Large Language Models (LLMs) perform outstandingly in various downstream tasks, and the use of the Retrieval-Augmented Generation (RAG) architecture has been shown to improve performance for legal question answering (Nuruzzaman and Hussain, 2020; Louis et al., 2024). However, there are limited applications in insurance questions-answering, a specific type of legal document. This paper introduces two corpora: the Quebec Automobile Insurance Expertise Reference Corpus and a set of 82 Expert Answers to Layperson Automobile Insurance Questions. Our study leverages both corpora to automatically and manually assess a GPT4-o, a state-of-the-art LLM, to answer Quebec automobile insurance questions. Our results demonstrate that, on average, using our expertise reference corpus generates better responses on both automatic and manual evaluation metrics. However, they also highlight that LLM QA is unreliable enough for mass utilization in critical areas. Indeed, our results show that between 5% to 13% of answered questions include a false statement that could lead to customer misunderstanding.

This work presents an investigation and assessment framework, which, supported by realistic data, aims at provisioning operators with in-depth insights into the consumer-perceived Quality-of-Experience (QoE) at public Electric Vehicle (EV) charging infrastructures. Motivated by the unprecedented EV market growth, it is suspected that the existing charging infrastructure will soon be no longer capable of sustaining the rapidly growing charging demands; let alone that the currently adopted ad hoc infrastructure expansion strategies seem to be far from contributing any quality service sustainability solutions that tangibly reduce (ultimately mitigate) the severity of this problem. Without suitable QoE metrics, operators, today, face remarkable difficulty in assessing the performance of EV Charging Stations (EVCSs) in this regard. This paper aims at filling this gap through the formulation of novel and original critical QoE performance metrics that provide operators with visibility into the per-EVCS operational dynamics and allow for the optimization of these stations' respective utilization. Such metrics shall then be used as inputs to a Machine Learning model finely tailored and trained using recent real-world data sets for the purpose of forecasting future long-term EVCS loads. This will, in turn, allow for making informed optimal EV charging infrastructure expansions that will be capable of reliably coping with the rising EV charging demands and maintaining acceptable QoE levels. The model's accuracy has been tested and extensive simulations are conducted to evaluate the achieved performance in terms of the above listed metrics and show the suitability of the recommended infrastructure expansions.

As a member of our thriving team, you have the opportunity to work alongside clinical research colleagues who understand the patients' mindset and their disease experiences. We help translate science into success for trials with a strategic and targeted, patient-centric approach. We are specialists who find solutions for novel trial challenges in our detailed approach throughout every study phase. From the beginning, we have nurtured an employee-centric company culture that focuses on patients' needs. Precision's team-focused culture ensures that team members will thrive and learn.

The ability to scale out training workloads has been one of the key performance enablers of deep learning. The main scaling approach is data-parallel GPU-based training, which has been boosted by hardware and software support for highly efficient point-to-point communication, and in particular via hardware bandwidth overprovisioning. Overprovisioning comes at a cost: there is an order of magnitude price difference between "cloud-grade" servers with such support, relative to their popular "consumer-grade" counterparts, although single server-grade and consumer-grade GPUs can have similar computational envelopes. In this paper, we show that the costly hardware overprovisioning approach can be supplanted via algorithmic and system design, and propose a framework called CGX, which provides efficient software support for compressed communication in ML applications, for both multi-GPU single-node training, as well as larger-scale multi-node training. CGX is based on two technical advances: \emph{At the system level}, it relies on a re-developed communication stack for ML frameworks, which provides flexible, highly-efficient support for compressed communication. \emph{At the application level}, it provides \emph{seamless, parameter-free} integration with popular frameworks, so that end-users do not have to modify training recipes, nor significant training code. This is complemented by a \emph{layer-wise adaptive compression} technique which dynamically balances compression gains with accuracy preservation. CGX integrates with popular ML frameworks, providing up to 3X speedups for multi-GPU nodes based on commodity hardware, and order-of-magnitude improvements in the multi-node setting, with negligible impact on accuracy.

At ServiceNow, our technology makes the world work for everyone, and our people make it possible. We move fast because the world can't wait, and we innovate in ways no one else can for our customers and communities. By joining ServiceNow, you are part of an ambitious team of change makers who have a restless curiosity and a drive for ingenuity. We know that your best work happens when you live your best life and share your unique talents, so we do everything we can to make that possible. We dream big together, supporting each other to make our individual and collective dreams come true.

