Classical engineering, referring to the three fields of civil, mechanical and electrical engineering, is currently based on traditional working methods. For example, the validation of plans is often done in paper version and the engineer must interpret photos and drawings manually, which introduces a risk of error due to the human factor. In addition, the shortage of labor in this area means that the economic potential of this industry in Canada cannot be exploited to its full value.
Financial data are known to be generated from complex distributions, often assumed to be changing over time. The aim of this project is to build a simulator of multivariate time series, parameterized as simply as possible by a user, with the freedom to build different models, to assess their general behavior and key properties. This will facilitate predictions of multiple sequences and their interactions, through a simple interface of possible configurations to the user, who could have a basic knowledge of statistics and limited knowledge of the mathematical details of the underlying models.
La plupart des documents d’ingénierie comportent des symboles pour caractériser les systèmes qu’ils représentent. Ils comportent également des annotations (identifiants, notes, spécifications) sous forme textuelle pour préciser certaines propriétés importantes ou identifier les composants. Si l’association entre les symboles et les composants est intuitive pour un expert humain, il en va autrement pour un ordinateur. Ce projet vise à permettre la découverte automatique de tels liens d’association par un ordinateur, en utilisant des techniques d’apprentissage automatique.
Le projet consiste à développer un système et une application web qui permettra aux aménagistes forestiers urbains de choisir la meilleure espèce d’arbre à planter à différents endroits de la ville afin de maximiser les retombées économiques et sociales et la résilience du couvert arboré face aux changements globaux.
Predictive modeling of financial data, especially trading activity or asset prices, is a very challenging task. There are a number of novel approaches to feature engineering, data preparation and model architectures that aim to mitigate some of the problems that arise from non-stationarity and other issues typically found in financial time series data.
Human perception has developed the ability to decompose scenes into fine grained elements. This lays the foundation for strong generalization to new situations where the base concepts can be recomposed to interpret objects never seen before. While it has been shown that, in the general case, proper decomposition is not possible, new paradigms provide provable decomposition in constrained environments. We hypothesize that the multiple sensory systems of human perception offer a strong signal for decomposing scenes in a proper way.
This research is carried out on the topic of natural language processing and specifically on word representation on Question Answering tasks. The state of the art in Question Answer task is Google’s Bidirectional Encoder Representations from Transformers (BERT) language model.
Koïos Intelligence is interested in fine-tuning this model for their closed domain artificial intelligence (AI) virtual assistant, targeted at insurance and financial applications.
It is well known that retailers have razor-thin margins. A few discount percentage points can make the difference between a bad and an excellent year. The goal of this project is to make sure that Altitude Sports’ prices are optimized to satisfy customers and maximize margins, all year long. There are a lot of factors influencing pricing decisions such as official and unofficial MAP (Minimum Price Policies enforced by brands), stock velocity, season stock levels, stock scarcity, cashflow and price elasticity. Furthermore, price elasticity in itself is highly variable.
Aid in the development of a Machine Learning Model for utilization by an Agricultural Robot. This Robot performs several tasks, primarily the mechanical removal of weeds from vegetable farms. Therefore, the machine learning model is concerned with informing the robot of locations of interest points of the weed and crop plants, as viewed from several sensors mounted on the robot. Other sensors of the robot, such as GPS, and wheel odometry, can be brought to bear as well.
The aviation industry connects people, markets, and cultures around the world and aviation is the key to ensuring that air transport continues to play a major role in driving sustainable economic and social development.