#Deep Learning

The story of the deep learning revolution from the AlexNet moment through the development of the Transformer, told as a narrative of rapid, cascading discovery in which one breakthrough enabled the next. The fastest scientific revolution in the history of AI — and what it actually means that machines can now do what only humans could do before.

The full story of the 'Attention Is All You Need' paper — how a Google Brain team developed a new architecture for sequence modelling that discarded recurrence entirely, why it worked better than everything that came before, and how it became the foundation for every large language model in existence. The paper that made GPT possible, and the elegant idea at its heart.

The Nobel laureate who spent fifty years building the technology he now warns against — the full story of Hinton's departure from Google, his public warnings about AI risk, and what it means that the person who did more than anyone to make the deep learning revolution possible now believes that revolution may have been a mistake. The most consequential change of mind in the history of AI.

The third Godfather of Deep Learning, who spent his career building the mathematical foundations of neural network learning and who has, in the years since the ChatGPT moment, become one of the most active and most credible advocates for AI safety research and AI regulation. Why the person who built so much of what AI is now believes that the field's progress requires governance it has been reluctant to accept.

How Fei-Fei Li assembled fourteen million labelled images over three years of painstaking work, created the most important dataset in the history of AI, and built the benchmark that made the deep learning revolution possible. The full story of ImageNet — the years of labour, the unconventional methodology, the competition that changed everything in 2012, and why one woman's conviction that data was as important as algorithms turned out to be exactly right.

The full story of the ImageNet competition in 2012 — the weeks of training on two gaming GPUs, the submission that shocked the computer vision world, the researchers who remember exactly where they were when the results came in, and why a single paper changed the trajectory of artificial intelligence. The starting gun of the modern AI era.

He kept working on neural networks when everyone told him it was a dead end. He developed backpropagation, built the research group that produced AlexNet, and triggered the deep learning revolution. Then he quit Google to warn the world that he was afraid of what he had built. The full story of the most important AI researcher of his generation — and the journey from stubborn optimist to frightened sage.

He invented convolutional neural networks, built the first AI system to process real-world visual data at scale, and became the architect of Meta's AI empire. The most argumentative of the Godfathers of Deep Learning — and why his arguments, however combative the delivery, usually turn out to be right.

The third Godfather of Deep Learning — his foundational contributions to recurrent networks, attention mechanisms, and generative models, his evolution from pure researcher to the field's most prominent voice for AI safety and ethics, and why the man who spent his career building increasingly powerful AI systems has become one of the most persuasive voices for ensuring those systems are safe.