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Science and technology

How are reinforcement learning and simulation improving robot dexterity?

Reinforcement learning and simulation: boosting robot dexterity

Robotic dexterity refers to a machine’s ability to manipulate objects with precision, adaptability, and reliability in complex, changing environments. Tasks such as grasping irregular objects, assembling components, or handling fragile items require subtle control that has historically been difficult to program explicitly. Reinforcement learning and large-scale simulation have emerged as complementary tools that are reshaping how robots acquire these skills, moving dexterity from rigid automation toward flexible, human-like manipulation.Foundations of Reinforcement Learning for Dexterous ControlReinforcement learning is a learning paradigm in which an agent improves its behavior by interacting with an environment and receiving feedback in the form of rewards…
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An asteroid discovered days ago will narrowly miss Earth

Asteroid spotted days ago to pass very close to Earth

A recently discovered asteroid will make a relatively close approach to Earth this Monday, drawing the attention of astronomers and space agencies worldwide. Despite the short cosmic distance, experts emphasize that the object represents no danger to the planet and will safely continue its journey 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,…
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How are companies preparing for phishing and deepfake threats at scale?

How do businesses prepare for widespread phishing and deepfake attacks?

Phishing has evolved from crude email scams into highly targeted, data-driven attacks, while deepfakes have moved from novelty to operational threat. Together, they create a scalable risk that can undermine trust, drain finances, and compromise strategic decisions. Companies are preparing for these threats by recognizing a central reality: attackers now combine social engineering, artificial intelligence, and automation to operate at unprecedented speed and volume.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. Executives have been…
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Obesity: why the approach is changing

Changing perspectives on obesity treatment

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 usually defined by body mass index (BMI) thresholds (BMI ≥30 kg/m² for adults), but BMI is a crude…
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What trends are reshaping software development with AI code generation?

What are the latest software development trends influenced by AI code generation?

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 can craft new…
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How are serverless and container platforms evolving for AI workloads?

AI Workloads: Serverless and Container Platform Trends

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.Why AI Workloads Stress Traditional PlatformsAI workloads differ greatly from traditional applications across several important dimensions:Elastic but bursty compute needs: Model training can…
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What is a keyword and how do you choose one?

The Significance of Vision-Language-Action Models in Robotics

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 broad perspective, these models link visual inputs from cameras to higher-level understanding and corresponding motor actions, enabling a robot to look at a messy…
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What trends are emerging in privacy tech for data sharing and analytics?

Unpacking Emerging Privacy Tech for Data Sharing & Analytics?

Data sharing and analytics drive modern innovation, yet growing regulatory demands, shifting consumer expectations, and the rising expense of data breaches are pushing organizations to reconsider how information is accessed and interpreted. Privacy technology has progressed from simple compliance tools to a strategic foundation that supports collaboration, sophisticated analytics, and artificial intelligence while lowering exposure to risk. Several distinct trends are now defining this environment, marking a transition from perimeter-focused protection to privacy capabilities woven directly into data workflows.Privacy-Enhancing Technologies Gain Widespread AdoptionA major emerging trend involves the use of privacy‑enhancing technologies, commonly referred to as PETs, which let organizations…
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What trends are accelerating brain-computer interface research?

Medical-Grade Wearables: The Future of Health Monitoring

Wearable technology emerged as a popular fitness accessory aimed at logging steps, monitoring calories, and promoting healthier routines. Early devices prioritized straightforward features and broad accessibility, supplying simple data that nudged users toward regular activity. Over the last ten years, however, wearables have evolved considerably. They are now crafted to provide medical-grade insights that aid in preventing illnesses, supporting diagnoses, and managing long-term health conditions.This shift reflects broader changes in healthcare, technology, and consumer expectations. As sensors become more accurate and data analytics more sophisticated, wearables are moving beyond lifestyle enhancement into the realm of clinical relevance.Progress in Sensor Technology…
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Why is vector search becoming a core database capability?

The Rise of Vector Search in Databases

Vector search has evolved from a niche research method into a core capability within today’s databases, a change propelled by how modern applications interpret data, users, and intent. As organizations design systems that focus on semantic understanding rather than strict matching, databases are required to store and retrieve information in ways that mirror human reasoning and communication.Evolving from Precise Term Matching to Semantically Driven RetrievalTraditional databases are optimized for exact matches, ranges, and joins. They work extremely well when queries are precise and structured, such as looking up a customer by an identifier or filtering orders by date.Many contemporary scenarios…
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