
Large language models, explained with a minimum of math and jargon
Date : 2023-07-27
Introduction
No one on Earth fully understands the inner workings of LLMs. Researchers are working to gain a better understanding, but this is a slow process that will take years—perhaps decades—to complete.
Still, there’s a lot that experts do understand about how these systems work. The goal of this article is to make a lot of this knowledge accessible to a broad audience. Timothy B Lee and Sean Trott aim to explain what’s known about the inner workings of these models without resorting to technical jargon or advanced math.
Read blog post here
Recently on :
Artificial Intelligence

WEB - 2024-12-30
Fine-tune ModernBERT for text classification using synthetic data
David Berenstein explains how to finetune a ModernBERT model for text classification on a synthetic dataset generated from argi...

WEB - 2024-12-25
Fine-tune classifier with ModernBERT in 2025
In this blog post Philipp Schmid explains how to fine-tune ModernBERT, a refreshed version of BERT models, with 8192 token cont...

WEB - 2024-12-18
MordernBERT, finally a replacement for BERT
6 years after the release of BERT, answer.ai introduce ModernBERT, bringing modern model optimizations to encoder-only models a...

PITTI - 2024-09-19
A bubble in AI?
Bubble or true technological revolution? While the path forward isn't without obstacles, the value being created by AI extends ...

PITTI - 2024-09-08
Artificial Intelligence : what everyone can agree on
Artificial Intelligence is a divisive subject that sparks numerous debates about both its potential and its limitations. Howeve...