphones,” Bagger said.
Nobel history and other 2025 prizes
Tuesday’s award was the 119th time the prize has been given. Last year, artificial intelligence pioneers John Hopfield and Geoffrey Hinton won the physics prize for helping create the building blocks of machine learning.
On Monday, Mary E. Brunkow, Fred Ramsdell and Dr. Shimon Sakaguchi won the Nobel Prize in medicine on Monday for discoveries about how the immune system knows to attack germs and not our bodies.
Nobel announcements continue with the chemistry prize on Wednesday and literature on Thursday. The Nobel Peace Prize will be announced Friday followed by the Nobel Memorial Prize in economics on Monday.
The award ceremony will be held Dec. 10, the anniversary of the 1896 death of Alfred Nobel, the wealthy Swedish industrialist and the inventor of dynamite who founded the prizes.
The prizes carry priceless prestige and a cash award of 11 million Swedish kronor (nearly $1.2 million).
Corder reported from The Hague, Netherlands, and Borenstein from Washington. Associated Press journalist Adithi Ramakrishnan in New York contributed to this report.
Copyright 2025. All rights reserved. This material may not be published, broadcast, rewritten or redistributed.
KPMG’s CEO Outlook survey offers an annual look behind the curtain at the issues keeping the top business leaders up at night. Every year, hundreds of leaders answer the call from the Big 4 accounting firm to speak frankly and anonymously about key issues that need to solved, and 400 participated in the 2025 edition. CEOs have a message for America: they just aren’t sure of, well, anything.
Business leaders told KPMG—and its recently anointed chair and CEO, Timothy Walsh—that they’re wrestling with uncertainty across several different areas of their work. This is well documented and is to be expected, Walsh told Fortune in an interview. “There’s this general, as you would expect, general conversation around business uncertainty,” Walsh said, adding that he was encouraged at least to see the “alignment” in terms of topics coming up in C-suite conversations.
Peeling back the survey data, Walsh revealed that an unsurprisingly sizable majority (89%) say tariffs will “significantly impact” their business’ performance and operations over the coming three years. And nearly as many, 86%, said their firm will increase prices as needed. They are working hard to get around this, with 85% saying their company will strive to shift its sourcing strategies to minimize the impact as much as possible. The landscape is so uncertain that nearly every CEO says they need to make some kind of change: 79% said they’ve adapted their growth plans.
Walsh talked to Fortune about uncertainty on tariffs and AI, and the importance of trust in a climate of such uncertainty. CEOs are concerned with another advancing technology with terrifying capabilities, Walsh said: cyber and quantum. “That honestly keeps me up at night.”
Cybersecurity’s quantum challenge
Cybersecurity risks remain elevated, especially as quantum computing approaches. As for advances in quantum computing, Walsh said it could one day soon be capable of breaking all encryption, and companies tell him that they’re doing full assessments. It’s a “massive effort” to ensure that they’re not exposed when that quantum computing capability arrives, Walsh warned.
Adding into the mix the capabilities of AI agents and, Walsh said, “in many cases, a nation-state-type investment,” he’s very concerned about malware and deepfake-type technologies escalating in danger. Over the next three years, 82% of CEOs polled said cybercrime and cyber insecurity was a top trend that could hurt their organization. Cyber risk was overall the second-highest cited pressure behind CEOs’ short-term decisions. CEOs are most concerned about fraud detection and prevention (65%) and identity theft (52%), but they also said they have plans in place to mitigate.
All that being said, Walsh said CEOs are “feeling optimistic because they see so many growth opportunities.” The economy has been surprisingly strong despite all the uncertainty, the tech sector is driving a very strong stock market, and he even noted some “large deals and transactions” are coming through when it comes to M&A. “Capital flows are starting to move and [be] a bit more liquid.”
Tariffs and the AI element
Walsh told Fortune that tariffs are obviously the number-one thing on every CEO’s mind. And it’s not only the fact of tariffs but potential changes to tariffs, and “the uncertainty around whether those tariffs will continue to change.” There’s an overwhelming need for businesses to not only consider what will change but to get agile enough to work on their supply chains to be prepared for future, still uncertain, changes to come. To that end, 34% of CEOs said in the survey that supply chain resilience is the top pressure driving short-term decisions, followed by cyber security risks (29%) and global economic uncertainty (25%).
