Insights

At its core, Random Circuit Sampling (RCS) is a way to test how well a quantum computer can generate the output of a complex quantum circuit. Compare the results to what an ideal quantum computer should produce. If the quantum computer’s output closely matches the theoretical expectations, it demonstrates that the system is performing quantum operations correctly ...

Model stealing, also known as model extraction, is the practice of reverse engineering a machine learning model owned by a third party without explicit authorization. Attackers don't need direct access to the model's parameters or training data to accomplish this. Instead, they often interact with the model via its API or any public interface, making queries (i.e., sending input data) and receiving predictions (i.e., output data). By systematically making numerous queries and meticulously studying the outputs, attackers can build a new model that closely approximates the target model's behavior ...

The secret sauce of quantum computing, which even Einstein called "spooky," is the ability to generate and manipulate quantum bits of data or qubits. Certain computational tasks can be executed exponentially faster on a quantum processor using qubits, than on a classical computer with 1s and 0s. A qubit can attain a third state of superimposition of 1s and 0s simultaneously, encode data into quantum mechanical properties by "entangling" pairs of qubits, manipulate that data and perform huge complex calculations very quickly ...

The shift to post-quantum cryptography is not a distant problem but an imminent challenge that requires immediate attention. The quantum threat affects all forms of computing - whether it’s enterprise IT, IoT devices, or personal electronics. Transitioning to quantum-resistant algorithms is a complex, resource-intensive task that demands coordination across the supply chain, extensive security audits, and careful management of performance and cost issues ...

Schrödinger’s equation is essentially the master instruction set for quantum systems – the quantum-world analogue of Newton’s famous F=ma in classical physics. In short, Schrödinger’s equation is to quantum mechanics what Newton’s second law is to classical mechanics: a fundamental law of motion describing how a physical system will change over time. It was formulated in 1925–26 by Erwin Schrödinger, who built on the idea that particles like electrons could behave as waves. By solving this equation, Schrödinger successfully predicted the allowed energy levels (the “bound states”) of the hydrogen atom, matching experimental observations of atomic spectra. This was a stunning validation – much like how Newton’s laws predict planetary orbits, Schrödinger’s equation accurately predicted the quantized orbits of electrons ...

Mosca’s Theorem is a risk framework formulated to help organizations gauge how urgent their post-quantum preparations should be. It is often summarized by the inequality X + Y > Q, where: X = the length of time your data must remain secure (the required confidentiality lifespan of the information). Y = the time required to migrate or upgrade your cryptographic systems to be quantum-safe (your migration timeline). Q = the expected time until quantum attackers can break today’s encryption (the “Z”ero-hour for current cryptography) ...

Because it demands so much manpower, cybersecurity has already benefited from AI and automation to improve threat prevention, detection and response. Preventing spam and identifying malware are already common examples. However, AI is also being used – and will be used more and more – by cybercriminals to circumvent cyberdefenses and bypass security algorithms. AI-driven cyberattacks have the potential to be faster, wider spread and less costly to implement. They can be scaled up in ways that have not been possible in even the most well-coordinated hacking campaigns. These attacks evolve in real time, achieving high impact rates ...

In the late 1990s, organizations worldwide poured time and money into exorcising the “millennium bug.” Y2K remediation was a global scramble. That massive effort succeeded: when January 1, 2000 hit, planes didn’t fall from the sky and power grids stayed lit. Ever since, Y2K has been held up as both a model of proactive risk management and, paradoxically, a punchline about overhyped tech doomsaying. Today, as boards hear warnings about cryptography-shattering quantum computers, the comparison to Y2K is increasingly cropping up. It’s easy to see why: preparing for “Q-Day”, the moment a quantum computer can crack RSA/ECC encryption, also involves updating or replacing countless systems in time to avoid a digital disaster. However, analogies can be double-edged. While the Y2K ...

Quantum computing holds the potential to revolutionize fields where classical computers struggle, particularly in areas involving complex quantum systems, large-scale optimization, and cryptography. The power of quantum computing lies in its ability to leverage the principles of quantum mechanics - superposition and entanglement - to perform certain types of calculations much more efficiently than classical computers ...

Quantum parallelism is often described in almost mystical terms – exponential computations happening in parallel in the multiverse! – but as we’ve explored, it boils down to the concrete physics of superposition and interference. A quantum computer superposes many states and processes them together, leveraging the wave-like nature of quantum amplitudes to sift out the answer we want. It’s like having an insanely massive parallel computer, but one that only yields useful output if programmed in just the right way. This duality is what makes quantum computing both exciting and challenging ...

Cryptographic systems rely on the unpredictability and randomness of numbers to secure data. In cryptography, the strength of encryption keys depends on their unpredictability. Unpredictable and truly random numbers - those that remain secure even against extensive computational resources and are completely unknown to adversaries - are among the most essential elements in cryptography and cybersecurity ...

Quantum Artificial Intelligence (QAI) represents an emerging frontier where quantum computing meets artificial intelligence. This interdisciplinary field explores how quantum algorithms can enhance, accelerate, and expand the capabilities of conventional AI systems. Quantum computing's potential to process complex datasets exponentially faster than classical computers could revolutionize areas like machine learning, optimization, and pattern recognition ...