Montreal-based centre unites strengths of McGill University, ÉTS, Mila, CNRS, Université Paris-Saclay, and CentraleSupélec A consortium of research organizations has gathered together to form a new International Research Laboratory (IRL) focused on artificial intelligence (AI) in Montreal. The new centre gathers together McGill University, École de technologie supérieure (ÉTS), Mila – Quebec AI Institute, France’s Centre Nationale de la Recherche Scientifique (CNRS), Université Paris-Saclay, and the École CentraleSupélec. The move confirms Montreal’s status as a leader in AI. While great strides have been made in AI recently, there is still a pressing need for new theoretical knowledge to better understand not only the capacities of this new technology, but how it achieves its results. The ILLS will focus on five main themes of research: fundamental aspects of artificial intelligence, sequential (real-time) machine learning, robust autonomous systems, natural language and speech processing, and applications to computer vision, signals, and information processing. In addition, the new centre will emphasize interdisciplinary collaborations with an aim to develop new methodologies and integrate these techniques into learning systems. “This new laboratory confirms Montreal’s global leadership in AI,” said Benoit Boulet, Associate Vice-Principal, Research & Innovation at McGill University. “This is a major hub with a talent pool that continues to deepen, and McGill researchers and students are embedded at every level of this activity. This new initiative will offer opportunities for our researchers to make even more breakthrough discoveries.” “The expertise of ÉTS in AI includes several laboratories and research chairs in artificial intelligence. This collaboration between France and Quebec makes it possible to innovate and deepen research in AI, a cross-cutting discipline from which we can benefit in many fields, including health, the built environment, robotics, and the Internet of Things. It is therefore with pride that ÉTS welcomes the new ILLS centre within its establishment,” said Christian Casanova, Director of Research and Partnerships at ÉTS. “Through its tools of international cooperation, CNRS supports the most promising cutting-edge joint research projects. The new international research laboratory brings together a powerful network of researchers from France and Québec to advance the knowledge and applications of AI. For the CNRS, this new lab is also an opportunity to strengthen more broadly its ties with the whole Canadian AI community,” said Antoine Petit, Chairman and CEO of CNRS. “AI at Paris-Saclay involves nearly 1,000 researchers, teacher-researchers, engineers and technicians and around forty laboratories, grouped together within our DataIA Institute. We will make our contribution to the ILLS in the form of the mobility of researchers, including the reception of Canadian colleagues at Paris-Saclay, the reception of Masters trainees, thesis funding in particular/among others. The University of Paris-Saclay is honored and proud to be associated with this signing ceremony for the creation of the IRL ILLS and to ensure its joint supervision" added Michel Guidal, Deputy Vice-President Research Sciences and Engineering at Université Paris-Saclay. “The ILLS, resulting from an unprecedented and international union, offers a unique potential for progress in the field of AI. It is an honor for CentraleSupélec to participate with our prestigious partners in this laboratory. Backed by this research, our teaching will thus be at the forefront of the world in terms of AI,” added Romain Soubeyran, Director of CentraleSupélec. The ILLS will join a burgeoning artificial intelligence (AI) sector in Montreal, which has attracted other major investments from government and business for the past several years. As a result, the city is one of the world’s leading hubs in this domain, with an estimated 27,000 workers in AI-related technologies and over 14,000 post-secondary students enrolled in AI-related study programs. The ILLS is the latest such laboratory to be launched in Canada, specifically in Quebec. In 2014, the CNRS and the Fonds de recherche du Québec – Nature et technologie (FRQNT) signed a letter of intent to support and promote the tradition of scientific cooperation that exists between France and Quebec. This collaboration has resulted in two International Research Laboratories in Quebec, as well as other shared research activities across the province. The CNRS has also established three other IRLs in Canada in partnership with other institutions. Present at the signing ceremony were: Frédéric Sanchez (Consul General of France), Remi Quirion (Quebec’s Chief Scientist), Antoine Petit (CNRS), Suzanne Fortier (McGill University), Francois Gagnon (ETS), Michel Guidal (Université Paris-Saclay), Franck Richecoeur (École CentraleSupélec), and Laurence Beaulieu (Mila). About McGill University Founded in Montreal, Quebec, in 1821, McGill University is Canada’s top ranked medical doctoral university. McGill is consistently ranked as one of the top universities, both nationally and internationally. It is a world-renowned institution of higher learning with research activities spanning three campuses, 11 faculties, 13 professional schools, 300 programs of study and over 39,000 students, including more than 10,400 graduate students. McGill attracts students from over 150 countries around the world, its 12,000 international students making up 30% of the student body. Over half of McGill students claim a first language other than English, including approximately 20% of our students who say French is their mother tongue.

Who are the key actors of artificial intelligence (AI) in Quebec? What are the links between the different organizations that constitute the AI research infrastructure? How have academia, politics and economics intermingled in the development of this infrastructure? Based on what promises did the Quebec and Canadian governments invest hundreds of millions of public funds in this infrastructure? This research note attempts to answer these questions.

French videogame giant Ubisoft's Montreal office is seen on July 18, 2020 in Quebec, Canada. French videogame giant Ubisoft's Montreal office is seen on July 18, 2020 in Quebec, Canada. Genshin Impact is an award-winning role-playing game created by Chinese video game developer miHoYo. A year after its September 2020 release, the game managed to amass a total revenue of more than $2 billion. That kind of revenue makes Genshin Impact one of the most profitable video game releases ever and easily miHoYo's most successful project in the company's nine-year history. After seeing such success, it was only natural for the company to expand.

Dr. Peter Metrakos is the Greek leader of a research team working on improving survival rates of cancer patients by using breakthrough artificial intelligence (AI) technology. The team of doctors, based in Canada, are working to help patients suffering from colorectal cancer survive an incredibly deadly disease, which as it stands has a five-year survival rate of only 12%. The research team is working with the Research Institute of the McGill University Health Centre (RI-MUHC) to develop personalized medicine in the colorectal cancer field. Current research is based on Metrakos' 2016 research into colorectal cancer cells' relationship to blood vessels. The Greek doctor and his team will use liquid biopsy techniques to separate constituent parts of the cancer patient's blood, in order to understand which are related to the cancer.

Enterprise cloud-based solutions provider ServiceNow today launched its Now Platform Quebec release, which the company says is designed to help enterprises innovate more quickly in a world changed by the pandemic. Quebec brings several new AI and machine learning-powered and low-code capabilities, including a predictive AIOps feature that anticipates issues and automates resolution and a virtual agent that provides guided setup and topic recommendations. "In today's challenging environment, organizations worldwide are pivoting fast, adopting new, distributed models of working and creating new workflow‑enabled ways of operating with more agile, resilient, digital enterprise value chains," Chirantan Desai, chief product officer at ServiceNow, said in a blog post. "Customers are relying on ServiceNow's Now Platform to deliver enterprise digital workflows, create new business models, enhance productivity and enable great customer and employee experiences in any operating environment. This newest version of the Now Platform further enhances the must‑have enterprise digital tools customers need today."