Over at Granta, Melissa Febos writes about truth. As she puts it, “The true telling of our stories often requires the annihilation of other stories, the ones we build and carry through our lives because it is easier to preserve some mysteries.”
True Story
Tuesday New Release Day: Bolaño, Crichton, Sondheim
Another posthumously published Roberto Bolaño novel has arrived, The Third Reich. Time to update our Bolaño Syllabus again? Also posthumously published is Michael Crichton’s Micro, which was a third finished when he died and was completed using Crichton’s notes by Richard Preston. Also new this week is Stephen Sondheim’s Look, I Made a Hat: Collected Lyrics (1981-2011).
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Perhaps They’re More Into Non-Fiction
I’m neither a therapist nor a zoologist, but maybe if we want to ward off midlife crises in great apes, we should stop reading them so much Jane Austen.
“You may better yourself by reading this, but who cares?”
“Usually, with a novel, you start with no idea what to do because your job is to create convincing characters and then they just run around getting crazy. The problem with writing a memoir, obviously, is you can’t do that because you sort of know what’s going to happen. Because you’re the character.” – Gary Shteyngart
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How the Novel Made the World
In the June Atlantic, William Deresiewicz revisits that old favorite subject, the past and future of the Great American novel, in a review of two new books about the history of novels: The Dream of the Great American Novel by Laurence Buell and The Novel: A Biography by Michael Schmidt. (Dizzy yet? If not, consider nine other experts’ opinions on the Great American Novel here at The Millions, for a round dozen.)
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The Power of Poetry
Computational linguists Marjan Ghazvininejad and Kevin Knight have created a computer program that uses meter and rhyme to generate more secure, memorable passwords. You could also check out Andrew Kay’s Millions essay on the power of poetry.
Twitter Bird Flu
Hypochondriacs rejoice! A team of scientists from the University of Rochester is working on a “machine-based algorithm” in the same vein as Google Flu Trends—but this time based on Twitter and smart phone data—to predict, with about 90% accuracy, when you’ll next get sick.