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14 articles
Learn to deploy an open-source openDesk environment using Docker containers, replicating the approach Swiss government divisions are taking to migrate from Microsoft 365.
CUA-Lite is a new open platform from UC Berkeley that unifies sandboxes, data, evaluation, and reinforcement learning for computer-use agents, enabling more efficient and standardized AI agent development.
Learn how to deploy AI workloads on Nvidia-powered data center infrastructure using containerization and GPU optimization techniques.
Learn to set up a GPU-accelerated AI development environment using NVIDIA CUDA, Docker containers, and popular AI frameworks like PyTorch and TensorFlow. This tutorial teaches you how to create a scalable AI infrastructure similar to what's being built by Nvidia and SoftBank investments.
Learn how to build and manage a distributed data center infrastructure using Kubernetes, Docker, and monitoring tools, similar to the large-scale infrastructure investments being made by companies like Orange and Morrison.
Learn to build and evaluate an agentic coding system similar to KAT-Coder-V2.5, implementing environment construction and sandbox auditing techniques.
Learn to build a secure AI sandbox environment that prevents unauthorized access and maintains control over AI systems, similar to the scenario described in the recent OpenAI-Hugging Face incident.
Learn to create a secure AI sandbox environment that demonstrates containment principles similar to those mentioned in recent OpenAI security incidents.
Learn to build a robot control system using ROS 2 that demonstrates safe and legal robot testing practices, avoiding unauthorized use of residential properties.
Learn how to set up and deploy the LiteLLM Agent Platform using Docker and Kubernetes for isolated AI agent sandboxes and persistent session management.
Learn how to set up a basic AI data center simulation using Python and Docker, mimicking the infrastructure work behind companies like Hut 8's transition from Bitcoin mining to AI computing.
Learn how to build scalable AI applications that can match large organization outputs using containerization, dynamic compute management, and cloud orchestration.
