Does deep learning understand our language?

If a computer gives you all the right answers, does it mean that it is understanding the world as you do? This is a riddle that artificial intelligence scientists have been debating for decades. And discussions of understanding, consciousness, and true intelligence are resurfacing as deep neural networks have spurred impressive advances in language-related tasks.

Many scientists believe that deep learning models are just large statistical machines that map inputs to outputs in complex and remarkable ways. Deep neural networks might be able to produce lengthy stretches of coherent text, but they don’t understand abstract and concrete concepts in the way that humans do.

Other scientists beg to differ. In a lengthy essay on Medium, Blaise Aguera y Arcas, an AI scientist at Google Research, argues that large language models—deep learning models that have been trained on very large corpora of text—have a great deal to teach us about “the nature of language, understanding, intelligence, sociality, and personhood.”

Read the full article on TechTalks.

For more on the philosophy of AI:

• Why lifeless AI is not intelligent

• To create AGI, we need a new theory of intelligence

• Will artificial intelligence have a conscience?

• Human Compatible: A timely warning on the future of AI