A study by professors Beuls and Van Eecke critically examines current AI language acquisition methods versus children's learning processes. Children learn through interactive communication, while AI models like ChatGPT rely on vast text data to generate responses. This study suggests rethinking AI language learning towards more human-like interactions, proposing that such models could understand language more contextually, resulting in reduced hallucinations and biases. By involving sensory experiences and environments, the new approach aims for a richer language comprehension in AI systems.
"Children learn their native language by communicating with the people around them in their environment. As they play and experiment with language, they attempt to interpret the intentions of their conversation partners."
"The current generation of large language models (LLMs), such as ChatGPT, learns language in a very different way, generating texts that are often indistinguishable from human writing but exhibiting inherent limitations."
Collection
[
|
...
]