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Vysloužilý smartphone může fungovat jako domácí server bez dodatečných nákladů • Velkou výhodou je integrovaná baterie sloužící jako záložní zdroj • Pro bezpečný trvalý provoz je vhodné omezit nabíjení baterie chytrou zásuvkou

Algorithmic advances are steadily lowering the bar for quantum attacks—even before large-scale hardware exists.

Online data is generally pretty secure. Assuming everyone is careful with passwords and other protections, you can think of it as being locked in a vault so strong that even all the world’s supercomputers, working together for 10,000 years, could not crack it.

But last month, Google and others released results suggesting a new kind of computer—a quantum computer—might be able to open the vault with significantly fewer resources than previously thought.

The changes are coming on two fronts. On one, tech giants such as IBM and Google are racing to build ever-larger quantum computers: IBM hopes to achieve a genuine advantage over classical computers in some special cases this year, and an even more powerful “fault-tolerant” system by 2029.

On the other front, theorists are refining quantum algorithms: Recent work shows the resources needed to break today’s cryptography may be far fewer than earlier estimates.

The net result? The day quantum computers can break widely used cryptography—portentously dubbed “Q-Day”—may be approaching faster than expected.

The Quantum Hardware Race

Quantum computers are built from quantum bits, or qubits, which use the counterintuitive properties of very tiny objects to carry out computations in a different and sometimes far more efficient way from traditional computers.

So far the technology is in its infancy, with the major goal to increase the number of qubits that can be connected to work as a single computer. Bigger quantum computers should be much better at some things than their traditional counterparts—they will have a “quantum advantage.”

Late last year, IBM unveiled a 120-qubit chip which it hopes will demonstrate a quantum advantage for some tasks.

Google also recently announced it planned to speed up its move to adopt encryption techniques that should be safe against quantum computers, known as post-quantum cryptography.

Alongside these tech giants, newer approaches are also flourishing. PsiQuantum is using light-based qubits and traditional chip-manufacturing technology. Experimental platforms such as neutral-atom systems have demonstrated control over thousands of qubits in laboratory settings.

In response, standards bodies and national agencies are setting increasingly concrete timelines for moving away from common encryption systems that are vulnerable to quantum attack.

In the United States, the National Institute of Standards and Technology (NIST) has proposed a transition away from quantum-vulnerable cryptography, with migration largely completed by 2035. In Australia, the Australian Signals Directorate has issued similar guidance, urging organizations to begin planning immediately and transition to post-quantum cryptography by 2030.

Algorithms Make the Lock-Picking Faster

Hardware is only half the story. Equally important are advances in quantum algorithms—ways to use quantum computers to attack encryption.

Much interest in quantum computer development was spurred by Peter Shor’s 1994 discovery of an algorithm that showed how quantum computers could efficiently find the prime factors of very large numbers. This mathematical trick is precisely what you need to break the common RSA encryption method.

For decades, it was believed a quantum computer would need millions of physical qubits to pose a threat to real-world encryption. This is far bigger than current systems, so the threat felt comfortably distant.

That picture is now changing.

In March 2026, Google’s Quantum AI team released a detailed study showing that far fewer resources may be needed to attack a different kind of encryption which uses mathematical objects called elliptic curves. This is what systems including Bitcoin and Ethereum use—and the study shows how a quantum computer with fewer than half a million physical qubits may be able to crack it in minutes.

That’s still a long way beyond current quantum computers, but around ten times less than earlier estimates.

At the same time, a March 2026 preprint from a Caltech—Berkeley—Oratomic collaboration explores what might be possible using neutral-atom quantum computers. The researchers estimate that Shor’s algorithm could be implemented with as few as 10,000–20,000 atomic qubits. In one design they propose, a system with around 26,000 qubits could crack Bitcoin’s encryption in a few days, while tougher problems like the RSA method with a 2048-bit key would need more time and resources.

In plain terms: The codebreakers are becoming more efficient. Advances in algorithms and design are steadily lowering the bar for quantum attacks, even before large-scale hardware exists.

What Now?

So what does this mean in practice?

First, there is no immediate catastrophe—today’s cryptography won’t be broken overnight. But the direction of travel is clear. Each improvement in hardware or algorithms reduces the gap between current capabilities and useful quantum cracking machines.

Second, viable defenses already exist. NIST has standardized several post-quantum cryptographic algorithms which are believed to be resistant to quantum attacks.

Technology companies have begun deploying these in hybrid modes: Google Chrome and Cloudflare, for example, already support post-quantum protections in some protocols and services.

Systems that rely heavily on elliptic-curve cryptography—including cryptocurrencies and many secure communication protocols—will need particular attention. Google’s recent work explicitly highlights the need to migrate blockchain systems to post-quantum schemes.

Finally, this is a two-front race. It is not enough to track progress in quantum hardware alone. Advances in algorithms and error correction can be just as important, and recent results show these improvements can significantly reduce the estimated cost of attacks.

