AI Ethics
Artificial intelligence (AI) is becoming essential to daily life, but its impact goes beyond convenience and efficiency. AI ethics are about ensuring that AI technology is developed and used responsibly.
Artificial Intelligence (AI)
Artificial Intelligence (AI) is a branch of computer science that focuses on creating machines or software capable of performing tasks that require human intelligence, like learning, problem-solving, decision-making, perception, and
Attention Mechanism
The attention mechanism is a core concept in deep learning, especially in natural language processing (NLP). It allows models to focus on the most relevant input parts when generating an
Auto-Scaling
Auto-scaling refers to automatically adjusting the number of computing resources assigned to a particular application or service based on its current demand. This technology is often used in cloud computing
Bias in AI
Bias in AI happens when artificial intelligence systems make unfair decisions. This means the AI favors one group over another. The unfairness comes from the data, how the system is
Chargeback in Cloud Computing
Chargeback in cloud computing is the practice of attributing the costs of cloud resources to the specific business units, departments, or projects that utilize those resources. This method helps promote
Cloud Cost Management
Cloud cost management, also known as cloud cost optimization, involves organizing and controlling the costs and operations of cloud technology within an organization. This includes identifying and implementing cost-effective strategies
Computational Creativity
Computational creativity is a field of study in artificial intelligence (AI) focused on building software and systems that can perform tasks typically associated with human creativity. This includes creating original
Container Cost Optimization
Container cost optimization refers to the practices and strategies employed to manage and reduce the costs of running containerized applications in cloud environments. This process involves maximizing resource utilization efficiency
Cost Allocation Tags
Cost allocation tags are key-value pairs attached to AWS resources that allow organizations to categorize and track their AWS costs with high granularity. These tags enable organizations to assign costs
Cost Anomaly Detection
Cost anomaly detection utilizes machine learning to identify and alert to unusual spending patterns within an organization’s AWS services. This tool is essential for monitoring and managing cloud costs by
Data Augmentation
Data augmentation is generating new data samples by modifying existing data. It helps improve machine learning (ML) model performance by increasing data variety without collecting more real-world data. The process
Data Transfer Costs
Data transfer costs in cloud computing refer to the fees associated with moving data within and between cloud services, across different regions, or from the cloud to on-premises environments. These
Deep Learning
Deep learning is a subset of machine learning that uses algorithms modeled after the human brain’s neural networks. It enables computers to analyze and learn from large amounts of data,
Diffusion Models
Diffusion models are generative machine learning models that create data, such as images, text, or audio, by reversing a noise process. They learn to generate high-quality outputs by gradually denoising
Dynamic Provisioning
Dynamic provisioning in cloud computing and data centers refers to the automated process of allocating and managing storage resources on demand. This technology eliminates the need for administrators to manually
Egress Charges
Egress charges refer to the fees incurred when data is transferred from a cloud provider’s network to another location, such as another cloud service, an on-premises data center, or the
Elasticity
Elasticity in cloud computing refers to the ability of a cloud environment to dynamically allocate and de-allocate resources as needed to handle fluctuating workloads efficiently. This capability allows systems to
Embeddings
Embeddings are a technique used in machine learning and natural language processing (NLP) to represent data—especially words, sentences, or items—as numerical vectors. These vectors capture the relationships, context, and similarities
Explainable AI (XAI)
What Is Explainable AI (XAI)? Explainable AI (XAI) refers to artificial intelligence systems that make their decision-making processes transparent. Unlike traditional AI models that work like black boxes, XAI provides
