In the spring of 2017, in a room on the second floor of Google's Building 1965, a college intern named Aidan Gomez stretched out, exhausted. It was three in the morning, and Gomez and Ashish Vaswani, a scientist focussed on natural language processing, were working on their team's contribution to the Neural Information Processing Systems conference, the biggest annual meeting in the field of artificial intelligence. Along with the rest of their eight-person group at Google, they had been pushing flat out for twelve weeks, sometimes sleeping in the office, on couches by a curtain that had a neuron-like pattern. They were nearing the finish line, but Gomez didn't have the energy to go out to a bar and celebrate. He couldn't have even if he'd wanted to: he was only twenty, too young to drink in the United States.

Publishing a book is a big occasion for any writer, and Rory Cellan-Jones is no exception. "Like any author, I obsessively check Amazon," he said. The former BBC technology correspondent wrote a memoir untangling the truth about his family history. What had popped up on the Amazon website was a biography of Cellan-Jones, with a naively designed cover by someone he had never heard of. "I thought: 'This is strange – who's writing a biography of me?'" Cellan-Jones told the Observer.

Niki Parmar and Ashish Vaswani co-authored a seminal paper that set the groundwork for ChatGPT and other generative AI models. ChatGPT has taken the world by storm, but seeds of the groundbreaking technology were sown at the USC Viterbi School of Engineering. The seminal paper "Attention Is All You Need," which laid the foundation for ChatGPT and other generative AI systems, was co-authored by Ashish Vaswani, a PhD computer science graduate ('14) and Niki Parmar, a master's in computer science graduate ('15). The landmark paper was presented at the 2017 Conference on Neural Information Processing Systems (NeurIPS), one of the top conferences in AI and machine learning. In the paper, the researchers introduced the transformer architecture, a powerful type of neural network that has become widely used for natural language processing tasks, from text classification to language modeling.

Kendal Parmar's son went from being a sporty and sociable boy who loved school, to a child who would stay in his room and rarely go outside. The change in his personality was down to a gaming disorder that crept up on him at the age of 12, when he started secondary school. Three years later, Joseph is still struggling with the problem. Parmar says the biggest sign that something was wrong was the amount of arguing that would occur when she asked him to stop playing video games. "Eventually his habits developed and he was gaming all the time. He became too terrified to go to school and he was terrified of people," she says.

A silicon wafer designed to sort particles found in bodily fluids for the purpose of early disease detection. A chip that can diagnose a potentially fatal condition faster than the best lab in the country, a camera that can see so deeply into a pill it can tell if its molecular structure has more in common with a real or counterfeit tablet, and a system that can help identify if a patient has a mental illness just from the words they use: IBM is betting that a mix of AI and new hardware can make all three possible within the coming years. IBM's research labs are already working on turning these concepts into fully-fledged healthcare tools, combining the company's existing machine learning and artificial intelligence systems with newer kit including revamped silicon and millimetre wave phased array sensors. Playing House: How IBM's Watson is helping doctors diagnose the most rare and elusive illnesses Marburg Hospital's Centre for the Rare and Undiagnosed Diseases is using the cognitive computing system to solve some of the most complex medical cases. The latter will be used in'hyperimaging systems' -- tools that will be able to pick up not only images from the visible light that humans can see, but other parts of the electromagnetic spectrum that we can't.