Science and Technology

Zero-trust security is an architectural approach that assumes no user, device, or application should be trusted by default, even when operating inside a corporate network. Access decisions are continuously evaluated using identity, device posture, context, and behavior. This model contrasts with perimeter-based security, which implicitly trusts users once they are inside the network.Cloud Adoption and the Fading Boundaries of the Network PerimeterAs organizations accelerate their shift toward cloud and hybrid ecosystems, one of the most powerful forces propelling zero-trust adoption is this swift transition, with businesses depending more heavily on multiple public clouds, diverse software-as-a-service solutions, and APIs that operate…

Satellite internet has evolved from a service mainly used in remote areas into a central element of emerging global connectivity, driven by lower launch expenses, improved satellite engineering, and closer coordination with ground-based networks, ultimately delivering a quicker, sturdier, and more accessible communication landscape that enhances fiber, 5G, and forthcoming 6G systems.Low Earth Orbit Constellations Transform Performance StandardsThe most transformative trend is the rise of Low Earth Orbit (LEO) satellite constellations. Orbiting at altitudes of roughly 300 to 1,200 kilometers, LEO satellites dramatically reduce latency compared to traditional geostationary satellites positioned 35,786 kilometers above Earth.Key impacts include:Lower latency: Round-trip delays…

Phishing has shifted from simple mass emails to precise, data‑fueled assaults, and deepfakes have progressed from mere curiosities to active operational threats; together, they introduce a rapidly scalable danger capable of eroding trust, draining resources, and steering critical decisions off course, prompting companies to prepare by acknowledging a key fact: adversaries now merge social engineering with artificial intelligence and automation to strike with unmatched speed and scale.Recent industry reports indicate that phishing continues to serve as the leading entry point for major breaches, while the emergence of audio and video deepfakes has introduced a more convincing dimension to impersonation schemes.…

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.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…

Obesity is increasingly recognized not as a simple result of willpower or a cosmetic issue, but as a complex, chronic health condition with biological, behavioral, social, and environmental drivers. That recognition has driven a substantive shift in prevention, clinical care, public policy, and research. This article explains the reasons for the change, summarizes evidence and examples, describes new tools and models of care, and considers challenges and implications for patients, clinicians, and societies.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 limited view…

AI code generation has shifted from experimental tooling to a foundational layer of modern software development. What began as autocomplete for snippets now influences architecture decisions, testing strategies, security reviews, and team workflows. The most significant change is not just speed, but a redefinition of how humans and machines collaborate across the software lifecycle.Copilots Pervading Everything: Spanning IDEs and the Broader ToolchainEarly AI coding assistants focused on in-editor suggestions. Today, copilots are embedded across the stack, including requirements gathering, code review, testing, deployment, and observability.IDE copilots generate functions, refactor legacy code, and explain unfamiliar codebases in real time.Pull request copilots…

Humanity’s most distant spacecraft continues its solitary voyage beyond the solar system’s edge, and engineers must now make difficult calls about which instruments should be shut down to prolong its travels. Each decision involves a delicate balance between safeguarding the craft and uncovering fresh discoveries at the universe’s remote frontier.As it journeys farther into interstellar space, Voyager 1 has shifted into a new operational stage, one centered on conserving resources rather than expanding capabilities, and in mid-April, NASA engineers sent a command to shut down one of the probe’s scientific instruments to save power and extend its functional lifespan, a…

Artificial intelligence workloads have reshaped how cloud infrastructure is designed, deployed, and optimized. Serverless and container platforms, once focused on web services and microservices, are rapidly evolving to meet the unique demands of machine learning training, inference, and data-intensive pipelines. These demands include high parallelism, variable resource usage, low-latency inference, and tight integration with data platforms. As a result, cloud providers and platform engineers are rethinking abstractions, scheduling, and pricing models to better serve AI at scale.How AI Processing Strains Traditional Computing PlatformsAI workloads vary significantly from conventional applications in several key respects:Elastic but bursty compute needs: Model training may…

Vision-language-action models, commonly referred to as VLA models, are artificial intelligence frameworks that merge three fundamental abilities: visual interpretation, comprehension of natural language, and execution of physical actions. In contrast to conventional robotic controllers driven by fixed rules or limited sensory data, VLA models process visual inputs, grasp spoken or written instructions, and determine actions on the fly. This threefold synergy enables robots to function within dynamic, human-oriented settings where unpredictability and variation are constant.At a high level, these models connect camera inputs to semantic understanding and motor outputs. A robot can observe a cluttered table, comprehend a spoken instruction…