Manulife doesn\u2019t need its tools to ace the LSAT or the MCAT, but it does, Wallis said, want models that deliver the most accurate results at the lowest cost for its in-house applications.<\/p>\n
New models out-performing their predecessors by a few percentage points isn\u2019t that important for large firms adopting AI, said Foteini Agrafioti, senior vice-president of data and AI at RBC. Rather than raw power, the bank needs models that it can use securely and quickly scale across the company.<\/p>\n
RBC plans to use<\/a> Cohere\u2019s technology for most of its generative tools. The bank wants to standardize and centralize its AI platform, the same way it has with software for other functions like cybersecurity or engineering, Agrafioti said. A single system makes it easier to keep data safe and transfer tools between different parts of the business, she added.\u00a0\u00a0<\/p>\n RBC tested technology from other firms, including OpenAI, Agrafioti said, but the bank wasn\u2019t willing to send client data to a system hosted on another company\u2019s cloud. So, RBC bought access to North, a Cohere product that lets users launch AI agents powered by the Toronto firm\u2019s large language models. It will run Cohere\u2019s technology on its own servers; the bank has built what it claims<\/a> is Canada\u2019s largest cluster of the graphics processing units used to power AI.\u00a0<\/p>\n \t\t\t\t\tRelated Articles<\/p>\n \t \t RBC and Cohere are co-developing a version of North that meets the bank\u2019s security and regulatory requirements. RBC employees building new AI applications that touch sensitive data must use North, which is rolling out to developers at the company this summer. In March, Canada\u2019s biggest bank announced<\/a> it\u2019s aiming to generate up to $1 billion in earnings using AI by 2027. \u201cIt\u2019s graduating out of experiments,\u201d Agrafioti said, to become \u201cmainstream.\u201d<\/p>\n Betting on Cohere as RBC\u2019s main generative AI provider comes with risks, Agrafioti said, since other AI firms might advance the technology faster. The bank will monitor those alternatives and give staff access to the latest models, she said. Still, she\u2019s keen to avoid the distraction of flashy new AI models. \u201cWe have something in our hands that does the job we need it to do really well, and we\u2019re going to use that,\u201d she said.<\/p>\n While big businesses may have the data, the technical staff and use cases to test AI models, smaller firms rely on third-party benchmarks such as LLM Arena and MMLU, including some that researchers have accused<\/a> tech firms of trying to game.\u00a0<\/p>\n
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