To Grok Grokking: Why Neural Networks Sometimes Understand Late

Tue, 27 Jan 2026 00:00:00 +0000

In machine learning, we expect a model to either learn or overfit. What we don’t expect is for a model to overfit first and then — much later, with no changes — suddenly start generalizing well. This phenomenon is called grokking, and it has puzzled researchers since its discovery. A new paper finally explains why it happens and proves it mathematically — in the simplest possible setting.

What is Grokking?

Grokking was first observed in 2022 on small algorithmic tasks (like modular arithmetic). The pattern is striking:

Cost-Constrained LLM Cascades — Meet C3PO

Fri, 14 Nov 2025 00:00:00 +0000

Imagine you have an army of helpers — several different Large Language Models (LLMs), each capable of handling tasks from simple queries to complex reasoning.
But each helper costs something: time, compute, or actual money if you’re using an API.

So the question is:
Can we orchestrate these models wisely — starting from the cheapest one that might do the job, escalating only when needed — without exceeding a cost budget?

Scientific Research on MLLog.dev

To Grok Grokking: Why Neural Networks Sometimes Understand Late

What is Grokking?

Cost-Constrained LLM Cascades — Meet C3PO