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By Shenson Joseph
Generative AI refers to those algorithms that have the ability to create new content-image, text, music, or whatsoever-based on the patterns the algorithm learns from existing data. This technology has started to gain remarkable attention in recent times for its applications across different industries. On the other hand, edge computing…
By Loganandh Natarajan
In the healthcare sector, revenue cycle management (RCM) is a process—patient registration through billing, collections, and reimbursement. Traditional RCM systems, while essential to profitability, are paper-based systems that are prone to inefficiency and mistake. Manual processes generate higher costs, delayed turnaround, and ultimately lost income opportunities. Generative AI is changing…
By Santosh Bhupathi
AI revolutionizes enterprise architecture by simplifying complex workflows and minimizing manual tasks to achieve greater scalability. The current business landscape requires organizations to manage massive data-driven operations which still depend on obsolete manual processes. Businesses can achieve greater scalability by using AI-driven automation which enhances efficiency and eliminates operational bottlenecks…
By Santosh Bhupathi
Introduction to Generative AI Generative AI (GenAI) represents a transformative leap in artificial intelligence, enabling machines to create human-like content, generate insights, and enhance decision-making across various domains. Unlike traditional AI models that classify or predict based on predefined patterns, GenAI leverages advanced machine learning techniques, such as deep learning…
By Pritesh Patel
Alert!!! This isn’t just another typical generative AI blog. It’s an opportunity to step beyond the basics and explore the lesser-known, often surprising aspects of what these models come up with when we step out of the room. Curious? Now imagine this. A generative model working silently in a data…
By IEEE Computer Society Team
Security verification for hardware is literally foundational: hardware resides on technology’s ground floor, so attacks on it can impact every floor above it, including operating systems, applications, and communications. To examine technology’s hardware foundation, a group of researchers recently used simulation-based hardware information-flow tracking (IFT) for hardware security verification. IFT…
By IEEE Computer Society Team
In a boon for student engagement in computer science and engineering disciplines, 70 pre-college students gathered for the IEEE Computer Society (CS) Juniors Program in Sayama, Japan. Over two days, these junior, middle, and high school students experienced the excitement of programming and artificial intelligence (AI) through creative, hands-on activities…
By IEEE Computer Society Team
Software-only solutions for preventing attackers from exploiting memory errors face two problems: They are too expensive to be broadly deployed. They are prone to circumvention. These issues have motivated researchers to explore how to build and implement more reliable, efficient defensive features in hardware. Exploring Hardware Security Approaches The ongoing…
By Shan Liu, Wenjie Zhu, Ge Li, Xiaoxu Luan
Introduction IEEE P3366.1 (Standard for Geometry Point Cloud Compression) aims at the standardization of point cloud compression technologies. There is a practical demand for point cloud compression standardization, especially for the transmission of high-volume volumetric data over bandwidth-constrained networks and the processing of such data on storage-constrained consumer devices. Point…
By IEEE Computer Society Team
When traditional semiconductor technologies are unable to meet specific nonfunctional requirements of emerging products—including for factors such as energy consumption, peak power dissipation, and chip cost and/or size—new technologies must emerge to fill the gap. In a recent IEEE Security & Privacy column, “Hardware Security in the Era of Emerging…
By IEEE Computer Society Team
Deep neural networks will be crucial to future human–machine teams aiming to modernize safety-critical systems. Yet DNNs have at least two key problems: Researchers have proposed many defense schemes to counter many attack vectors, yet none have yet secured DNNs from adversarial examples (AEs). This DNN vulnerability to AEs renders…
IEEE Transactions on Software Engineering (TSE) Celebrates 50 Years of Excellence with Special Issue
For 50 years, the IEEE Transactions on Software Engineering (TSE) has published influential research on the field of software engineering, and in celebration of its 50 years of excellence, IEEE CS is honoring the journal with a special issue this March. Designed to be both retrospective and forward-looking, the TSE…
By IEEE Computer Society Team
As AI applications proliferate across industries and sectors, two key security questions arise: Are these AI applications cyber-secure? Can bad actors exploit them through attacks? A recent article discusses these questions in relation to AI’s Achilles’ heel: adversarial machine learning (AdvML). In “Lights Toward Adversarial Machine Learning: The Achilles’ Heel…
By IEEE Computer Society Team
For all its promised benefits and applications across industries, AI remains neither fully transparent nor explainable. For this and other reasons, AI is challenging us in myriad ways, both in what we must learn and how we must learn it—and it is doing so at warp speed. The Computer article,…
By Sukhdeep Saini
In today’s lightning-fast software world, meeting tight deadlines and high-quality standards makes swift and efficient testing and release processes more crucial than ever. Cloud computing advancements have significantly transformed the software development lifecycle (SDLC), with container technologies such as Docker and Kubernetes leading in this transformation. These game-changing tools have…
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