Author Archives: dselz

Large Language Models (LLMs) have taken the world of artificial intelligence by storm, showcasing impressive capabilities in text comprehension and generation. However, as with any technology, it’s essential to understand its strengths and limitations. When it comes to search functionality, … Continue reading →

In the ever-evolving landscape of artificial intelligence, the emergence of Retrieval Augmented LLMs (raLLM) has marked a significant turning point. This innovative approach, which combines an information retrieval stack with large language models (LLM), has rapidly become the dominant design … Continue reading →

The other day we were asked to take part in a accelerator program. As always some form to be filled out. I was short on time. In fact it was aleady past the official deadline. But the organizer wanted us … Continue reading →

We released GPT for the Enterprise – https://squirro.com/enterprise-generative-ai-and-large-language-models/… Obviously we’re trying it on our own stuff, e.g. our ISO Rulebook. And as obvious we try to see if we can break it. Here’s a test. We failed… You can try … Continue reading →

“Since AI has been around for many years already, I expect a comparable diffusion in one or two years.” We spoke about this in the EM Interview in February 2022. https://link.springer.com/article/10.1007/s12525-021-00516-w

Adopting large language models (LLMs) is not without its challenges, especially for enterprises.. To overcome these challenges and achieve maximum benefit from these models, the combination of composite AI with large language models is the best way forward for enterprises.  … Continue reading →

Adopting large language models (LLM) such as ChatGPT  in an enterprise is not without its challenges. In this post, we’ll discuss some of the key challenges that enterprises face when it comes to adopting large language models and how they … Continue reading →

ChatGPT is one of the most advanced language models in the world. While it is often referred to as a “AI language model,” it is important to note that it is not truly autonomous or intelligent in the same way … Continue reading →

Robert Solow, an economist, said in 1987 that computers show up everywhere except for the productivity statistics. It took a good two decades at the time for this to fundamentally change. I predict the same “Solow Paradox” will apply to … Continue reading →

In the finance industry a fat finger event describes a typo with consequences. A few years ago, a Deutsche Bank trader mistakenly transferred 6 billion. Prediction: This is exactly what will happen with GPT as well. Actually, it will happen … Continue reading →