Walsh emphasized that tariffs are introducing a multi-dimensional challenge for CEOs. “The CEOs I speak with are addressing tariff impacts in three areas: cost take-out, supply chain optimization including reshoring, onshoring considerations, and ultimately pricing.” He said KPMG is actively working with clients in all of those areas and yes, AI is part of this transformation, too. The prominence of AI is another layer of uncertainty being added to the picture, but Walsh said it’s helping a lot of CEOs: “AI is not just an efficiency play, CEOs are focused on innovating their business models and introducing new revenue streams and products.”
The AI hourglass to come?
Walsh said AI capabilities are changing quickly, and he acknowledged that companies are starting to restructure in response. The survey found that CEOs “mostly see an hourglass shape” to their organizations in next three years, Walsh said, noting that’s typical with every new technology deployment. He added that “no one knows exactly where [workforce shape] is headed … It’s a challenge to forecast as AI advances rapidly.” In the survey, 35% said they are planning for workforce reductions in some areas over the next two to five years due to AI, and 69% see an hourglass with higher numbers of senior leaders and early-career workers and fewer in the middle (another 16% said a vertical triangle, 13% a triangle and 2% an inverted pyramid).
Managers are facing new responsibilities, managing teams with integrated AI agents, for instance. Walsh said some CEOs describe teams with both people and AI agents on them, “and managers of those teams have to ensure [that] agents complete steps in the workflow process, that agents have good data inputs so that their outputs can be relied upon, and continuously review those outputs.” CEOs surveyed said 86% of them see AI agents becoming embedded team members next year, and half think managers will be primarily responsible for managing AI agents’ performance as opposed to, say, HR or IT.
Walsh agreed with Fortune‘s reporting that “human skills” still matter as AI implementation shows the necessity of reviewing AI outputs. “Human skills are critically important,” Walsh said. Even though KPMG invests in and spends time upskilling its workers on AI and providing them with tools and licenses, he said he continues to remind leaders that “human-to-human relationships are critical … both internally and externally. Trust is more important than ever. Building trust with our teams, clients and ensuring we can trust outputs of technology like AI.” Given the uncertain climate, he added, trust is at a premium. The top change that CEOs see coming is retaining and re-training high-potential talent (75%), followed by redesigning roles to reflect AI collaboration (65%) and hiring AI-capable talent (64%).
Fortune Global Forum returns Oct. 26–27, 2025 in Riyadh. CEOs and global leaders will gather for a dynamic, invitation-only event shaping the future of business. Apply for an invitation.
Quantum computers are already here, even though it’s not readily apparent. Now, researchers say quantum advantage—the field’s long-promised milestone of outperforming classical computers—appears to have finally arrived. But the story comes with an important caveat.
Research by scientists at the University of Texas at Austin and Colorado computing firm Quantinuum devised and carried out an experiment that demonstrates “unconditional” quantum advantage, sometimes referred to as quantum supremacy. As the researchers phrased it, their “result is provable and permanent: no future development in classical algorithms can close this gap.” The preprint, which has yet to be peer reviewed, was made available on arXiv earlier this month.
Gizmodo reached out to several experts in the field, who affirmed the new results. They added that the experiment, while commendable, isn’t the most practical use of a quantum computer—which already gets flak for its uselessness to everyday users.
Then again, “quantum advantage” is a weird, surprisingly malleable concept with many possible applications. Overall, the results are definitely worth a closer look.
Alice and Bob make a cameo
Quantum enthusiasts may be familiar with Alice and Bob, two fictional characters often summoned for quantum thought experiments. In the context of the new experiment, Alice and Bob are two researchers collaborating on a computation using a single device. They receive different inputs at different points in time, but only Alice can send Bob a message, and not the other way around. Based on Alice’s message, Bob must decide how to measure and interpret to produce a final output.
According to the paper, “the use of a quantum message can provably reduce the amount of communication required by an exponential factor compared to any protocol that uses classical communication alone.” In other words, a small quantum message can replace a much larger classical one. To prove their point, the team repeated the experiment 10,000 times on Quantinuum’s H1-1 trapped-ion quantum computers, coupled with a careful mathematical validation of their protocol.
