May 6, 2024
This impenetrable primer from science writer Ananthaswamy (Through Two Doors at Once) unsuccessfully attempts to elucidate how AI works. He explains that it learns by scanning data for patterns and then makes predictions about what kinds of data are likely to appear in sequence. Unfortunately, the excruciatingly detailed breakdown of the roles played by probability, principal component analysis (“projecting high-dimensional data onto a much smaller number of axes to find the dimensions along which the data vary the most”), and eigenvectors (which are never satisfactorily defined) will sail over the heads of anyone without an advanced math degree. Biographical background on physicist John Hopfield, electrical engineer Bernhard Boser, and other pioneering contributors to machine learning does little to alleviate the labyrinthine discussions of their advances. There are some bright spots—as when Ananthaswamy discusses how statisticians deduced the authorship of the contested Federalist Papers by analyzing whether the writing more closely reflected the vocabulary of James Madison or Alexander Hamilton—but these highlights are few and far between, surrounded by bewildering equations and dense proofs for mathematical theorems. General readers will struggle to follow this. Agent: Peter Tallack, Curious Minds Agency.
June 15, 2024
A study of the concepts that power AI. In this demanding but rewarding book, Ananthaswamy, author of The Man Who Wasn't There, "explains the elegant mathematics and algorithms [behind]...machine learning, a type of AI that involves building machines that can learn to discern patterns in data without being explicitly programmed to do so." With astute reference to principles from the disciplines of math, computer science, physics, and neuroscience, the author guides readers through the conceptual frameworks involved in the creation of AI. While it would be helpful to come to the book with a strong background in math (especially statistics and calculus), clear and detailed illustrations help make it accessible to anyone willing to immerse themselves in the material. Ananthaswamy makes the power of AI obvious, and his engaging case studies explore its emerging abilities in the generation of new media--text, images, video, and music--and contributions to discoveries in areas such as drug development and the dynamics of gene expression. The author also provides a vivid picture of how AI will continue to transform everyday activities and, very soon, revolutionize our social and economic lives. Ananthaswamy demonstrates how a profound merging of human activities with machine processes is already far along and will soon accelerate strikingly. The author could have offered a little more insight about these coming changes, though the introduction and epilogue do touch on pressing questions about the various risks of emerging technologies and how they might be mitigated. Familiarizing ourselves with what is at stake, the author rightly notes, is now an urgent personal and public responsibility: "It is only when we understand the inevitability of learning machines that we will be prepared to tackle a future in which AI is ubiquitous, for good and for bad." A challenging and illuminating overview of how machine learning works.
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