Science and Technology

Artificial intelligence systems are increasingly used to generate scientific results, including hypotheses, data analyses, simulations, and even full research papers. These systems can process massive datasets, identify patterns faster than humans, and automate parts of the scientific workflow that once required years of training. While these capabilities promise faster discovery and broader access to research tools, they also introduce ethical debates that challenge long-standing norms of scientific integrity, accountability, and trust. The ethical concerns are not abstract; they already affect how research is produced, reviewed, published, and applied in society.Authorship, Attribution, and AccountabilityOne of the most immediate ethical debates concerns…

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 usually defined by body mass index (BMI) thresholds (BMI ≥30 kg/m² for adults), but BMI is a crude measure that…

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…

Humanity’s farthest spacecraft presses onward in quiet solitude beyond the bounds of the solar system, and to sustain its journey, engineers now face tough decisions about which instruments must be powered down. Every choice demands a careful trade‑off between preserving the craft and pursuing new insights at space’s outer 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…

Humanity’s most distant spacecraft continues its silent voyage beyond the solar system. To keep it alive, engineers are making difficult choices about which instruments must go dark. Each decision reflects a delicate balance between survival and discovery at the edge of space.As it ventures deeper into interstellar space, Voyager 1 has entered a new phase of its mission—one defined by careful resource management rather than expansion of capabilities. In mid-April, engineers at NASA issued a command to deactivate one of the probe’s scientific instruments, a move aimed at conserving energy and prolonging the spacecraft’s operational life. The decision underscores both…

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 Workloads Put Pressure on Conventional PlatformsAI workloads differ from traditional applications in several important ways:Elastic but bursty compute needs: Model training may…

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 reshaped how cloud infrastructure is designed, deployed, and optimized, prompting serverless and container-driven platforms once focused on web and microservice applications to rapidly evolve to meet the unique demands of machine learning training, inference, and data-intensive workflows; these needs include extensive parallel execution, variable resource usage, ultra‑low‑latency inference, and frictionless connections to data ecosystems, leading cloud providers and platform engineers to rethink abstractions, scheduling methods, and pricing models to better support AI at scale.How AI Processing Strains Traditional Computing PlatformsAI workloads differ from traditional applications in several important ways:Elastic but bursty compute needs: Model training may…

Obesity and excess weight are chronic, relapsing conditions with complex biological, environmental, and behavioral drivers. Medications for weight management are increasingly important tools that can produce clinically meaningful weight loss, improve metabolic health, and reduce disease burden when used as part of a broader treatment plan. This article explains how these drugs work, summarizes evidence of benefit, lists key risks, and sets realistic expectations for patients and clinicians.How weight-loss medications workMedications influence multiple physiological systems involved in appetite control, fullness signals, digestive processes, and overall energy regulation:Appetite-modulating incretin receptor agonists (GLP-1 and dual GLP-1/GIP agonists) curb hunger, enhance satiety, and…