By: Azin Asgarian Generative AI models such as GPT-4, Bard and LLaMA have become increasingly popular due to their remarkable capabilities in various tasks, including text generation, summarization and categorization. …

By: Benjamin Ye This is our third and final blog post on anomaly detection in time series. If you’ve been following along with us: thank you for your patience! 🎉 If this is the first time you’ve stumbled across this series, fear not! …

By: Benjamin Ye and Angeline Yasodhara This is the second post of our series on time series outlier detection. You can read the first post here. In our last blog, we have introduced the main families of scoring algorithms and how Georgian together with cybersecurity companies used these techniques to…

By: Benjamin Ye Introduction There has been a murder on the Orient Express! Among the passengers, detective Hercule Poirot must find the mastermind behind it all! In many detective stories, time plays a crucial role in finding the eventual suspect. It’s not enough to base a conjecture on point-in-time information, as…

By: Kyryl Truskovskyi At Georgian, our R&D department often works with our portfolio companies — who we refer to as our customers — to help them multiply ROI. One important way we add value to their products is through machine learning. On the R&D team, my main task is to…

By: Elliot Henry, Azin Asgarian & Rohit Saha Pretrained language models (PLMs) like BERT and BLOOM have become ubiquitous; from summarizing long legal contracts to making suggestions on improving sales emails. Despite this progress, there are still many questions and challenges when it comes to productizing these models. What are…

By: Angeline Yasodhara From BERT to CNN, the need to automatically encode raw data into usable representations (aka representation learning) has been groundbreaking and integral to all machine learning applications. This past month, over a thousand papers were presented at the 10th International Conference on Learning Representations (ICLR). ICLR is…

By: Jason Brenier Welcome back to Agile AI at Georgian, where I share lessons learned about how to adapt agile methodologies for AI products. In previous installments, we’ve talked about finding your project’s North Star, motivating your team, mastering experimental design, and managing the data lifecycle. Today, we’re going to…

By: Jason Brenier Welcome back to Agile AI at Georgian, where I share lessons learned about how to adapt agile methodologies for AI products. In previous installments, we’ve talked about finding your project’s North Star, motivating your team and mastering experimental design. …