Kees van Berkel

Technical University Eindhoven, The Netherlands

Scaling Mount AI, a literature study

Abstract

In 1998 Hans Moravec asked the question When will computer hardware match the human brain?

His colorful predictions are often cited and represent the first AI scaling laws.

• How did Moravec’s predictions pan out?
• How do various AI metrics scale with the applied compute resources?
• What are the limits to AI scaling? Can AI scaling continue through 2030?
• Will AI scaling enable Artificial General Intelligence (AGI)?

Biography

Kees van Berkel received an MSc degree in EE from TU Delft and a PhD degree in CS from TU Eindhoven. He worked for over 40 years in the semiconductor industry (Philips Research, NXP, ST-Ericsson, Ericsson, and GrAI Matter Labs), and for 26 years as part-time full professor at the TU/e. He pioneered asynchronous VLSI from theory to mass production, and likewise for vector processors for software-defined radio.

Today he is a consultant on neural computing for Snap Labs and an emeritus professor at the TU/e. His current research interest is models of (parallel) computation: dataflow, cellular automata, neural computing, and quantum computing. His favorite application domain is radio astronomy.