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Prefill vs Decode in LLMs: Key Differences and Performance
Explore the key differences between Prefill and Decode in LLMs, how each stage uses GPU resources, and how TTFT, TPOT, and KV caching affect inference performance.
Fatemeh Jahangard · Nov 10, 2026 · 15 min read - AI
LLM Quantization for Inference: Methods, Memory, and Speed
Explore how LLM quantization reduces GPU memory usage, compare FP8, INT8, INT4, and leading quantization methods, and understand their impact on inference speed and model accuracy.
Fatemeh Jahangard · Nov 10, 2026 · 14 min read - AI
Speculative Decoding Explained: How It Speeds Up LLM Inference
Explore how speculative decoding accelerates LLM inference through draft models, parallel token verification, and efficient generation without compromising output quality.
Fatemeh Jahangard · Nov 9, 2026 · 13 min read - AI
Continuous Batching for LLMs: How It Works and Improves Throughput
Learn how continuous batching improves LLM inference throughput, manages concurrent requests, and balances GPU utilization with latency in production.
Fatemeh Jahangard · Nov 9, 2026 · 14 min read - AI
KV Cache in LLMs Explained: How It Works and Memory Usage
Understand how KV caching reduces repeated attention calculations, how much GPU memory it consumes, and how to manage cache storage for efficient LLM inference.
Fatemeh Jahangard · Nov 8, 2026 · 14 min read - AI
LLM Inference Optimization: Techniques, Latency, and GPU Efficiency
Discover how to optimize LLM inference by reducing latency, increasing token throughput, improving GPU memory efficiency, and lowering serving costs.
Fatemeh Jahangard · Nov 8, 2026 · 14 min read - AI
Feature Store Explained: Architecture, Types, and Use Cases
Feature Stores help machine learning teams manage reusable features and maintain consistent data for training and inference. Explore their architecture, types, and practical applications.
Fatemeh Jahangard · Nov 6, 2026 · 13 min read - AI
Best MLOps Tools in 2026: Features, Comparison, and Use Cases
Compare leading MLOps tools by use case, infrastructure requirements, and cost to find the right combination for your machine learning projects.
Fatemeh Jahangard · Nov 5, 2026 · 15 min read - AI
CI/CD for Machine Learning: Pipelines, Testing, and Automation
Learn how CI/CD for Machine Learning automates testing, model validation, and release workflows. Explore pipeline stages, quality gates, and practical implementation.
Fatemeh Jahangard · Nov 5, 2026 · 11 min read - AI
ML Model Registry Explained: Versioning, Lineage, and Workflow
Managing multiple machine learning models requires more than storing files. Discover how an ML Model Registry simplifies versioning, model lineage, approval workflows, and model management.
Fatemeh Jahangard · Nov 4, 2026 · 11 min read - AI
Model Drift Explained: Causes, Types, and Detection Methods
Machine learning models can lose accuracy as data and real world conditions change. Explore the causes, types, and detection methods of model drift and how to maintain reliable predictions.
Fatemeh Jahangard · Nov 4, 2026 · 11 min read - AI
Model Monitoring Explained: Process, Metrics, and Tools
A deployed model can keep running while its predictions lose accuracy. Learn how model monitoring tracks performance, detects changes, and helps teams maintain reliable machine learning systems.
Fatemeh Jahangard · Nov 3, 2026 · 10 min read - AI
Model Deployment Explained: Process, Methods, and Strategies
Model deployment turns trained machine learning models into working applications. Explore deployment methods, production workflows, release strategies, and the tools behind reliable predictions.
Fatemeh Jahangard · Nov 3, 2026 · 10 min read - AI
MLOps Explained: How It Works, Lifecycle, Benefits, and Tools
A machine learning model is only as useful as its performance in production. Explore how MLOps connects development, deployment, monitoring, and continuous improvement.
Fatemeh Jahangard · Nov 2, 2026 · 11 min read - AI
AI Lip Sync Video: How to Sync Audio and Make Talking Videos
Learn how to create realistic AI lip sync videos from photos or existing footage, compare leading tools, and synchronize speech with natural mouth movements.
Fatemeh Jahangard · Nov 2, 2026 · 13 min read - AI
AI Video Upscaling: How to Upscale Videos to 4K and Best Tools
Learn how to upscale videos to 4K with AI, compare the best video upscaling tools, and improve resolution while preserving natural details and motion.
Fatemeh Jahangard · Nov 1, 2026 · 12 min read - AI
AI Video Character Consistency: Keep the Same Character Across Scenes
Learn how to keep AI characters consistent across multiple video scenes using reference images, character sheets, practical prompts, and proven workflows.
Fatemeh Jahangard · Nov 1, 2026 · 13 min read - AI
AI Video Prompting: How to Write Better Prompts with Examples
Learn how to write effective AI video prompts with practical examples, camera movement techniques, and tips for creating more controlled video results.
Fatemeh Jahangard · Oct 31, 2026 · 13 min read - AI
Image to Video AI: How to Turn Photos into Videos and Best Tools
Turn still images into moving videos with AI. Explore the best image to video tools, practical animation methods, motion controls, and tips for improving video quality.
Fatemeh Jahangard · Oct 31, 2026 · 13 min read - AI
Integrated Gradients: How It Works and Examples
Explore how Integrated Gradients explains neural network predictions through feature attribution, baseline comparisons, practical examples, and visual interpretation.
Fatemeh Jahangard · Oct 30, 2026 · 15 min read