Surprisingly, they found that a quantum computer only needed 12 qubits (qubits are the smallest unit of information for quantum computers) to solve this problem. By contrast, even the most efficient classical computers needed 330 bits.
A different way to play the game
“This is a very different type of quantum advantage than we have seen before—not better or worse, but it’s just proving something completely different from past experiments,” Bill Fefferman, a computer scientist at the University of Chicago, told Gizmodo in an email. Fefferman previously collaborated with senior author Scott Aaronson but wasn’t involved in the new study.
Fefferman explained that scientists typically equate quantum advantage to “striving to perform a computation on a quantum computer that can be solved dramatically faster than any classical computer.” By contrast, the new experiment achieves “quantum information supremacy,” in which the focus isn’t so much on speed as it is on using fewer qubits to solve a problem that classical computers need many more bits to crack.
“It is true that their result is unconditional, in the sense that it doesn’t rely on unproven assumptions,” Fefferman said. “This is, of course, a great feature of this new experiment, but it’s also inherited by this ‘moving of the goalposts.’”
Gizmodo contacted the study’s authors, who said they couldn’t comment until the paper is formally published.
Pressing the advantage
The results raise questions about the broader goals of proving quantum advantage. As IBM Quantum’s director told Gizmodo in a previous interview, a potential answer is to ask how quantum computers can enhance computing problems we’re already familiar with.
But as Fefferman noted, there isn’t necessarily a better or worse approach for arriving at quantum advantage—although this “goalpost” appears to be the holy grail for the field’s struggle to prove its worth.
That may be a product of quantum computing’s history, Giuseppe Carleo, a computational physicist at EPFL in Switzerland who wasn’t involved in the new work, explained to Gizmodo in a video call. The rapid growth of quantum computing makes it easy to forget how recently the right hardware became available to test theory.
“So the field has developed historically in the past 20, 30 years much closer to mathematics, rather than an applied field where, if you want, you can use a machine to run things,” said Carleo, who spoke with Gizmodo about the history of quantum computing. As a result, most of the analysis in the field remained at theoretical levels for a longer time than scientists would’ve hoped.
But with hardware advances and a fast-growing industry, this trend is gradually shifting—as it should, Carleo said. More projects are moving away from designing quantum advantage experiments “specifically tailored to show advantage,” he said, turning instead to places where quantum computers can help, not necessarily upend.
That’s actually closer to the field’s “origins,” he added. Richard Feynman, the physicist instrumental to quantum computing’s foundations, suggested that quantum computers should predict quantum phenomena. Sure, there might not be so much “money attached to it,” but they are “of tremendous interest for theoretical physics,” particularly with regard to fundamental questions about our universe, Carleo explained.
Quantum-anything never makes it easy
The new experiment might struggle to prove its immediate connection to practicality. But in a way, the preprint does adhere to Feynman’s advice. It’s certainly a theoretically robust demonstration of using quantum hardware to investigate quantum concepts.
At this very moment, that makes it seem detached from reality. Then again, when has anything quantum ever given easy answers? Yet, if science history is any guide, the best discoveries come from the most unexpected, seemingly impractical pursuits. We’ll just have to keep watch.
Depending on how you think about it, there’s half a dozen or more approaches to the hardware. And I became excited that within the hardware approach, the neutral atom approach was high potential. So we backed [Thompson’s] company called Logiqal.
What happens if you’re right?
I’m a venture investor, and we believe in convexity—taking risks on things that most likely won’t work, but if they do work could be 500x in value.
It’s a real earth-moving innovation if there’s a chance that quantum computers find the path toward success. You unlock these thinking engines, these computational engines that can run the future of material sciences, the future of pharmaceutical innovation, the future of logistics, the future of financial markets in ways that we’ve never seen before.
You can see a future where you could create pharmaceutical advancements that could elongate life 20 to 30 years. You could see changes in material sciences where we could invent new products. It could help us get to Mars! That is what quantum computing unlocks.
The way you talk about quantum computing sounds a lot like how many AI enthusiasts talk about artificial general intelligence.