Every new headline about reduced qubit counts or faster quantum algorithms should be understood for what it is: another step toward a future where today’s cryptographic assumptions no longer hold.

The only reliable defense is to move—deliberately but decisively—toward quantum-safe cryptography.

This article is republished from The Conversation under a Creative Commons license. Read the original article.

The post Quantum Computers Are Coming to Break Cryptography Faster Than Anyone Expected appeared first on SingularityHub.

Natočit dobrou komedii je dost těžké. Natočit dobrou komedii, která umí být zároveň znepokojivá, není o nic lehčí. Snímek Ovce žerou první režiséra Jana Musila Přejmenovaného míchá komickou absurditu, komediální vzorce o loserech a prvky zneklidňujícího psychothrilleru. Což je prakticky vše, co si ...

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Po 17 letech od spuštění vznikla datovka s číslem 5 000 000. • Celkem už lidé a organizace poslali 1,6 miliardy datových zpráv. • Stávající adresa mojedatovaschranka.cz letos skončí.

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It looks very much as if Apple’s former designer Jony Ive will compete against the company his friend Steve Jobs created as he works with OpenAI on a device that seems to be some form of competitor for the iPhone.

In a post on X, TF International Securities analyst Ming-Chi Kuo claims OpenAI is working with Qualcomm and MediaTek to build SoCs for smartphones. These chips will be built to deliver faster AI performance. Kuo claims the plan is to achieve mass production by 2028 with the hardware specifications for these devices set to be finalized by early 2027. 

You could argue that as well as working with Apple’s former design lead, OpenAI is also taking a leaf out of the company’s processor playbook with this strategy. That’s because just as Apple works with TSMC on chip design, OpenAI intends to work with Qualcomm and MediaTek, which may help it achieve competitive processors far more quickly than it would take if building these things from scratch.

Apple faces a new competitor

What’s interesting about this is the release schedule as it suggests mass production of the new device may commence as soon as 2028, one year after the iPhone’s twentieth anniversary. We know that Apple will not sit on its iPhone laurels in the coming years and already expect the company to introduce a new folding device as well as a potential new high-end device.

We also think that Apple will be shipping devices with very fast, very power-efficient 1.4nm processors by the time the purported OpenAI product appears. It’s open to question if OpenAI’s new partnership will be able to develop AI processors for smartphones that compare to those Apple will have available by then, given its advantages in the space today, but neither company can afford to be complacent in this arena.

Why is it so important? 

Because of the nature of AI. 

It’s all about AI agents

While today’s leading AI services tend to rely on cloud-based models, tomorrow’s services will be far more independent and far more likely to run securely on edge devices.

AI agents, for example, may call on server-based intelligence to accomplish some tasks, but there will be an increasing tendency to maintain data privacy within the transaction. Agents will call on servers to provide only the computational assistance they require, handling other tasks natively on device. This will be agentic edge intelligence, which is what I anticipate Apple will discuss at WWDC 2026 in a couple of months.

Kuo says AI agents will replace apps on devices, and that’s going to require both on-device edge intelligence and cloud AI integration. To deliver that, OpenAI will need to emulate Apple’s famed ‘whole widget’ approach by controlling both hardware and software.

The analyst predicts that part of the go-to-market plan for the new Apple competitor involves subscriptions and development of a third-party AI agent ecosystem. It’s a model in which you don’t purchase apps but do invest in utility. This will also likely be part of Apple’s message to developers in the coming years — though rather than leaning into OpenAI, it will draw on some of the on-device AI models it is building with help from Google Gemini.

What comes next?

Apple is no stranger to existential struggle. The story of its resurrection after the return of Steve Jobs is legendary, but the company has faced its share of other threats since then. Who else recalls the great smartphone design wars, the entire netbook category, or Windows Mobile, for example?

Apple’s new challenge is just the latest chapter in its book, and the most likely outcome I can imagine sees OpenAI grabbing most of its market share from Android, rather than iOS — particularly as Android device manufacturers search for excuses to offer devices at higher price points in the face of stiff component costs and Apple’s aggressive move into the mid-range market. It is also fair to think that component costs may yet delay elements of OpenAI’s plan, particularly as Apple seems to be paying top dollar to secure supply.

All in all, we are entering interesting times as Apple’s newly promoted CEO, John Ternus, takes command — and his insight and experience in hardware development and design seems even more well-timed in the face of the news from OpenAI.

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On Thursday, April 30 at 2:00 PM ET, BleepingComputer will host a live webinar with threat intelligence company Flare and threat intelligence researcher Tammy Harper, exploring how security teams can identify early warning signs of attacks before they escalate into incidents. [...]

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V Paříži a na Polymarketu bylo horko. Za poslední měsíc dvakrát. Znáte Polymarket? Je to na blockchainu založená platforma, která umožňuje uživatelům sázet na výsledek reálných událostí z oblasti politiky, sportu, vědy nebo popkultury. Nebo také na počasí. A přesně to udělal zatím neznámý sázkař ...