Babies use ‘helpless’ phase to build powerful neurological foundations

Babies use the period of ‘postnatal helplessness’ to learn powerful foundation models similar to those underpinning generative Artificial Intelligence, according to a new study led by Trinity College Dublin. 

 

Compared to many animals, humans are helpless for a long time after birth. Many animals, such as horses and chickens, can walk on the day they are born. This protracted period of ‘helplessness’ puts human infants at risk and places a huge burden on the parents, but surprisingly has survived evolutionary pressure.  

 

Recently published in Trends in Cognitive Sciences study authors found that the classic explanations for infant helplessness are not supported by modern brain data.

 

“Since the 1960s scientists have thought that the helplessness exhibited by human babies is due to the constraints of birth,” lead author Professor Rhodri Cusack said. 

 

“The belief was that with big heads human babies have to be born early, resulting in immature brains and a helpless period that extends up to one year of age. We wanted to find out why human babies were helpless for such a long period.” 

 

Working with Professor Christine Charvet of Auburn University and Dr. Marc’Aurelio Ranzato, a senior AI researcher at DeepMind, the researchers compared brain development across animal species drawing on longstanding project Translating Time, which equates corresponding ages across species to establish that human brains are more mature than many other species at birth.  

 

The researchers used brain imaging and found that many systems in the human infant’s brain are already functioning and processing the rich streams of information from the senses, contradicting the long-held belief that many infant brain systems are too immature to function. 

 

Comparisons with AI

 

The team then compared learning in humans with the latest machine learning models, where deep neural networks benefit from a ‘helpless’ period of pre-training.  

 

In the past, AI models were directly trained on tasks for which they were needed. 

 

For example a self-driving car was trained to recognise what they see on a road. But now models are initially pre-trained to see patterns within vast quantities of data, without performing any task of importance. The resulting foundation model is subsequently used to learn specific tasks. It has been found this ultimately leads to quicker learning of new tasks and better performance.  

 

“We propose that human infants similarly use the ‘helpless’ period in infancy to pre-train, learning powerful foundation models, which go on to underpin cognition in later life with high performance and rapid generalisation. This is very similar to the powerful machine learning models that have led to the big breakthroughs in generative AI in recent years, such as OpenAI’s ChatGPT or Google’s Gemini,” Professor Cusack explained. 

 

This development, and increased understandings about how babies learn, researchers believe, could change the next generations of AI models. 

 

“Although there have been big breakthroughs in AI, foundation models consume vast quantities of energy and require vastly more data than babies,” the Professor continued. 

 

“Understanding how babies learn may inspire the next generation of AI models. The next steps in research would be to directly compare learning in brains and AI,” he concluded. 

 

This research was supported by the European Research Council. Review ‘Helpless infants are learning a foundation model’ here.