It's not often you start reading a book and within a few pages are thinking 'this is something special.' Peter Lamont writes with a distinctive style, in places verging on poetry or liturgy in the way he uses repeated sentences for emphasis. There's also something of the dance of the seven veils about the whole thing - he glides around a subject, letting the reader catch a glimpse of something interesting, but taking his time to coyly reveal things. That can be a touch irritating at times, but it certainly catches the attention. What this book isn't despite the subtitle, is a 'how to' guide, except at the most basic level. And it probably isn't about radical thinking per se either - it's more about the nature of thinking in general, and critical thinking in particular. Lamont uses various walks around bits of Edinburgh (where he lives and works), using historical connections to expose us to the nature of what we think about things and what to make of...

Marcus Chown graduated from the University of London in 1980 with a first class degree in physics. He also earned a Master of Science in astrophysics from the California Institute of Technology. With much experience writing for magazines such as New Scientist, Chown has written a string of successful popular science books. His latest title is A Crack in Everything . Why black holes? I thought there was a fascinating, and largely untold, story about how black holes, once considered so ridiculous as to not even be the preserve of science fiction, have moved relentlessly into the centre of science over the past century. They evidently play some key but mysterious role in the universe, creating all we see around us and even explaining why we are here at all. But what that is nobody knows. What I am talking about is 'supermassive' black holes. There is one in the heart of every galaxy, and some have huge masses of tens of billions of times that of the sun. What they are doing there?...

We've all got a favourite bit of technology that has been 'coming soon' for decades. Nicole Kobie takes us through the historical journey to the present for a range of such technologies from flying cars to robots (more detail in a moment). In each case these technologies seemed achievable many decades earlier, but the reality has been that making the dream real proved much harder than most envisaged (especially the inventors and investors). Kobie takes us through driverless cars, AI, robots, augmented and virtual reality (AR/VR), cyborgs and brain interfaces, flying cars, Hyperloops and smart cities. Many of these topics are much discussed, but it's really helpful seeing them all pulled together to get an overview of the way that we repeatedly get drawn into failed investments of time and money into a science fictional future without thinking enough about the practicalities of making it happen. My least favourite section was smart cities - I think most people (once Hype...

When I first saw the title of this book I assumed it was yet another attempt to take us from the earliest life to humans, but, as the subtitle suggests, the target is much broader - getting to us all the way from the Big Bang. This makes it sound like it's going to be a chronological approach, but it's rather more fragmented - while it does sort of follow a timeline, we get, for example, a chapter that introduces the relevant key parts of physics and another primarily on molecules, with the timeline more of a background than the main content. Taking this long span and wide sciences approach means there is a huge amount to cram in, even though it's a somewhat over-long book. Covering so much is a daunting endeavour for which I have to admire Tim Coulson's bravery. One potential problem is that it means having to be very summary in parts. Almost inevitably it's more summary about areas outside Coulson's own field of biology and this can be detrimental - in can be ...

Neil Lawrence is the DeepMind Professor of Machine Learning at the University of Cambridge where he leads the university-wide initiative on AI, and a Senior AI Fellow at the Alan Turing Institute. Previously he was Director of Machine Learning at Amazon, deploying solutions for Alexa, Prime Air and the Amazon supply chain. Co-host of the Talking Machines podcast, he's written a series for The Guardian and appeared regularly on other media. Known for his policy and societal work with the UK's AI Council, the Centre for Data Ethics and Innovation, and the OECD's Global Partnership on AI, his research focuses on improving data governance, accelerating scientific discovery, and how humans can take back control of large AI systems. His latest title is  The Atomic Human . What would you like your book to achieve? I wanted it to speak to individuals from different backgrounds in a way that didn’t preach or tell, but told stories in a way the reader could relate to. I hope the book...

There's no doubt that Matt Parker can make practically anything interesting - this is one of the few books I've ever read where I genuinely enjoyed the introduction. But there was a real challenge here. In a review of a recent book about maps and mathematics I said 'I always found [geometry and trigonometry] the most tedious aspect of maths.' Take a look at the subtitle here: 'the life-changing magic of trigonometry'. It's no surprise that the 'trig' word turns up - it literally means triangle measuring (trigon is an obsolete term for a triangle). But it inevitably raises a shudder for many. Parker does acknowledge this in his pure trigonometry section, suggesting it's primarily because it's a pain remembering what tan and cos and sin refer to, but pointing out convincingly how useful and powerful trigonometry is. I confess, however, it was still my least-favourite chapter in the book. Thankfully there's a lot more, introduced with Parke...

I very much enjoyed Lucy Jane Santos' previous title Half Lives , which covered 'the unlikely history of radium'. Her enthusiasm for the topic shone through (in true radium fashion). As well as the straight history of the discovery and deployment of radium, we got lots on its use in commercial products - initially in quack medicine, but later in every type of product imaginable, with Boots even selling radiated soda syphon cartridges. In this follow-up Santos takes on what might seem a quite similar topic: the history of our discovery and use of uranium. There is obviously a degree of overlap between the topics, particularly in the quack medicine usage - particularly delightful were some of the more wacky US attempts to monetise atomic appeal by, for instance, setting up treatment barns where you could be immersed in allegedly (though often not actually) radioactive soil in a process that felt more like going to Lourdes than a true medical treatment. But in practice both be...

Jules Howard is a zoological correspondent, science writer and broadcaster, whose recent book, Wonderdog , won the 2022 Barker Book Prize for non-fiction. He writes on a host of topics relating to zoology, ecology and wildlife conservation and appears regularly in BBC Science Focus magazine and on radio and TV, including BBC Breakfast and Radio 4's Nature Table and The Ultimate Choice. He lives in Northamptonshire with his wife and two children. His latest title is Infinite Life . Why write about eggs? Like many, I have always loved those big epic tales, based on science, that chart the evolution of animals – the Cambrian Explosion, fish moving onto the land, early amphibians and reptiles, the demise of dinosaurs and the rise of mammals… Gould, Dawkins, Attenborough did it so well, and I loved this kind of information when I was starting out in zoology. I guess I was always looking for an opportunity to tell my own version of this… and that’s where the eggs idea comes into it. Eggs...

Some titles tell you nothing about the book itself - but The AI Mirror puts Shannon Vallor's central argument front and centre: that artificial intelligence, particularly generative AI such as ChatGPT, is not intelligence at all, but rather holds a mirror up to our own intelligence. As Vallor points out, your reflection in a mirror certainly looks and acts like you - but it is not a person. This is a metaphor that works impressively well. It reflects (get it?) the total lack of understanding in systems that are simply reflecting back data from a vast amount of human output. That's not to say that they have no value, but we always have to be aware of their nature and their abilities both to produce errors as a result and to reflect our in-built biases, which we may consciously suppress but nonetheless come through in the data. To quote Vallor, these systems 'aren't designed to be accurate, they are designed to sound accurate'. What Vallor tells us we have that AI d...