Although Mallaby does occasionally still go into fan mode - reading this you would think that AlphaFold had successfully perfectly predicted the structure of every protein, where it is usually not sufficiently accurate for its results to have direct practical application - we get a real feel for the way this relatively unusual company was swiftly and successfully developed away from Silicon Valley. It's readable and gives an important understanding of where some our key AI expertise came from.
Perhaps not surprisingly, where the book really takes off is in the later chapters, after the successes of AlphaGo and AlphaFold. when the DeepMind people were left behind by OpenAI's generative AI work and had to rapidly change gear under outside pressure. Let's face it, a story of responding to threat is much more interesting than one of straight success. Not only was this phase of development one where the team was caught on the back foot, a huge rift emerged over whether developers should be heading towards artificial general intelligence (AGI) very carefully for safety reasons (the initial DeepMind approach) or just going for it full throttle like OpenAI.
It's arguable some of the safety concerns were fruitless in that large language models seem unlikely ever to be the starting point for a true AGI, but there was (and is) still a very real threat from this software in areas such as privacy, copyright theft and environmental impact. This part of the book is unputdownable stuff.
Overall, The Infinity Machine is a little too long, giving too much detail of the people outside the core group and of every step along the way of the company's development. However, this doesn't really matter as it provides excellent documentation of a key player in the rise and rise of AI.
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Review by Brian Clegg - See all Brian's online articles or subscribe to a weekly email free here
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