Science and Technology

How are reinforcement learning and simulation improving robot dexterity?

Advanced robot dexterity: RL and simulation methods

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.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 context…
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How are companies preparing for phishing and deepfake threats at scale?

Companies’ readiness for phishing and deepfake threats on a large scale

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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What trends are reshaping software development with AI code generation?

Understanding the trends in AI code generation for dev

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 Everywhere: From IDEs to the Entire 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 functions, reorganize outdated…
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What trends are emerging in privacy tech for data sharing and analytics?

What’s New in Privacy Tech for Data Sharing and Analytics?

Data sharing and analytics are essential for innovation, but rising regulatory pressure, consumer expectations, and the cost of data breaches are forcing organizations to rethink how data is accessed and analyzed. Privacy technology has evolved from basic compliance tooling into a strategic layer that enables collaboration, advanced analytics, and artificial intelligence while reducing risk. Several clear trends are shaping this landscape, reflecting a shift from perimeter-based security to privacy embedded directly into data workflows.Privacy-Enhancing Technologies Become MainstreamOne of the strongest trends is the adoption of privacy-enhancing technologies, often abbreviated as PETs. These tools allow organizations to analyze or share data…
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