System status
Yet, the transition raises serious concerns. Issues like data security, sustainable AI practices, and equitable access to AI technology loom large. Additionally, the promise of AI brings a host of challenges that, if not properly anticipated and addressed, could hinder its seamless and ethical integration.
Three major challenges
AI relies heavily on data processing and needs high-performance computing (HPC) systems to work. It’s a resource-intensive technology with a large footprint in terms of energy use and carbon emissions. The massive data centres required to run AI models consume vast amounts of electricity and generate a lot of heat, bringing the sustainability of AI under scrutiny and driving efforts to make AI more environmentally friendly.
Data security in the age of AI is another burning issue. Transferring and processing data outside secure sites makes the data vulnerable to risks, increasing the need for constant vigilance and hefty investments in robust security measures to maintain data integrity throughout the data lifecycle.
What’s more, the high costs and limited access to AI technology—particularly cutting-edge AI technology—also pose significant hurdles. The cost of acquiring and maintaining sophisticated infrastructure, combined with a tight supply of processors capable of handling advanced AI tasks, is yet another barrier that prevents equitable access to AI technology.
To tackle those challenges, educational institutions and AI stakeholders must join forces as members of the Réseau d’Informations Scientifiques du Québec (RISQ) network. By working closely together under one umbrella, they can develop strategies to unlock the power of AI in education and make sure the technology is used responsibly, while contributing to data protection and making AI both affordable and environmentally sustainable.
A smart way to ensure needs are better met
Having a dedicated hub for all things AI would help educational institutions:
- Easily access artificial intelligence, facilitating and expanding its use across their campuses.
- Address shadow IT to limit the use of unapproved IT solutions through centralized management.
- Share knowledge through communities of practice to encourage the exchange of ideas and experience, while fostering innovation, advancements in AI and collaborative research.
- Take a unified approach to prevent silos, consolidating efforts to avoid project fragmentation and develop a cohesive implementation strategy.
- Cut AI costs and achieve significant savings while harnessing artificial intelligence through effective resource use and management.
A state-of-the-art, secure and accessible eco-friendly solution
At Micrologic, we’re determined to make real-time, high-performance computing clusters accessible via RISQ. We believe this innovative solution is the way forward.
But we won’t stop there. Since you will be accessing AI systems via our Cirrus sovereign cloud, your data will stay in Canada and will be governed by Canadian laws. Plus, your data will be hosted in a data centre at the forefront of technology through strategic partnerships with NVIDIA and QScale. What’s more, with Cirrus there are no egress fees and you won’t get locked in like you would with a hyperscaler cloud.
Our approach combines environmental responsibility with the benefits of our Cirrus sovereign cloud to successfully meet the AI processing needs of educational institutions across the province.
Together, we can make AI happen in Quebec!
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This is an excerpt from a talk given by Micrologic’s Stéphane Garneau at the RISQ conference held in Montreal on February 21, 2024.
