Email Use Worldwide

Source: Statista

To save visitors to TPV any mental over-exertion, it would appear that, on a world-wide bases, individuals send and receive an average of 76 emails per day.

Makes PG seem like less of an outlier than he thought he was. Who says people don’t read any more?

‘The Spotify Play’ Review: Better Than Piracy

From The Wall Street Journal:

Neil Young, Stevie Nicks and Lindsey Buckingham owe Daniel Ek an enormous debt of gratitude right about now. The rock legends have all recently sold their song publishing rights for gigantic sums, sell-offs that can partially be attributed to the surge in digital revenue that accounts for more than half the global recorded-music market. One man saw all this coming before anyone else: Mr. Ek, the 37-year-old co-founder of Spotify, the world’s largest streaming service with 320 million users and counting.

For those of us who regularly call up almost any song we desire with a tap on our phone screens, it’s easy to think of streaming music as an inevitable development. But for Mr. Ek, streaming’s triumph was more of a self-fulfilling prophecy. Having endured years of pushback, Spotify has been at the vanguard of a global revolution in the way music is consumed. It’s quite a turnabout for the Stockholm native, who has endured heaps of negative press, the enmity of underpaid musicians everywhere, and the looming threat of competing services from Apple, Jay-Z’s Tidal and many others.

. . . .

A rabid music fan as a teenager, Mr. Ek’s exposure to Napster was a profound conversion experience. Shawn Fanning and Sean Parker’s file-sharing service was the shrapnel blast that tore holes through the web’s commercial firewalls. “Napster is probably the internet service which has changed my life more than anything else,” Mr. Ek once told an interviewer. What if he could merge Napster’s peer-to-peer technology with commercial content? What if he could draw file-sharing out of the shadows?

Even while Mr. Ek was rapidly moving up as a programmer in Stockholm’s hot tech market, the notion of a legal answer to Napster’s music streaming never left him. In 2006 Mr. Ek’s tiny startup Advertigo was acquired by Tradedoubler, a digital marketing company whose co-founder Martin Lorentzon was enamored of Mr. Ek and his ideas. The savvy, flamboyant Mr. Lorentzon would become both partner and cheerleader. When he came to visit Mr. Ek in his raffish Stockholm neighborhood, Mr. Ek quoted “The Godfather” at him: “Put your hand in your pocket like you have a gun.”

Mr. Ek knew that what made Napster so revolutionary was its decentralized protocol, its ability to transform everyone’s hard drives into public servers. Mr. Ek’s idea was to use similar technology in an improved experience that would be “better than piracy.” There was only one man for the job: Ludvig “Ludde” Strigeus, Sweden’s leading file-sharing technologist and the inventor of uTorrent, a program for ripping content from illegal sites. Mr. Strigeus and his team of engineers one-upped Napster, devising a system that eliminated glitchy downloading. Mr. Ek was on his way.

It was an inauspicious time for Mr. Ek to be stirring the pot. The music world was squirming its way through an uneasy transition into a digital future, and the great file-sharing panic of the early aughts was still in effect. Thousands of file-sharing users were slapped with lawsuits, while record labels fretted over the cannibalization of CD sales by a method of music consumption they likened to stealing cars from showroom lots in broad daylight. What Mr. Ek envisioned was a “freemium” music service in which ad revenue would be paid to the labels in exchange for the use of their catalogs. Customers would, in theory, eventually convert to the paid subscription service.

Record labels were cold to the ad-revenue model, and insisted on cash on the barrelhead before opening their songbooks. The pursuit of music licenses, Mr. Ek’s biggest hurdle, runs through “The Spotify Play” like a Holy Grail quest. In order to get, Spotify had to give, which is how, according to this book, behemoths like Sony BMG were paid tens of millions in non-recoupable advances and negotiated deals that gave them big equity stakes in Ek’s company.

It wasn’t just the music companies that Mr. Ek had to contend with; Steve Jobs wanted him marginalized, as well. By the time Spotify was founded in 2006, the iTunes store was the most successful music retailer on the planet, creating a proprietary system of MP3s for sale that drove consumers to Apple’s iPods. Spotify was bad for business, and Apple mounted a campaign against Mr. Ek, at one point threatening to remove Spotify from its app store. A fusillade of litigation between the two companies followed—and continues unabated. Eventually, Apple would see the wisdom of Mr. Ek’s model and offer streaming, though Spotify currently has more than five times as many paid subscribers as Apple Music’s streaming service.

