DeepLearning

This comprehensive guide provides background and a detailed comparison of Anaconda, Miniconda, and Mamba - three powerful tools that have become essential for Python developers and data scientists working with complex dependencies and scientific computing environments.

The proliferation of AI-generated content has created a new challenge: distinguishing genuine human writing from “AI slop” - low-quality, mass-produced synthetic text.

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.

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

Apache Airflow is an open-source platform designed to programmatically author, schedule, and monitor workflows, - entirely in Python code, offering a flexible and powerful alternative to traditional, manual, or UI-based workflow tools.

How PCIe Lanes Affect LLM Performance? Depending on the task. For training and multi-gpu inferrence - perdormance drop is significant.

In the midst of the modern world’s turmoil here I’m comparing tech specs of different cards suitable for AI tasks (Deep Learning, Object Detection and LLMs). They are all incredibly expensive though.

I’ve used MMDetection (mmengine, mdet, mmcv) quite a bit, And now looks like it’s out of the game. It’s a pity. I liked it’s model zoo.

On one cold winter day in July … that is in Australia … I felt urgent need to train AI model for detecting uncapped concrete reinforcement bars…