Trends
In-depth analysis of the latest tech trends, with highlights of the top research from the world's standard-bearer for computing professionals.
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By Eric Arnold
Quantum Algorithms That Work
A central problem in quantum computing is the development of domain-specific algorithms that enable real scientific and economic contributions. Quantum algorithms in numerous domains such as finance, chemistry, physics, and biology are being developed with the intention of achieving quantum advantage, i.e. to der...
By Gopinath Kathiresan
Modern businesses are rushing to adopt artificial intelligence (AI) technologies, but this rapid integration comes with unexpected challenges. A phenomenon known as "hallucinations" occurs in large language models (LLMs) and deep learning systems and threatens software quality and trust. These hallucinations occur when AI presents false informati...
By Paul Chaney
As supply chains generate ever-larger datasets and demand faster decisions, traditional central processing unit (CPU)-based systems are approaching their limits. To meet real-time requirements at scale, developers turn to accelerated computing powered by graphics processing units (GPUs). These massive parallel processors reshape how data is acces...
By Amit Singh
The way we work has fundamentally shifted, with hybrid and remote models becoming a widespread reality. This evolution brings tremendous benefits but also presents significant challenges for IT and security teams tasked with ensuring seamless access to applications and protecting sensitive data outside the traditional corporate perimeter.
Tradit...
By Xiaojun Yuan, Ye Tian, Huiyuan Zhang
"Guide for Application of Knowledge Graphs for Rail Transit," designated by the Project Number P2807.9, is a groundbreaking standard that has significantly impacted the rail transit industry. By providing a comprehensive framework for the development and implementation of Knowledge Graphs (KG), specifically tailored for the rail transit sector, ref...
By Amit Singh
Extended Detection and Response (XDR) is a modern security technology designed primarily as a Security Operations Centre (SOC) enabler tool. It addresses the complexities and challenges faced by security teams in today's evolving threat landscape. The core idea behind XDR is to take challenging incident response processes and make security analys...
By IEEE Computer Society Team
Quantum annealing (QA) has emerged as an effective way to find the optimal solution using a large dataset. While this has applications in an endless variety of use cases, its application in the realm of finance may be one of the fastest ways for researchers to realize a significant ROI in their annealing work.
Yao-Hsin Chou, Ching-Hsuan Wu, Pei-...
By Rambabu Bandam
Introduction
Standard large language models (LLMs) possess vast knowledge but struggle with limitations like hallucinations and accessing real-time information due to their static training data. This has spurred the development of dynamic AI architectures. Retrieval-Augmented Generation (RAG) has emerged as a key solution, integrating extern...
By Rambabu Bandam
Bridging the Visual Gap with Sound in 2025
As AI innovations reshape technology landscapes in 2025, accessibility for visually impaired users is gaining unprecedented momentum. Currently, an estimated 285 million people globally experience some degree of visual impairment, limiting their ability to fully engage with visually driven data envi...
By Madhu Chavva
Back in the 90s, when I was in school, education was like a uniform everyone had to wear—the same textbooks, the same blackboard, and the same hurried lessons for all. If you fell behind, your only lifeline was to awkwardly raise your hand in the middle of class or spend hours in the library after school, rifling through reference books. Fast f...
By Vaibhav Pandey
The convergence of artificial intelligence (AI), machine learning (ML), and quantum computing unlocks groundbreaking advancements in software engineering. Quantum computing accelerates ML model training, solves complex optimization problems, and enables new AI architectures that classical computing struggles to support. At the same time, AI and M...
By Rambabu Bandam
Artificial intelligence (AI) has rapidly permeated every facet of modern life, seamlessly performing tasks ranging from trivial errands to complex decision-making processes. The allure of AI lies predominantly in its unmatched potential for efficiency, convenience, and accuracy. However, this unprecedented convenience brings with it a hidden yet ...
By Michael Martin
Digital twins—virtual models that simulate real-world city dynamics—are transforming urban transportation and mobility planning. These intelligent systems integrate real-time data, machine learning (ML) algorithms, and transportation research to optimize citywide solutions. By simulating traffic patterns, travel demand, and road dynamics, cit...
By Eric Arnold
Since its conception in the 1980s, quantum computing (QC) has presented academia and industry with numerous challenges as the technology has scaled. While QC systems have grown exponentially, with qubit numbers per system increasing from single digits to more than a thousand, a byproduct of this growth is a fragmented software and hardware ecosys...
By Randy Rozema
Integrating physical and virtual testing environments into research and development (R&D) is rapidly moving from a cutting-edge concept to standard practice across many industries. Organizations that take this approach gain a variety of benefits that improve efficiency. Among the advantages is the ability to minimize prototype builds, optimize te...
By Jiewu Leng
Introduction
The rapid development of electronic products results in a significant need for either upgrading existing electronics production lines (EPLs) or designing newEPLs. Changes in product orders also lead to a frequent reconfiguration of electronics production lines. However, due to unreasonable design, many EPLs fail to meet the init...
By Isla Banda
AI is having a major impact on society, from consumer technologies to driving businesses. But among all these large language models and deep neural networks, there are lurking inefficiencies that most people aren't taking into account. Wasted computational power, hidden costs, the environmental footprint, and more. Whether these inefficiencies ar...
By Kunal Khanvilkar
Ensuring regulatory compliance is a high-stakes challenge across industries. Banks, payroll processors, and legal firms alike grapple with complex rules and massive data — and the consequences of failure are severe. In 2024, U.S. regulators fined Citigroup $136 million for falling short in fixing data management issues flagged years prior [1]. In...
By Isla Banda
Consensus in blockchain isn't just a technical problem—it's an intellectual minefield. You've got decentralized nodes spread across the globe, each operating under different assumptions, with varying latencies, incentives, and potential motivations, and yet they're all expected to come to the same conclusion about the state of a distributed led...
By Isla Banda
They aren't your average hires. They don't glide through job interviews or thrive in open-plan offices. But when it comes to pattern recognition, threat modeling, or zero-day hunting, neurodiverse individuals often outperform their peers. And yet, they remain largely untapped in the cybersecurity workforce. If we're serious about fortifying digit...
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