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Software supply-chain attacks have evolved from a niche worry into a major force reshaping contemporary software engineering, as adversaries exploit the trusted tools, libraries, and services developers rely on, enabling a single vulnerability to expose countless organizations, while high-profile breaches in recent years have transformed how teams architect, create, and sustain software, driving security considerations much earlier and more deeply into the entire development process.Understanding Software Supply-Chain AttacksA software supply-chain attack takes place when adversaries penetrate the development or delivery workflow rather than targeting the final application itself, compromising shared elements like open-source libraries, build systems, package registries, or update…

Quantum computers promise exponential speedups for certain problems, but they are exceptionally fragile. Quantum bits, or qubits, are highly sensitive to noise from their environment, including thermal fluctuations, electromagnetic interference, and imperfections in control systems. Even small disturbances can introduce errors that quickly overwhelm a computation.Quantum error correction (QEC) addresses this challenge by encoding logical qubits into entangled states of multiple physical qubits, allowing errors to be detected and corrected without directly measuring and collapsing the quantum information. Over the past decade, several QEC approaches have moved from theory to experimental demonstrations, with measurable improvements in error rates, scalability, and…

Robotic dexterity describes a machine’s capacity to handle objects with precise, adaptable, and dependable control even in dynamic, unpredictable settings. Activities like grasping uneven items, assembling parts, or managing delicate materials call for nuanced manipulation that has long been challenging to encode directly. By combining reinforcement learning with large-scale simulation, researchers are transforming how robots develop these abilities, shifting dexterity away from rigid automation and toward more flexible, human-like interaction.Core Principles of Reinforcement Learning for Skilled Dexterous ControlReinforcement learning is a learning paradigm in which an agent improves its behavior by interacting with an environment and receiving feedback in the…