Human babies are fascinating creatures. Despite being completely depending on their parents for a very long time, they will do some amazing stuff. Babies have an innate understanding of the physics of our world and may learn latest concepts and languages quickly, even with limited information. Even essentially the most powerful AI systems now we have today lack those abilities. Language models that power systems like ChatGPT, for instance, are great at predicting the following word in a sentence but don’t have anything even near the common sense of a toddler.  

But what if an AI could learn like a baby? AI models are trained on vast data sets consisting of billions of information points. Researchers at Latest York University desired to see what such models could do once they were trained on a much smaller data set: the sights and sounds experienced by a single child learning to speak. To their surprise, their AI learned loads—due to a curious baby called Sam. 

The researchers strapped a camera on Sam’s head, and he wore it on and off for one and a half years, from the time he was six months old until somewhat after his second birthday. The fabric he collected allowed the researchers to show a neural network to match words to the objects they represent, reports Cassandra Willyard on this story. (Price clicking only for the incredibly cute pictures!) 

This research is only one example of how babies could take us a step closer to teaching computers to learn like humans—and ultimately construct AI systems which can be as intelligent as we’re. Babies have inspired researchers for years. They’re keen observers and excellent learners. Babies also learn through trial and error, and humans keep getting smarter as we learn more in regards to the world. Developmental psychologists say that babies have an intuitive sense of what is going to occur next. For instance, they know that a ball exists regardless that it’s hidden from view, that the ball is solid and won’t suddenly change form, and that it rolls away in a continuous path and may’t suddenly teleport elsewhere. 

Researchers at Google DeepMind tried to show an AI system to have that very same sense of “intuitive physics” by training a model that learns how things move by specializing in objects in videos as an alternative of individual pixels. They trained the model on a whole bunch of 1000’s of videos to learn the way an object behaves. If babies are surprised by something like a ball suddenly flying out of the window, the speculation goes, it’s because the article is moving in a way that violates the newborn’s understanding of physics. The researchers at Google DeepMind managed to get their AI system, too, to point out “surprise” when an object moved in another way from the way in which it had learned that objects move.

Yann LeCun, a Turing Prize winner and Meta’s chief AI scientist, has argued that teaching AI systems to watch like children could be the way in which forward to more intelligent systems. He says humans have a simulation of the world, or a “world model,” in our brains, allowing us to know intuitively that the world is three-dimensional and that objects don’t actually disappear once they exit of view. It lets us predict where a bouncing ball or a speeding bike might be in just a few seconds’ time. He’s busy constructing entirely latest architectures for AI that take inspiration from how humans learn. We covered his big bet for the long run of AI here.

The AI systems of today excel at narrow tasks, resembling playing chess or generating text that feels like something written by a human. But compared with the human brain—essentially the most powerful machine we all know of—these systems are brittle. They lack the form of common sense that will allow them to operate seamlessly in a messy world, do more sophisticated reasoning, and be more helpful to humans. Studying how babies learn could help us unlock those abilities. 

Deeper Learning

This robot can tidy a room with none help

Robots are good at certain tasks. They’re great at picking up and moving objects, for instance, they usually’re even convalescing at cooking. But while robots may easily complete tasks like these in a laboratory, getting them to work in an unfamiliar environment where there’s little data available is an actual challenge.

Pick this up, please: Now, a brand new system called OK-Robot could train robots to choose up and move objects in settings they haven’t encountered before. It’s an approach that may have the ability to plug the gap between rapidly improving AI models and actual robot capabilities, because it doesn’t require any costly, complex additional training. Read more from Rhiannon Williams here.

Bits and Bytes

Semafor 🤝🏻 Microsoft 
The news startup has struck a cope with Microsoft to make use of the tech giant’s AI chatbots to create stories. In breaking news events, Semafor will use the chatbots to look for reporting and commentary in several languages from other news sources all over the world. This reporting will go right into a latest feed called “Signals.” (Financial Times) 

A multinational company lost $26 million in a deepfake call scam
Deepfakes are uncontrolled, and it’s not only porn. Using deepfakes of a multinational company’s chief financial officer, scammers managed to idiot employees into transferring company funds to 5 different Hong Kong bank accounts, based on the  As this technology gets higher and more accessible, expect to see more stories like this. (Bloomberg) 

EU countries give the AI Act their seal of approval
The AI Act has inched closer to getting into force as EU countries voted in favor of the law. But in typical EU fashion, there was plenty of last-minute panicking and raised tensions as France tried to water down the bill.  has a full summary of the drama. The last remaining step is for the European Parliament to vote for it later this spring. Dragoș Tudorache, one in all the leading negotiators for the AI Act, might be speaking at our event EmTech Digital in London on April 16 and 17. 

Contained in the music industry’s high-stakes AI experiments
A fun story taking a look at the disruption happening within the music industry and the way one veteran, Lucian Grainge, the chairman and CEO of Universal Music Group, is attempting to reap the advantages of the technology without sacrificing copyright. (The Latest Yorker)