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Creatively Speaking: Hallie Ephron

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Creatively Speaking continues today with author and journalist Hallie Ephron. You've probably heard of her sister, Nora, and we've written here on this blog before about another Ephron sister, Amy, but would you believe all four Ephron girls are accomplished writers? And if that wasn't enough, how about this: Mom and Dad Ephron were also successful writers! (playwrights and screenwriters) Hallie has a new novel out called Never Tell a Lie, a wonderful mystery set in and around New England. In the below interview, she talks candidly about growing up in a household of writers, her work as a book reviewer, the process of writing a mystery, as well as her experience penning her own books, including her latest.

Tune back in tomorrow for a chance to win one of TWO copies of
Never Tell a Lie. As always, you'll need to answer some questions that tie back into today's interview. So if you want to better your chances, be sure to click through and read the whole interview.

DI: Let's start with some family history. Both your parents were
accomplished writers; likewise all three of your sisters are. What on
earth was in the water in your neck of the woods?

HE: I don't know about the water, but the house had wall-to-wall books.
I grew up being read to, reading, reciting poetry, and generally
cherishing the written word. Knowing that I come from that amazing gene
pool gave me the courage to write.

DI: You've published other books before, but never fiction. Was there
some hesitation due to the success of your sisters in that genre? Or
were you just saving it all up for this debut?

HE: This is my first solo novel - I published five mysteries with a
co-author writing under the pseudonym G. H. Ephron - but even those I
didn't start writing until I was forty. Of course there was hesitation,
worry that I'd be compared (unfavorably) to them. Finally I decided that
it was okay to try and fail, not okay to fail to try. So I jumped in.

DI: You've been reviewing mystery novels for the Boston Globe for many
moons. Clearly you know what works and what doesn't. Did that make
writing your mystery any easier?

HE: Being a book reviewer makes the writing harder and easier. Harder
because it's nearly impossible to shut down that inner critic and get a
lousy first draft written. Easier because I've seen what works and what
doesn't, I know a cliche when I see it, and I'm aware of the wide range
of crime fiction sub-genres that are happily thriving so I don't feel
constrained by "rules."

DI: What's the hardest thing about writing a mystery?

HE: Making the ending surprising AND credible at the same time. You want
the reader to say, "Of course, I should have seen that coming." You want
it to be like the ending of "The Sixth Sense" when you realize the main
character is dead and you want to watch that movie again to find the
clues that you missed the first time around.

DI: Never Tell a Lie starts with a newspaper clipping from the missing
persons page. In a way, this little teaser borrows from the in medias
res
technique, which I just blogged about on this site a couple weeks ago.
Of course, lots of mysteries make great use of the device to ensure the
reader is hooked from the beginning. Did you always know you'd start the
story with the newspaper announcement that Melinda White had gone
missing, and then double back to the time when she disappears? Or was
the teaser added later, after the novel was finished?

HE: Great question! That newspaper article is the last thing I wrote,
and full credit for it goes to my daughter Naomi. She read Chapter 1 and
said to me that she'd loved it, but it was so much more compelling and
suspenseful **because** she knew that Melinda, the woman who comes to the yard sale,
was going to disappear. A light bulb went off in my head, and I added
the newspaper clipping to give readers that same insight. It adds a
layer of suspense to what might seem like a safe suburban opening scene.

DI: What was the process like for this book? How long did it take to
crank out the first draft? How long did you revise? Who were your
readers and how much revising did you do based on their suggestions?

HE: It felt like this book took me forever -- about three years, from
inspiration at that yard sale until final-final draft. The first two
years were writing (I was also working on "1001 Books for Every Mood")
and a year to revise. I have a wonderful writing group and they are my
first readers.

Then I have a few other writer friends who read the various finished
drafts and I revise some more. My agent is a fantastic reader, too, and
after I'm satisfied with it, I send it to her and we go back and forth a
few more times. Every time I make a major change to the manuscript, I do
a "SAVE AS" and increment the version number--the final file name for the novel was
NTAL32.

DI: With all your siblings' Hollywood connections, are there any plans
to turn the novel into a movie?

HE: There's a lot of interest in it right now but nothing definite.
Fingers crossed!

DI: What are some of your favorite mysteries?

HE: There are so many! I was hooked early on by one of the classics,
Wilkie Collins's "Woman in White." Some more recent favorites: Michael
Connelly's "Lincoln Lawyer" and Leonie Swann's "Three Bags Full" and
Jess Walter's "Citizen Vince" and Nancy Pickard's "The Virgin of Small
Plains."

DI: What advice do you have for aspiring mystery writers?

HE: Actually, I have a whole book full of advice in my "Writing and
Selling Your Mystery Novel: How to Knock 'Em Dead with Style." Bottom
line, you'll need dogged determination and intestinal fortitude to stick
with it, through first draft and endless revisions, until your words are
polished to lapidary perfection. It doesn't hurt, either, to have the
hide of a rhinoceros to withstand the inevitable rejections. Talent
being equal, what separates many a published mystery writer from an
unpublished one is sheer stamina and blind luck. Only gluttons for
punishment need apply.

Browse through past Creatively Speaking posts here >>

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iStock // Ekaterina Minaeva
technology
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
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iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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iStock
Animals
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Scientists Think They Know How Whales Got So Big
May 24, 2017
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iStock

It can be difficult to understand how enormous the blue whale—the largest animal to ever exist—really is. The mammal can measure up to 105 feet long, have a tongue that can weigh as much as an elephant, and have a massive, golf cart–sized heart powering a 200-ton frame. But while the blue whale might currently be the Andre the Giant of the sea, it wasn’t always so imposing.

For the majority of the 30 million years that baleen whales (the blue whale is one) have occupied the Earth, the mammals usually topped off at roughly 30 feet in length. It wasn’t until about 3 million years ago that the clade of whales experienced an evolutionary growth spurt, tripling in size. And scientists haven’t had any concrete idea why, Wired reports.

A study published in the journal Proceedings of the Royal Society B might help change that. Researchers examined fossil records and studied phylogenetic models (evolutionary relationships) among baleen whales, and found some evidence that climate change may have been the catalyst for turning the large animals into behemoths.

As the ice ages wore on and oceans were receiving nutrient-rich runoff, the whales encountered an increasing number of krill—the small, shrimp-like creatures that provided a food source—resulting from upwelling waters. The more they ate, the more they grew, and their bodies adapted over time. Their mouths grew larger and their fat stores increased, helping them to fuel longer migrations to additional food-enriched areas. Today blue whales eat up to four tons of krill every day.

If climate change set the ancestors of the blue whale on the path to its enormous size today, the study invites the question of what it might do to them in the future. Changes in ocean currents or temperature could alter the amount of available nutrients to whales, cutting off their food supply. With demand for whale oil in the 1900s having already dented their numbers, scientists are hoping that further shifts in their oceanic ecosystem won’t relegate them to history.

[h/t Wired]

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