Docker

vLLM is a high-throughput, memory-efficient inference and serving engine for Large Language Models (LLMs) developed by UC Berkeley’s Sky Computing Lab.

Cognee is a Python framework for building knowledge graphs from documents using LLMs. But does it work with self-hosted models?

Local deployment of LLMs has become increasingly popular as developers and organizations seek enhanced privacy, reduced latency, and greater control over their AI infrastructure.

Modern Go development demands rigorous code quality standards. Linters for Go automate the detection of bugs, security vulnerabilities, and style inconsistencies before they reach production.

As AI and ML workloads become increasingly complex, the need for robust orchestration systems has become greater. Go’s simplicity, performance, and concurrency makes it an ideal choice for building the orchestration layer of ML pipelines, even when the models themselves are written in Python.

Cross-modal embeddings represent a breakthrough in artificial intelligence, enabling understanding and reasoning across different data types within a unified representation space.

The democratization of AI is here. With open-source LLMs like Llama 3, Mixtral, and Qwen now rivaling proprietary models, teams can build powerful AI infrastructure using consumer hardware - slashing costs while maintaining complete control over data privacy and deployment.

Prometheus has become the de facto standard for monitoring cloud-native applications and infrastructure, offering metrics collection, querying, and integration with visualization tools.

Building high-performance REST APIs with Go has become a standard approach for powering systems at Google, Uber, Dropbox, and countless startups.

Grafana is the leading open-source platform for monitoring and observability, transforming metrics, logs, and traces into actionable insights through stunning visualizations.

Helm has revolutionized Kubernetes application deployment by introducing package management concepts familiar from traditional operating systems.

Linux has become the de facto operating system for data science professionals, offering unmatched flexibility, performance, and a rich ecosystem of tools.

Configuring context sizes in Docker Model Runner is more complex than it should be.

Docker Model Runner is Docker’s official tool for running AI models locally, but enabling NVidia GPU acceleration in Docker Model Runner requires specific configuration.

When data is the a valuable asset, securing it has never been more critical. From the moment information is created to the point it’s discarded, its journey is fraught with risks - whether stored, transferred, or actively used.

Choosing the right headless CMS can make or break your content management strategy. Let’s compare three open-source solutions that influence how devs build content - driven applications.