Science and Technology

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 occurs when attackers infiltrate the development or distribution process rather than directly attacking the end application. Instead of breaking into a single system, they compromise shared components such as…

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.Foundations of Reinforcement Learning for Dexterous ControlReinforcement learning describes a paradigm where an agent refines its behavior through interactions with an environment, guided by rewards or penalties. In the context of…

Quantum computers hold the potential to deliver exponential acceleration on specific tasks, yet their components remain extraordinarily delicate, with qubits—quantum bits—reacting intensely to environmental noise such as thermal shifts, electromagnetic disruptions, and flaws within control mechanisms; even minimal interference can trigger errors that rapidly undermine an entire computation.Quantum error correction (QEC) tackles this issue by embedding logical qubits within entangled configurations of numerous physical qubits, enabling the identification and correction of faults without directly observing and collapsing the underlying quantum data. During the last decade, various QEC methods have progressed from theoretical constructs to practical demonstrations, yielding notable gains in…

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 describes a paradigm where an agent refines its behavior through interactions with an environment, guided by rewards or penalties. In the…

A recently detected asteroid will pass relatively close to Earth this Monday, attracting the interest of astronomers and space agencies worldwide. Even with the narrow cosmic distance, experts stress that the object poses no risk to the planet and will proceed safely along its trajectory through space.Astronomers are closely monitoring an asteroid known as 2026JH2, a rocky object expected to glide past Earth at an estimated distance of about 91,593 kilometers, roughly 56,900 miles. According to calculations from the European Space Agency, its trajectory will bring it to nearly one quarter of the usual gap between Earth and the moon,…

AI code generation has evolved from a cutting‑edge experiment into a core pillar of contemporary software creation, shifting from simple snippet autocompletion to influencing architectural planning, testing approaches, security evaluations, and team operations, ultimately marking a major shift not only in development speed but in how humans and machines now collaborate throughout the entire software lifecycle.Copilots Pervading Everything: Spanning IDEs and the Broader ToolchainEarly AI coding assistants were initially built to offer suggestions within the editor, but now copilots are woven throughout the entire development lifecycle, spanning requirements collection, code evaluation, testing, deployment, and system observability.IDE copilots generate functions, refactor…

Obesity is increasingly understood not as a matter of willpower or aesthetics, but as a multifaceted, long‑term medical condition shaped by biological, behavioral, social, and environmental influences. This broader understanding has prompted major shifts in prevention strategies, clinical practice, public policy, and scientific research. This article outlines the factors behind this change, reviews supporting evidence and examples, presents emerging tools and care models, and examines the challenges and consequences for patients, healthcare professionals, and communities.What obesity is and why it mattersObesity is commonly identified using body mass index thresholds (BMI ≥30 kg/m² for adults), though this metric offers only a…

Expectations shape physiology. The terms placebo and nocebo capture the positive and negative consequences of those expectations. A placebo effect occurs when a beneficial health change follows an inert treatment or contextual therapeutic act; a nocebo effect is when negative outcomes or side effects follow due to negative expectations. Both are not “just in the head”: they produce measurable changes in symptoms, biological markers, brain activity, and behavior. Understanding these phenomena matters for clinical care, trial design, public health policies, and ethical communication.Essential Terms and Clear DistinctionsPlacebo: an improvement that stems from psychological influences and situational elements rather than the…

Artificial intelligence workloads have transformed the way cloud infrastructure is conceived, implemented, and fine-tuned. Serverless and container-based platforms, which previously centered on web services and microservices, are quickly adapting to support the distinctive needs of machine learning training, inference, and data-heavy pipelines. These requirements span high levels of parallelism, fluctuating resource consumption, low-latency inference, and seamless integration with data platforms. Consequently, cloud providers and platform engineers are revisiting abstractions, scheduling strategies, and pricing approaches to more effectively accommodate AI at scale.Why AI Workloads Stress Traditional PlatformsAI workloads differ from traditional applications in several important ways:Elastic but bursty compute needs: Model…

Artificial intelligence workloads have transformed the way cloud infrastructure is conceived, implemented, and fine-tuned. Serverless and container-based platforms, which previously centered on web services and microservices, are quickly adapting to support the distinctive needs of machine learning training, inference, and data-heavy pipelines. These requirements span high levels of parallelism, fluctuating resource consumption, low-latency inference, and seamless integration with data platforms. Consequently, cloud providers and platform engineers are revisiting abstractions, scheduling strategies, and pricing approaches to more effectively accommodate AI at scale.Why AI Workloads Stress Traditional PlatformsAI workloads differ from traditional applications in several important ways:Elastic but bursty compute needs: Model…