Author: Paulo Maia

Ditch the Crystal Ball: Reverse-Engineering with Machine Learning

  Machine Learning models are estimators – which means they can be used not only to predict unknowns in your business but also to reverse-engineer complex business processes. As part of this blog post, you will learn how to identify these potential points of improvement, prioritize them, and create models to estimate them. Identification How […]

Written by on Dec 27, 2023

Customizing Language Models: Fine-Tuning vs. Prompt Engineering

In the rapidly evolving landscape of artificial intelligence, there’s a notable surge in interest and activity surrounding generative AI. The question arises: Why this rush? What’s the driving force? The answer lies in the transformative power of customizing Large Language Models (LLMs). Businesses are increasingly captivated by the potential these models hold, specifically when tailored […]

Written by on Nov 6, 2023

Classifying text using LLMs

  Text classification is one of the most common use cases in Natural Language Processing, with numerous practical applications – now easier to access with Large Language Models. Companies use text classification in multiple scenarios to become more efficient: Tagging large volumes of data: reducing manual labor with better filtering, automatically organizing large volumes of […]

Written by on Aug 29, 2023

Spatial Explanations: Unlocking Insights with Occlusions

Spatial Explanations with Occlusions: In computer vision, businesses must grasp the workings of image models to fully leverage visual data. Our simple method called spatial explanations with occlusions, helps achieve a deeper understanding. By employing spatial occlusions across images, this technique unveils critical areas that significantly influence the model’s predictions.” What to do with these […]

Written by on Aug 2, 2023

The Impact of Large Language Models

Large Language Models (LLMs) are THE hot topic of the year. If the name Large Language Models sounds unfamiliar to you, I’m pretty sure you’ve heard of ChatGPT, OpenAI, and Bard. People who don’t know how to code have gained access to a tool that allows them to build Proof of Concepts for ideas they’ve […]

Written by on May 25, 2023

In medio stat virtus? Not always!

The Problem What do you do when the model is underperforming? When the models’ performance does not meet our expectations, we usually spend time searching for the flaws, selecting and analyzing the cases where it failed to understand why it happened. Then, we try to apply more robust solutions, train, test, and repeat. In some […]

Written by on Apr 10, 2023

Our vision of AI in Financial Services

In recent years, the financial services industry has been innovating technologically, supported by a complex ecosystem including banks, financial service providers, and start-ups (link). Within this blogpost, we showcase our vision of AI in Financial Services. AI in Financial Services From our point of view, we can group use cases in AI in three distinct […]

Written by on Dec 12, 2022

Stop removing outliers just because!

Outliers are data points that stand out for being different from the remaining data distribution. An outlier can be: An odd value in a feature A data point distant from the centroid of the data A data point in a region of low density, but between areas of high density. Suppose you have been working […]

Written by on Nov 14, 2022

Achieving diverse product recommendations

In this blog post, you’ll learn about some examples of decision processes you can use in recommender systems: do you see any usage for recommending less popular products as a way to improve your business? You will see it now! The Use Case Let’s imagine a use case where you are building a MOOC platform […]

Written by on May 25, 2022

Teaching Models With Free Data

“The more I see, the less I know” might be a saying, but it does not apply to AI models. It’s well known that the performance of an artificial neural network is highly dependent on the volume and on the diversity of the data that was shown to the model. This happens because exposing the […]

Written by on Feb 23, 2022