Skip to main content

Authors - G

A-B-C-D-E-F-G-H-I-J-K-L-M-N-O-P-Q-R-S-T-U-V-W-X-Y-Z

Greg Gage (with Tim Marzullo)

Pauline Gagnon

Chris Gainor

Clive Gamble (with John Gowlett and Robin Dunbar)

Lynn Gamwell

Bergita and Urs Ganse

Shan Gao

Marta Garcia-Matos (with Lluis Torner)

Dan Gardner

Martin Gardner

Evalyn Gates

Atul Gawande

Adam Gazzaley (with Larry Rosen)

James Geach

Henry Gee

Rose George

Sean Gerrish

Christopher Gerry (with Kimberley Bruno)

Shohini Ghose

Masha Gessen

David Gibson

Susannah Gibson

Gerd Gigerenzer

George Gilder

Colin Gillespie

James Gillies

Malcolm Gladwell

Joshua Glenn (Ed.)

James Gleick

Marcelo Gleiser (with Adam Frank and Evan Thompson)

Ian Glynn

Laurie Godfrey (with Andrew Petto)

Philip Goff

Ben Goldacre

Billy Goldberg (with Mark Leyner)

Alfred Scarf Goldhaber (with Robert Crease)

Noah Goldstein (with Steve Martin & Robert Cialdini)

Mike Goldsmith

Lawrence & Nancy Goldstone

Jeff Gomez

Laurence Gonzales

Jane Goodall

  • Hope for Animals and their World ****
  • Paul Goodwin

  • Something Doesn't Add Up: surviving statistics in a post-truth world ***
  • Michael Gordin

    Alan Goriely

    Elisabeth Gordon (with Laurent Keller)

    Angélica Gorodischer

    Richard Gott (with Michael Strauss and Neil de Grasse Tyson)

    Richard Gott

    John Gowlett (with Clive Gamble and Robin Dunbar)

    Francis Graham-Smith

    Ron Graham (with Persi Diaconis)

    John Grant

    Andrew Granville and Jennifer Granville

    Or Graur

    Jeremy Gray

    Theodore Gray

    Samuel Graydon

    Kevin Grazier (with Stephen Cass)

    Jaime Green

    Brian Greene

    Kate Greene

    Samuel Greengard

    Pietro Greco

    Peter Grego

    Andrew Gregory

    Bruce Gregory

    Jane Gregory

    Richard Gregory

    Tim Gregory

    John Gribbin

    John Gribbin (with Mary Gribbin)

    Tom Griffiths (with Brian Christian)

    Tom Grimsey (with Peter Forbes)

    Frederick Grinnell

    Simon Guerrier (with Marek Kukula)

    Göran Grimvall

    Steven Gubser (with Frans Pretorius)

    Lee Gutkind


    Comments

    Popular posts from this blog

    Math for English Majors - Ben Orlin *****

    Ben Orlin makes the interesting observation that the majority of people give up on understanding maths at some point, from fractions or algebra all the way through to tensors. At that stage they either give up entirely or operate the maths mechanically without understanding what they are doing. In this light-hearted take, Orlin does a great job of taking on mathematical processes a step at a time, in part making parallels with the structure of language. Many popular maths books shy away from the actual mathematical representations, going instead for verbal approximations. Orlin doesn't do this, but makes use of those linguistic similes and different ways of looking at the processes involved to help understanding. He also includes self-admittedly awful (but entertaining) drawings and stories from his experience as a long-time maths teacher. To make those parallels, Orlin refers to numbers as nouns, operations as verbs (though he points out that there are some flaws in this simile) a

    Everything is Predictable - Tom Chivers *****

    There's a stereotype of computer users: Mac users are creative and cool, while PC users are businesslike and unimaginative. Less well-known is that the world of statistics has an equivalent division. Bayesians are the Mac users of the stats world, where frequentists are the PC people. This book sets out to show why Bayesians are not just cool, but also mostly right. Tom Chivers does an excellent job of giving us some historical background, then dives into two key aspects of the use of statistics. These are in science, where the standard approach is frequentist and Bayes only creeps into a few specific applications, such as the accuracy of medical tests, and in decision theory where Bayes is dominant. If this all sounds very dry and unexciting, it's quite the reverse. I admit, I love probability and statistics, and I am something of a closet Bayesian*), but Chivers' light and entertaining style means that what could have been the mathematical equivalent of debating angels on

    2040 (SF) - Pedro Domingos ****

    This is in many ways an excellent SF satire - Pedro Domingos never forgets that part of his job as a fiction writer is to keep the reader engaged with the plot, and it's a fascinating one. There is one fly in the ointment in the form of a step into heavy-handed humour that takes away its believability - satire should push the boundaries but not become totally ludicrous. But because the rest of it is so good, I can forgive it. The setting is the 2040 US presidential election, where one of the candidates is an AI-powered robot. The AI is the important bit - the robot is just there to give it a more human presence. This is a timely idea in its own right, but it gives Domingos an opportunity not just to include some of the limits and possibilities of generative AI, but also to take a poke at the nature of Silicon Valley startups, and of IT mega-companies and their worryingly powerful (and potentially deranged) leaders. Domingos knows his stuff on AI as a professor of computer science w