Julia Turc
AI researcher and content creator specializing in efficient machine learning techniques, particularly around model compression and training optimization.
- Video: How does 4bit quantisation work (2026-04-14) - Discusses evolution of training large-language-models with reduced precision, focusing on 4-bit floating-point (FP4) training challenges. Highlights cost of training LLMs (Gemini Ultra: ~78M in 2023) and shift toward Quantisation techniques to reduce computational demands.
- Key insight: Reducing precision from 16-bit to 4-bit significantly lowers training costs while maintaining model performance through advanced Quantisation methods.
2026 04 14 How does 4bit quantisation work
Source Notes
- 2026-04-23: https://www.youtube.com/watch?v=-cRedoYETzQ Julia Turc The video discusses the evolution and challenges of training large language models (LLMs) with reduced precision, particularly focusing on the shift towards 4-bit floating-point (FP4) training. Cost of Training LLMs: Tr (How does 4bit quantisation work)
- 2026-04-14: # How does 4bit quantisation work --- --- https://www.youtube.com/watch?v=-cRedoYETzQ Julia Turc The video discusses the evolution and challenges of training large language models (LLMs) w (How does 4bit quantisation work)