AWS S3, Garage, or MinIO - overview and comparison.
AWS S3 remains the “default” baseline for object storage: it is fully managed, strongly consistent, and designed for extremely high durability and availability. Garage and MinIO are self-hosted, S3-compatible alternatives: Garage is designed for lightweight, geo-distributed small-to-medium clusters, while MinIO emphasises broad S3 API feature coverage and high performance in larger deployments.
Garage is an open-source, self-hosted, S3-compatible object storage system designed for small-to-medium deployments, with a strong emphasis on resilience and geo-distribution.
Strategic guide to hosting large language models locally with Ollama, llama.cpp, vLLM, or in the cloud. Compare tools, performance trade-offs, and cost considerations.
Running large language models locally gives you privacy, offline capability, and zero API costs.
This benchmark reveals exactly what one can expect from 14 popular
LLMs on Ollama on an RTX 4080.
The Go ecosystem continues to thrive with innovative projects spanning AI tooling, self-hosted applications, and developer infrastructure. This overview analyzes the top trending Go repositories on GitHub this month.
vLLM is a high-throughput, memory-efficient inference and serving engine for Large Language Models (LLMs) developed by UC Berkeley’s Sky Computing Lab.
Choosing the Best LLM for Cognee demands balancing graph-building quality, hallucination rates, and hardware constraints.
Cognee excels with larger, low-hallucination models (32B+) via Ollama but mid-size options work for lighter setups.
Ollama’s Python library now includes native OLlama web search capabilities. With just a few lines of code, you can augment your local LLMs with real-time information from the web, reducing hallucinations and improving accuracy.
Choosing the right vector store can make or break your RAG application’s performance, cost, and scalability. This comprehensive comparison covers the most popular options in 2024-2025.