Category: Artificial Intelligence - Page 2

Containerizing large language models requires precise CUDA version matching, optimized Docker images, and secure model formats like .safetensors. Learn how to reduce startup time, shrink image size, and avoid the most common deployment failures.

Learn how to choose optimal batch sizes for LLM serving to cut cost per token by up to 87%. Discover real-world results, batching types, hardware trade-offs, and proven techniques to reduce AI infrastructure costs.

Vibe coding lets fintech teams build tools with natural language prompts instead of code. Learn how mock data, compliance guardrails, and AI-powered workflows are changing how financial apps are developed-without sacrificing security or regulation.

Learn how hardware-friendly LLM compression lets you run powerful AI models on consumer GPUs and CPUs. Discover quantization, sparsity, and real-world performance gains without needing a data center.

NLP pipelines and end-to-end LLMs aren't competitors-they're complementary. Learn when to use each for speed, cost, accuracy, and compliance in real-world AI systems.

Training data poisoning lets attackers corrupt AI models with tiny amounts of fake data, leading to hidden backdoors and dangerous outputs. Learn how it works, real-world cases, and proven defenses to protect your LLMs.

Error-forward debugging lets you feed stack traces directly to LLMs to get instant, accurate fixes for code errors. Learn how it works, why it's faster than traditional methods, and how to use it safely today.

Most LLMs are overconfident in their answers. Token probability calibration fixes this by aligning confidence scores with real accuracy. Learn how it works, which models are best, and how to apply it.

LLM-powered semantic search is transforming e-commerce by understanding user intent instead of just matching keywords. See how it boosts conversions, reduces abandonment, and what you need to implement it successfully.

Learn how to choose between NVIDIA A100, H100, and CPU offloading for LLM inference in 2025. See real performance numbers, cost trade-offs, and which option actually works for production.

Learn how to visualize LLM evaluation results effectively using bar charts, scatter plots, heatmaps, and parallel coordinates. Avoid common pitfalls and choose the right tool for your needs.

Speculative decoding and Mixture-of-Experts (MoE) are cutting LLM serving costs by up to 70%. Learn how these techniques boost speed, reduce hardware needs, and make powerful AI models affordable at scale.