For decades linguists have argued over how children learn language. Some think that babies are born as “blank boards” who pick up language simply from experience — hearing, seeing and playing with the world. Others argue that experience is not enough and that babies’ brains must be hardwired to make acquiring language easy.
AI models such as GPT-4 have done little to settle the debate. The way these models learn language — by collecting lots of text data from millions of web pages—is greatly different to the experiences of babies.
A team of scientists at New York University examined the question by training an AI model on the experiences of a single baby. Between the ages of six and 25 months, a young child called Sam had a head-wearing camera for an hour a week-around one of his waking hours. The camera recorded everything he saw and heard while he played with toys, enjoyed days at the park and interacted with his pet cats. The recordings and audio were fed into an Al, which was set up to know that images and words that appeared at the same time were related, but was otherwise left to make sense of the mess of colors and speech that Sam experienced.
Despite the limited training data, the AI was able to pick out objects and learn the matching words. The researchers tested the model by asking it to identify objects that Sam had seen before, such as a chair from his home or one of his toy balls. Given a list of four options the model picked the correct word 62 of the time, far above the chance level of 25%. To the researchers’ surprise, the model could also identify chairs and balls that Sam had never seen. The AI learned at least 40 different words, but it was far from matching Sam’s vocabulary and language abilities by the end of the experiment.
The researchers recently argue in the journal Science that, to match words to objects, learning from experience may well be enough. Doubters, however, doubt that the AI would be able to learn abstract nouns or verbs, and question how similar the learning processes really are. The mystery of language acquisition lives on.
【小题1】What does the underlined word “hardwired” in Paragraph 1 probably mean?| A．Organic. | B．Average. | C．Born. | D．Reliable. |
| A．AI models can understand babies’ speech. |
| B．AI models can enrich their vocabulary by themselves. |
| C．AI models can remember more objects but can’t pick them out. |
| D．AI models can learn more words but can’t match babies’ abilities. |
| A．Leaning from experience is far from enough. |
| B．Language abilities of babies are born in nature. |
| C．How the AI is developed proves easy for scientists. |
| D．How the AI picks up the language remains unknown. |
| A．Positive. | B．Doubtful. | C．Unclear. | D．Subjective. |
