Different methods from the field of NLP helped us to create a software that spots errors in legal contracts
By Emilius Richter • July 18th, 2022
For a software provider, the project proposal is the first step toward meeting the needs of the customer. In this article, I will describe the most important modules in machine learning project proposals.
By Marty Oelschläger (PhD) • December 20th, 2021
I explain why language models tend to reproduce stereotypes and prejudices with potentially harmful consequences - and how to use them with care.
By Fabian Gringel • October 24th, 2021
Here I explain in which situations GPT-3 fails and why it is far from having proper natural language understanding, which approaches can help to mitigate these issues and might lead to the next breakthrough and what alternatives to GPT-3 there are already.
By Fabian Gringel • September 27th, 2021
In this blog article I will explain how GPT-3 works, why some people think it’s dangerous, and how you can try out a GPT-3-like model yourself for free.
By Emilius Richter • May 21st, 2021
We discuss what questions should be considered and answered up front to launch a successful machine learning software project.
By Angela Maennel • April 26th, 2021
Here I show how open-domain question answering systems work and how they can enhance search engines. We will have closer look at one specific type of system, DrQA.
By How to extract text from PDF files • August 17th, 2020
In the following I want to present the open-source Python PDF tools PyPDF2, pdfminer and PyMuPDF that can be used to extract text from PDF files. I will compare their features and point out some drawbacks.
By Fabian Gringel • March 30th, 2020
In this blog post I present the three best free text annotation tools for the manual labeling of documents in NLP projects. You will learn how to install, configure and use them and find out which one of them suits your purposes best. The tools I'm going to present are brat, doccano and INCEpTION.