So what about the musicians themselves? Spotify is still regarded as an evil empire among artists who feel they are grossly underpaid by the service. Does Spotify in fact shortchange performers to maximize profits? Not according to Messrs. Carlsson and Leijonhufvud, who claim that the labels, with their fat Spotify sinecures, choose to hoard the revenues (70 cents of every dollar Spotify makes is paid to master and publishing owners).

Link to the rest at The Wall Street Journal (PG apologizes for the paywall, but hasn’t figured out a way around it.)

PG notes that the music business exploits its creators just as much as the traditional publishing industry exploits its creators.

PG also notes that, in it’s infinite marketing wisdom, the publisher has not enabled Look Inside, but the links take you to Amazon for a preorder. Given the price, you can expect pirated versions of the ebook to appear shortly.

Did a Person Write This Headline, or a Machine?

From Wired:

The tech industry pays programmers handsomely to tap the right keys in the right order, but earlier this month entrepreneur Sharif Shameem tested an alternative way to write code.

First he wrote a short description of a simple app to add items to a to-do list and check them off once completed. Then he submitted it to an artificial intelligence system called GPT-3 that has digested large swaths of the web, including coding tutorials. Seconds later, the system spat out functioning code. “I got chills down my spine,” says Shameem. “I was like, ‘Woah something is different.’”

GPT-3, created by research lab OpenAI, is provoking chills across Silicon Valley. The company launched the service in beta last month and has gradually widened access. In the past week, the service went viral among entrepreneurs and investors, who excitedly took to Twitter to share and discuss results from prodding GPT-3 to generate memes, poems, tweets, and guitar tabs.

The software’s viral moment is an experiment in what happens when new artificial intelligence research is packaged and placed in the hands of people who are tech-savvy but not AI experts. OpenAI’s system has been tested and feted in ways it didn’t expect. The results show the technology’s potential usefulness but also its limitations—and how it can lead people astray.

. . . .

Other experiments have explored more creative terrain. Denver entrepreneur Elliot Turner found that GPT-3 can rephrase rude comments into polite ones—or vice versa to insert insults. An independent researcher known as Gwern Branwen generated a trove of literary GPT-3 content, including pastiches of Harry Potter in the styles of Ernest Hemingway and Jane Austen. It is a truth universally acknowledged that a broken Harry is in want of a book—or so says GPT-3 before going on to reference the magical bookstore in Diagon Alley.

Have we just witnessed a quantum leap in artificial intelligence? When WIRED prompted GPT-3 with questions about why it has so entranced the tech community, this was one of its responses:

“I spoke with a very special person whose name is not relevant at this time, and what they told me was that my framework was perfect. If I remember correctly, they said it was like releasing a tiger into the world.”

The response encapsulated two of the system’s most notable features: GPT-3 can generate impressively fluid text, but it is often unmoored from reality.

. . . .

When a WIRED reporter generated his own obituary using examples from a newspaper as prompts, GPT-3 reliably repeated the format and combined true details like past employers with fabrications like a deadly climbing accident and the names of surviving family members. It was surprisingly moving to read that one died at the (future) age of 47 and was considered “well-liked, hard-working, and highly respected in his field.”

. . . .

Francis Jervis, founder of Augrented, which helps tenants research prospective landlords, has started experimenting with using GPT-3 to summarize legal notices or other sources in plain English to help tenants defend their rights. The results have been promising, although he plans to have an attorney review output before using it, and says entrepreneurs still have much to learn about how to constrain GPT-3’s broad capabilities into a reliable component of a business.

More certain, Jervis says, is that GPT-3 will keep generating fodder for fun tweets. He’s been prompting it to describe art house movies that don’t exist, such as a documentary in which “werner herzog [sic] must bribe his prison guards with wild german ferret meat and cigarettes.” “The sheer Freudian quality of some of the outputs is astounding,” Jervis says. “I keep dissolving into uncontrollable giggles.”

Link to the rest at Wired

Algorithms Could Save Book Publishing—But Ruin Novels

From Wired:

Jodie Archer had always been puzzled by the success of The Da Vinci Code. She’d worked for Penguin UK in the mid-2000s, when Dan Brown’s thriller had become a massive hit, and knew there was no way marketing alone would have led to 80 million copies sold. So what was it, then? Something magical about the words that Brown had strung together? Dumb luck? The questions stuck with her even after she left Penguin in 2007 to get a PhD in English at Stanford. There she met Matthew L. Jockers, a cofounder of the Stanford Literary Lab, whose work in text analysis had convinced him that computers could peer into books in a way that people never could.

