Large language models (LLMs) have advanced rapidly in recent years. As new generations of models are developed, researchers and engineers need to stay informed on the latest progress. This article…
Considering the rapid advancements in the field of LLM “chains”, “agents”, chatbots and other use cases of text-generative AI, evaluating the performance of language models is crucial for…
What neighborhood do you live in? What drug were you prescribed? Why did you cancel your streaming subscription? These days, there’s a code for that, stored in databases by whatever governments…
While many of us spend most of our data education and careers working with data in relatively “friendly” formats, such as spreadsheets and CSV files, there may come a time when you’re confronted with…
Sometimes you work on projects that you have to share with the world (or your company). These projects make an impact, and by sharing them you can get more support or show the value you bring. It can…
The process of augmenting data usually involves a scenario where you have some data but not enough data. When you have some data you can apply a range of techniques that sample, re-sample, modify…
This article is about optimizing the communication between your Python app and a database so that your app runs smoothly and your database server doesn’t melt. This article addresses a common…
Within this article, I share some of the basics to create a LLM-driven web-application, using various technologies, such as: Python, FastAPI, Pydantic, VertexAI and more. Disclaimer: I am using data…
Running large language models (LLMs) on consumer hardware can be challenging. If the LLM doesn’t fit on the GPU memory, quantization is usually applied to reduce its size. However, even after…
Choosing the font when we are working on a digital document is trivial. We can always choose the preferred font in the drop-down font list in the editor. How about changing the font of the text in an…