data science

are large-scale AI models trained on an unlimited and diverse range of information, comparable to audio, text, images, or a mix of them. For this reason versatility, foundation models are revolutionizing Natural Language...

You’ve argued that a well-designed experiment can teach you greater than knowing the counterfactual. In practice, where experimentation remains to be underused, what’s your minimum viable experiment when data is scarce or stakeholders are...

composers are known to reuse motifs (i.e., characteristic note progressions or melodic fragments) across their works. For instance, famous Hollywood composers corresponding to John Williams (, , ) and Hans Zimmer (, ,...

Introduction Ever watched a badly dubbed movie where the lips don’t match the words? Or been on a video call where someone’s mouth moves out of sync with their voice? These sync issues are greater...

language models has made many Natural Processing (NLP) tasks appear effortless. Tools like ChatGPT sometimes generate strikingly good responses, leading even seasoned professionals to wonder if some jobs is likely to be handed...

, I discovered myself wondering why some dashboards immediately grabbed my attention, while others just felt flat. A giant a part of that magic is color. As basic because it sounds, it plays a...

In my last article , I threw out a number of ideas centered around constructing structured graphs, mainly focused on descriptive or unsupervised exploration of information through graph structures. Nevertheless, once we use graph...

. Semantic entity resolution uses language models to bring an increased level of automation to schema alignment, blocking (grouping records into smaller, efficient for all-pairs comparison at quadratic, n² complexity), matching and even ...