A detailed guide for building a powerful AI training system has been published by machine learning engineer Sabareesh Subramani on his personal website. The setup, costing approximately $12,000, uses four NVIDIA 4090 graphics cards to train large language models (LLMs) similar to but much smaller than ChatGPT. The system can effectively train AI models with up to 500 million parameters.
Subramani explains that the setup requires specific hardware components, including an AMD Threadripper PRO processor, 128 GB of memory, and dual 1500-watt power supplies. The NVIDIA 4090 graphics cards were chosen for their 24 GB of video memory and advanced processing capabilities, particularly their ability to handle specialized AI calculations.
The guide provides comprehensive instructions for assembly, cooling considerations, and software configuration. Subramani notes that while cloud computing services offer cheaper alternatives, building a personal system allows for extensive experimentation and deeper understanding of AI model training.
The setup requires careful power management, with each graphics card consuming about 450 watts during intensive training sessions. The system runs on Linux and uses custom software to enable communication between the graphics cards for improved performance.
Despite the high initial cost, Subramani argues that the investment enables hands-on learning and experimentation with AI technology that would be difficult to achieve through cloud services alone.