In many ways, quantum is today where AI was back in 2015, which is a lot of really big research and science projects and starting to have practical applications rather than just pure research.
You mentioned that it’s hard to fake being a quantum expert. I would posit that it is not as hard to fake being an AI expert. How do you decide who to back?
There are so many companies that are being built and born in AI that when you extrapolate them 5, 10 years will not have a true genuine moat outside of brand or speed. Brand and speed are rarely strong enough moats to build a generational company.
I’ll give you an example. BrightAI creates stickers that are roughly this big [she makes a circle with her fist]. The company puts a sticker on every telephone pole, on every HVAC system, on every water line system, and then observes it for long periods of time, 5, 10, 15, 20 years [and flags potential issues]. That’s a pretty good moat. You’re not ripping all those stickers off.
For the most part, the value in AI accrues to the incumbents. Penny, my cofounder, is on the board of Microsoft. If you think about it, Microsoft and Google—Google has 3 billion users. Microsoft has a billion users. They can launch a product that is OK, not excellent, and they still have a pricing power, a distribution power. And so we very much think about the world where when the elephants dance. Don’t be an ant.
How do you use AI?
For everything. There’s nothing you don’t use AI for, nothing. From every question, I mean, today I probably used it 25 times.
It’s replaced Google for you?
Everything. Everything. Deep research, sourcing. Today I was looking up what jobs are declining fastest in the world. Truly, I would say it’s not a dozen times a day. It’s dozens of times a day.
For billions of years, solar winds have bombarded the Moon. Over time, this constant onslaught of charged particles has caused helium-3 to accumulate in the lunar surface. This isotope is rare on Earth, and rising demand from several industries—including quantum computing—has incentivized some companies to explore the possibility of lunar mining.
One such company is Interlune, a Seattle-based startup that aims to extract natural resources—primarily helium-3—from the lunar surface. Interlune eventually hopes to sell its harvested helium-3 to government and commercial customers in the national security, medical imaging, fusion energy, and quantum computing industries—and it just struck a major commercial deal.
The largest purchase of lunar resources yet
On Tuesday, Interlune announced a partnership with Bluefors, a leading manufacturer of dilution refrigerators and one of the world’s largest consumers of helium-3. Its continuous cooling systems use helium-3 to keep quantum computers running at the ultra-low temperatures required for maintaining qubit stability and reliable operation.
As the quantum computing industry moves toward commercialization—with tech giants such as Google, IBM, and Microsoft reporting progress in scaling—the demand for helium-3 is set to rise. Bluefors agreed to purchase up to 10,000 liters of helium-3 annually from Interlune between 2028 and 2037. This substance trades at around $2,500 per liter, according to a 2024 estimate from The Edelgas Group. The deal is the largest purchase of lunar resources to date.
“A majority of the quantum technology industry relies on Bluefors systems to operate and accelerate development,” Rob Meyerson, Interlune co-founder and CEO, said in a company release. “We are excited to help Bluefors continue advancing companies toward unlocking scientific and medical discoveries made possible only by near-absolute-zero temperatures.”
How Interlune plans to mine the Moon by 2028
Meyerson, former president of Blue Origin, founded Interlune in 2020 alongside former chief architect Gary Lai and Harrison Schmitt, the only living member of Apollo 17. Ever since that mission, Schmitt—a geologist—has advocated for humanity to harness the Moon’s helium-3 reserves.
Interlune has spent the past five years working toward that goal. The company has raised over $18 million in venture funding to develop robotic harvesters and launch a demonstration mission in 2027 as well as a pilot plant by 2029, according to SpaceNews.
This funding and the clearly laid-out roadmap are promising, but it remains to be seen whether Interlune will overcome the steep technological, logistical, and financial challenges of lunar mining by 2028. Though the prospect has garnered plenty of buzz in recent years, very few companies have made real progress toward achieving it.
What’s more, some experts argue that the value of mining the Moon’s helium-3 is overblown. The fact is, we don’t know for sure how much is up there. And although the highest concentrations measured in the Apollo and Luna samples are greater than Earth’s, they’re still very low.
For now, the Moon’s helium-3 is more promise than product, but Interlune’s deal with Bluefors signals rising demand from the quantum computing industry—and could mark a major step toward a new era of space resource extraction.
