November 2022

Stable Diffusion has been a buzzword in the last months after it was publicly unveiled by its developer Stability AI on August 22, 2022. Not only Stable Diffusion generates complex artistic images based on text prompts, but it’s also an open source image synthesis AI model available to everyone. Its free accessibility makes it very different from its predecessors. In this post, we explain how it works, what prospects it opens, and share tips on how you can […]

Ver mais

The DataKinds language extension doesn’t work the way you think it does… probably. Of course I can’t possibly know what mental model you have for DataKinds. Perhaps you are one of the few who understand its true nature. But I’ve seen experts – yes, type-level Haskell wizards – fall into the trap that I’m about to expose. How DataKinds are commonly explained To set the stage, let’s take a look at how DataKinds are commonly explained. Matt Parsons […]

Ver mais

Models that allow interaction via natural language have become ubiquitious. Research models such as BERT and T5 have become much more accessible while the latest generation of language and multi-modal models are demonstrating increasingly powerful capabilities. At the same time, a wave of NLP startups has started to put this technology to practical use. While such language technology may be hugely impactful, recent models have mostly focused on English and a handful of other languages with large amounts […]

Ver mais

Training machine learning models requires a lot of data, which is not always available. This is where transfer learning comes into play as it leverages previously trained models. In this blog post, we’ll explore the definition, methodology, benefits, and applications of transfer learning. We’ll also discuss various transfer learning strategies and provide a selection of pre-trained models. What is transfer learning? Transfer learning is an ML method that uses a pre-trained model as the basis for training a […]

Ver mais