A crucial reason that it is possible to train ML systems to outperform human experts in narrow domains such as protein folding or chess, is because for these well-defined problems, it is easy to produce a reliable reward signal. However, current techniques for aligning frontier models with human goals, such as human feedback, are only […]

AltaML builds artificial intelligence (AI)-enabled solutions to business problems. We work with organisations, bringing together their data and domain expertise with our AI expertise, to develop AI solutions that are deployed in their operations. We also commercialize AI-enabled products business via industry-specific ventures, yielding scalability from our investment in the first solution. Competition for tech […]

In this project, the candidate will gather new & utilize existing data in conjunction with machine learning algorithms to optimize various aspects of how one (or more) social games operates. Experiments will be proposed and run in order to gather operational data. This data will be used in conjunction with existing player & game data […]

Cells cultured on planar surfaces adopt a variety of morphological shapes. Despite their seeming randomness, such morphology is determined by a biophysical process that represents the sum of multiple cellular processes. Cell morphology is dynamic, and cells change their shape with time and across different time scales, e.g. with local modification of the environment, or […]

The company collects survey data from websites which is combined with behavioural data from survey respondents. This combined data set is information rich but can be too sparse for modelling purposes in a straight forward supervised learning context. As such, on-going research concerns optimizing the process by which non-survey related behavioural data can be leveraged […]

CEIMIA is an international non-profit organization that mobilizes expertise and resources to promote the development and responsible use of artificial intelligence for the benefit of humanity. One of CEIMIA’s role is to establish supportive connections between key players in the national and international AI ecosystems, while promoting diversity and inclusion in all their projects.

The project involves the development of a machine learning model which can predict targeted properties of materials from their band structure. Computational modeling methods, such as ab initio (quantum chemistry) calculations, Density Functional Theory and Molecular Dynamics, enable us to calculate properties of materials from their crystalline structure. The band structure is a representation of […]

This project is to continue to implement data analysis algorithms for real time analysis of precision feeding data provided by a novel custom poultry precision feeding system. In addition if time allows work on some computer vision algorithms to detect the presence of a bird in a feeding station.

MedMe Health is pursuing further growth within Canada, especially in Quebec, and prepares for expansion into new markets such as the United States and the United Kingdom. The company’s customer onboarding process is currently cumbersome and manual, which affects scalability and limits customers’ control over account management. They also face the hurdle of language localization […]

This project aims to benefit society by improving accessibility for viewers who may not be able to receive sound information well from the media content, including DHH viewers. To develop and research for the project, it is necessary to reflect an in-depth and multi-faceted case analysis on the topic of improving sound accessibility. To fulfil […]

AltaML builds artificial intelligence (AI)-enabled solutions to business problems. We work with organisations, bringing together their data and domain expertise with our AI expertise, to develop AI solutions that are deployed in their operations. We also commercialize AI-enabled products business via industry-specific ventures, yielding scalability from our investment in the first solution. Competition for tech […]

The objective of this project is to develop artificial intelligence (AI)-based solutions aimed at denoising ventilation-perfusion (V/Q) planar images for the detection of pulmonary embolism (PE). The denoising algorithm has the potential to solve two major limitations of V/Q scans: long acquisition times and currently insufficient techniques for generating pseudo-planar images from SPECT acquisitions. Our […]