Hub will feature the state’s first hybrid quantum data center
Facility expected to open in 2029 after three years of development
Project aims to enhance secure internet and tech-driven economic growth
New York State is investing $300 million to launch the Quantum Research and Innovation Hub at Stony Brook University. The initiative aims to integrate research, computing and workforce training to address complex societal challenges and build a “faster, smarter and more secure internet,” according to the university.
The 150,000-square-foot facility will be home to the SUNY Stony Brook Quantum Institute, the state’s first university-based hybrid quantum data center, and the SUNY Stony Brook Quantum Education Consortium. Planning and construction are expected to take about three years, with an anticipated opening in 2029.
Calling Stony Brook University a “research powerhouse,” Gov. Kathy Hochul said in a news release that the university “will now be able to reach new heights in quantum.”
Hochul made the announcement on Wednesday at Stony Brook’s New York State Center of Excellence in Wireless and Information Technology.
“We know that to provide our state and nation with a brighter future, we need to invest today, and that is what New York is committed to do,” she said.
The funding comes at a time when organizations are navigating pauses and cuts in federal funding.
Hochul said that “when national investment in research and innovation is at risk, New York State is doubling down, and SUNY is on the move.”
Speaking about Stony Brook University’s quantum network, which she described as the largest in the nation, President Andrea Goldsmith said in the news release that through “such transformative research, in partnership with New York State and SUNY, we are accelerating technological advancement and its positive impact across our state and beyond.”
The hub, she said “will spearhead the future of quantum computing and networking. Today’s historic investment further advances Stony Brook’s leadership in quantum science and technology, and showcases the bold ground-breaking research across our campus that delivers solutions to society’s most pressing challenges.”
Empire State Development President, CEO and Commissioner Hope Knight said the investment would drive economic growth.
“The creation of the Quantum Research and Innovation Hub marks the next step in expanding research capacity, cultivating top talent, and advancing breakthroughs that will drive economic growth and cement New York’s position as a global leader in quantum technology,” Knight said.
“This investment will give Long Island the bandwidth to be at the forefront of the next era of science and innovation,” Stony Brook alumna and State Senator Monica Martinez said in the news release. “The future Quantum Research and Innovation Hub at Stony Brook will build the infrastructure necessary to expand human understanding and drive the discoveries of tomorrow, creating new economic opportunities that strengthen our region and position New York to lead.”
Say you want to send a private message, cast a secret vote, or sign a document securely. If you do any of these tasks on a computer, you’re relying on encryption to keep your data safe. That encryption needs to withstand attacks from code breakers with their own computers, so modern encryption methods rely on assumptions about what mathematical problems are hard for computers to solve.
But as cryptographers laid the mathematical foundations for this approach to information security in the 1980s, a few researchers discovered that computational hardness wasn’t the only way to safeguard secrets. Quantum theory, originally developed to understand the physics of atoms, turned out to have deep connections to information and cryptography. Researchers found ways to base the security of a few specific cryptographic tasks directly on the laws of physics. But these tasks were strange outliers—for all others, there seemed to be no alternative to the classical computational approach.
By the end of the millennium, quantum cryptography researchers thought that was the end of the story. But in just the past few years, the field has undergone another seismic shift.
“There’s been this rearrangement of what we believe is possible with quantum cryptography,” said Henry Yuen, a quantum information theorist at Columbia University.
In a string of recent papers, researchers have shown that most cryptographic tasks could still be accomplished securely even in hypothetical worlds where practically all computation is easy. All that matters is the difficulty of a special computational problem about quantum theory itself.
“The assumptions you need can be way, way, way weaker,” said Fermi Ma, a quantum cryptographer at the Simons Institute for the Theory of Computing in Berkeley, California. “This is giving us new insights into computational hardness itself.”
This Message Will Self-Destruct
The story begins in the late 1960s, when a physics graduate student named Stephen Wiesner started thinking about the destructive nature of measurement in quantum theory. Measure any system governed by the rules of quantum physics, and you’ll alter the quantum state that mathematically describes its configuration. This quantum measurement disturbance was a hindrance for most physicists. Wiesner, who took an unorthodox information-centric view of quantum theory, wondered whether it could be made useful. Perhaps it could serve as a form of built-in tamper protection for sensitive data.
