Between sustainability and risk: why CIOs are considering small language models

For example, Esposito says, IT can isolate a narrow language task, take an SLM, put it in its cloud, and give it access only to the corporate document database. From there, it asks the model only questions related to those documents.

“From the first experiments, it seems that not only energy consumption is reduced, but also the probability of hallucinations,” he says. “After all, companies’ AI models don’t have to know everything, but only respond to certain applications. SLMs can still do translations, perform market trend analysis, automate customer service, manage IT tickets, create a business virtual assistant, and more. It seems more efficient to me to limit the domain and specialize it, keeping it under IT control.”

Weighing gen AI business and small models

Control is key. Alessandro Sperduti, director of the Augmentation Center of the Bruno Kessler Foundation (FBK), says in AI, we risk the domination of private companies. “In the past, the most important AI systems in the world were developed in universities, while today they’re not because private technological giants have emerged with a spending power with which the public can’t compete,” he says.



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