Overall message
The video explains what “multimodal AI” means today, how the underlying architectures have evolved from simple “bolt-on” systems to truly unified models, and what new capabilities this enables.
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I appreciate blog post “Making sense of MVP” by Henrik Kniberg as it addresses a few important points when it comes to shipping customer solutions. In my professional carrer I have encountered already a few times issues along these points:
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Conceptually, RAG is simple: You’ve got your LLM but it lacks private information, corporate data or has a data cut-off which is too far in the past. Therefore, you make more data available, usually usig a vector store.
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Up until today OAuth2 was always very opaque to me. Sure, I was using short-lived token to e.g. make API requests but I never tried to understand the mechanism itself. And actually it’s not that complicated from a conceptual point of view.
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When transforming data, I have often been using a pattern like the following. I’ve created a class that is responsible for different data transformation steps. Generally speaking, structuring data transformations using classes makes sense as classes are a neat way to group related functions together. For another developer who has...
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When systems exchange data there are some obvious choices like csv, JSON or XML. The advantage of these are the human readability and wide adoption amongst different languages and frameworks.
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When writing data with Spark, it’s easy to get confused as there are different ways to do so. The different ways do different things under the hood and depending on what you want it might be good or bad. This illustration helps to understand better what is going on when...
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Today I learned about a new python module called HiPlot. It uses a simple yet powerful visualization technique to uncover patterns and relationships in a data set. Uses cases are for example to identify the relevant features for a ML algorithm, to obtain decision rules for classification or to analyze...
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