But Wiesner’s ideas were too far ahead of their time, and he left academia after graduate school. Fortunately, he’d discussed his ideas with his friend and fellow physicist Charles Bennett, who unsuccessfully tried to interest others in the subject for a decade. Finally, in 1979, Bennett met the computer scientist Gilles Brassard while swimming off the coast of Puerto Rico during a conference. Together, they wrote a groundbreaking paper describing a new approach to an important cryptographic task. Their protocol was based on quantum measurement disturbance, and needed no assumptions about the difficulty of any computational problems.
Financial institutions are exploring the use of quantum tech to optimize operations within payments and security. Quantum technology can make payments safer through cryptography and by providing secure communications, Lily Varon, principal analyst at think tank Forrester, told Bank Automation News. “When we think about quantum computing, we think about payments and quantum security in […]
HSBC is restructuring the organization by leaving some geographic territories, investing in tech and — most recently — undergoing a leadership change. The bank is looking for a replacement for Chief Executive Noel Quinn, HSBC Chairman Mark Tucker announced during today’s first-quarter earnings call. Tucker said he hoped to have a replacement for Quinn by […]
This extreme fragility might make quantum computing sound hopeless. But in 1995, the applied mathematician Peter Shor discovered a clever way to store quantum information. His encoding had two key properties. First, it could tolerate errors that only affected individual qubits. Second, it came with a procedure for correcting errors as they occurred, preventing them from piling up and derailing a computation. Shor’s discovery was the first example of a quantum error-correcting code, and its two key properties are the defining features of all such codes.
The first property stems from a simple principle: Secret information is less vulnerable when it’s divided up. Spy networks employ a similar strategy. Each spy knows very little about the network as a whole, so the organization remains safe even if any individual is captured. But quantum error-correcting codes take this logic to the extreme. In a quantum spy network, no single spy would know anything at all, yet together they’d know a lot.
Each quantum error-correcting code is a specific recipe for distributing quantum information across many qubits in a collective superposition state. This procedure effectively transforms a cluster of physical qubits into a single virtual qubit. Repeat the process many times with a large array of qubits, and you’ll get many virtual qubits that you can use to perform computations.
The physical qubits that make up each virtual qubit are like those oblivious quantum spies. Measure any one of them and you’ll learn nothing about the state of the virtual qubit it’s a part of—a property called local indistinguishability. Since each physical qubit encodes no information, errors in single qubits won’t ruin a computation. The information that matters is somehow everywhere, yet nowhere in particular.
“You can’t pin it down to any individual qubit,” Cubitt said.
All quantum error-correcting codes can absorb at least one error without any effect on the encoded information, but they will all eventually succumb as errors accumulate. That’s where the second property of quantum error-correcting codes kicks in—the actual error correction. This is closely related to local indistinguishability: Because errors in individual qubits don’t destroy any information, it’s always possible to reverse any error using established procedures specific to each code.
Taken for a Ride
Zhi Li, a postdoc at the Perimeter Institute for Theoretical Physics in Waterloo, Canada, was well versed in the theory of quantum error correction. But the subject was far from his mind when he struck up a conversation with his colleague Latham Boyle. It was the fall of 2022, and the two physicists were on an evening shuttle from Waterloo to Toronto. Boyle, an expert in aperiodic tilings who lived in Toronto at the time and is now at the University of Edinburgh, was a familiar face on those shuttle rides, which often got stuck in heavy traffic.
“Normally they could be very miserable,” Boyle said. “This was like the greatest one of all time.”
Before that fateful evening, Li and Boyle knew of each other’s work, but their research areas didn’t directly overlap, and they’d never had a one-on-one conversation. But like countless researchers in unrelated fields, Li was curious about aperiodic tilings. “It’s very hard to be not interested,” he said.
Quantum tech provider Quantum Dice has developed hardware to make financial services operations faster and more efficient. The Oxford, U.K.-based company’s hardware can increase the accuracy in statistical modeling, speeding processes like trading activities and risk assessment by 15% to 20%, Annika Moslein, technical project manager at Quantum Dice, told Bank Automation News Feb. […]
