adesso Blog

When searching for relevant sources for editorial work, specialised knowledge databases are indispensable. But even in this rich pool, the search is often laborious. The solution? Concise summaries of each entry that enable a quick assessment of relevance. In our blog post, we present proven concepts for the mass generation of machine-generated summaries with Aleph Alpha Luminous and report on a realised customer project.

The ‘Intelligent knowledge database – support during Aleph Alpha integration’ project focuses on the use of Aleph Alpha’s large language models to make the day-to-day work involved in maintaining text documents and editorial processes more intelligent and efficient. adesso implements the work processes for data analysis and clustering in the database as a pro bono service. In my blog post, I will provide a detailed look inside the workshop that accompanies the AI project as well as key aspects of it.

This is the third and final instalment of my blog series titled ‘Machine-generated text summarisation in Aleph Alpha Luminous using R’. Here, I will use a high-level example to explain the various steps in a transformation pipeline and present the intermediate results.

Running large language models using a fancy, ready-to-use interface increases accessibility for many, even for people who do not know any programming languages. Part two of my blog series focuses on technical aspects such as specifying the scope of the summary, prompt engineering and quality factors.

Running large language models using a fancy, ready-to-use interface increases accessibility for many, even for people who do not know any programming languages. Part two of my blog series focuses on technical aspects such as specifying the scope of the summary, prompt engineering and quality factors.

Running large language models using a fancy, ready-to-use interface increases accessibility for many, even for people who do not know any programming languages. In my blog post, I will focus on the backend component in R and explain how R is used to manage interface integration into Aleph Alpha.

In this blog post, I want to give an introduction to the AI models of the German company Aleph Alpha given the current attention that large language models such as OpenAI’s ChatGPT are attracting and how people are increasingly using it to solve natural language processing problems. I will explain why it is of great importance to have AI companies based in Europe and why the everyday use of ChatGPT can be problematic given that it is the product of a US company.

In this blog post, I will show how you can harness the power of Aleph Alpha’s ‘Luminous’ series of large language models for automated document processing. I will present detailed use cases and explain how Luminous efficiently, accurately and cost-effectively enables the extraction of information from documents.