The problem of defining Artificial Intelligence has always clashed with the difficulties we have in understanding and defining what Intelligence itself is. As a matter of fact, for legislative purposes it is preferred to define what an AI system is. The problem has been debated for centuries, influencing how research has dealt with the problem of simulating the phenomenon in machines. While the hype around AI is high, at this time, given the success of Large Language Models (LLMs), we are still very far from reproducing intelligence, whatever that is. We have, however, created some useful and powerful tools that learn to perform a good amount of tasks without any need to understand them. While there is still a long way to go before we can explore the problem of providing machines with raison d’être, these tools provide a good set of new capabilities that enable us to start investigating the problem of raison d’exprimer, or the capability for machines to use language as a tool to influence a communicative context, rather than as a product in itself.
Toronto???s 2023 By-Election: Implications for the city???s youth
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