Scaling

Scaling refers to techniques and methods for efficiently managing the increase in computational requirements as machine learning models grow larger. This can involve everything from parallelization strategies on modern hardware like GPUs and TPUs to innovative approaches that leverage older or less powerful systems.

Related Concepts

• hardware
• parallel-processing
• retro-computing
• transformer-models

Notable Examples & Case Studies

• Running a transformer model on a 1979 44 computer, as explored in the video “EXPOSED: The Dirty Little Secret of AI (On a 1979 PDP-11)” by Dave’s Garage.
  • A single 6MHz CPU and initially 64KB RAM, later upgraded to 4MB.
  • Demonstrates that modern advancements are not inherently magical but rather the result of iterative improvements in technology and algorithms.

Backlinks

2026 04 13 Demystifying AI Transformer Training on a 1979 PDP 11