AI Infrastructure (6 articles)

Chroma Vector Database: The Open-Source Foundation for AI Search

The Economics of AI Training and Inference: How DeepSeek Broke the Cost Curve

AI training and inference costs are reshaping the AI industry, with DeepSeek, OpenAI, and Google optimizing architectures for efficiency. Explore how AI models are driving down computational expenses and redefining the business of artificial intelligence.

How DeepSeek-R1 Was Built: Architecture and Training Explained

Explore the DeepSeek-R1 Architecture and Training Process, from its Mixture of Experts (MoE) design to its reinforcement learning-based training. Learn how its expert routing, parallelization strategy, and optimization techniques enable high-performance AI at reduced computational costs.

Running OpenChat and Zephyr Locally – How They Compare to DeepSeek R1

Learn how to run OpenChat and Zephyr locally and compare their performance with DeepSeek R1. Discover installation steps, use cases, and practical insights on leveraging these powerful open-source LLMs.

Collaboration and Competition: Shaping the Future of AI Innovation

Discover how OpenAI, Microsoft, Google, Meta, Anthropic, and DeepMind are shaping the future of AI innovation through collaboration and competition, driving breakthroughs in superintelligence.

Serverless for AI: Redefining Scalability and Efficiency

Discover how serverless AI transforms scalability and efficiency, with no infrastructure management, dynamic scaling, and cost-effective solutions.