Soon the two of them went to work on the “bestseller” problem: How could you know which books would be blockbusters and which would flop, and why? Over four years, Archer and Jockers fed 5,000 fiction titles published over the last 30 years into computers and trained them to “read”—to determine where sentences begin and end, to identify parts of speech, to map out plots. They then used so-called machine classification algorithms to isolate the features most common in bestsellers.

The result of their work—detailed in The Bestseller Code, out this month—is an algorithm built to predict, with 80 percent accuracy, which novels will become mega-bestsellers. What does it like? Young, strong heroines who are also misfits (the type found in *The Girl on the Train, Gone Girl, *and The Girl with the Dragon Tattoo). No sex, just “human closeness.” Frequent use of the verb “need.” Lots of contractions. Not a lot of exclamation marks. Dogs, yes; cats, meh. In all, the “bestseller-ometer” has identified 2,799 features strongly associated with bestsellers.

What Archer and Jockers have done is just one part of a larger movement in the publishing industry to replace gut instinct and wishful thinking with data. A handful of startups in the US and abroad claim to have created their own algorithms or other data-driven approaches that can help them pick novels and nonfiction topics that readers will love, as well as understand which books work for which audiences. Meanwhile, traditional publishers are doing their own experiments: Simon & Schuster hired its first data scientist last year; in May, Macmillan Publishers acquired the digital book publishing platform Pronoun, in part for its data and analytics capabilities.

While these efforts could bring more profit to an oft-struggling industry, the effect for readers is unclear.

“Part of the beautiful thing about books, unlike refrigerators or something, is that sometimes you pick up a book that you don’t know,” says Katherine Flynn, a partner at Boston-based literary agency Kneerim & Williams. “You get exposed to things you wouldn’t have necessarily thought you liked. You thought you liked tennis, but you can read a book about basketball. It’s sad to think that data could narrow our tastes and possibilities.”

They Know What You Did Last Night

Once, publishers had to rely on unit sales to figure out what readers wanted. Digital reading changed that. Publishers can know that you raced through a novel to the end, or that you abandoned it after 20 pages. They can know where and when you’re reading. On some reading sites and apps, users sign in with their Facebook accounts, opening up more personal data. There’s a wrinkle, though: Companies such as Amazon and Apple have the data for books read on their devices, and they aren’t sharing it with publishers.

London-based startup Jellybooks offers a workaround. Publishers can hire Jellybooks to conduct virtual focus groups, giving readers free ebooks, often in advance of publication, in exchange for their sharing data on how much, when, and where they read. Javascript is embedded in the books, and at the end of each chapter, readers are asked to click a link that sends the data to Jellybooks. In almost two years, the company has run tests for publishers in the US, England, and Germany, and uncovered one sobering fact: Most novels are abandoned before readers are halfway through them. Jellybooks’s findings can guide publishers on their marketing, and even whether it’s worth signing an author again. “Hollywood moguls might do test screenings for movies to decide on how much [marketing] budget a movie should get,” says Andrew Rhomberg, the founder of Jellybooks. “That was never done for books.”

The ability to know who reads what and how fast is also driving Berlin-based startup Inkitt. Founded by Ali Albazaz, who started coding at age 10, the English-language website invites writers to post their novels for all to see. Inkitt’s algorithms examine reading patterns and engagement levels. For the best performers, Inkitt offers to act as literary agent, pitching the works to traditional publishers and keeping the standard 15 percent commission if a deal results. The site went public in January 2015 and now has 80,000 stories and more than half a million readers around the world.

Albazaz, now 26, sees himself as democratizing the publishing world. “We never, ever, ever judge the books. That’s not our job. We check that the formatting is correct, the grammar is in place, we make sure that the cover is not pixelated,” he says. “Who are we to judge if the plot is good? That’s the job of the market. That’s the job of the readers.”

. . . .

The Data Scare

As Archer and Jocker shopped the *Bestseller Code *manuscript to acquisitions editors, word of their powerful algorithm spread—as did worry and suspicion among those in the publishing profession. “The fear is we can homogenize the market or try and somehow take their jobs away from them, and the answer is no and no,” says Archer. “What the bestseller-ometer is trying to do is say, ‘Hey, pick this new author that you might not dare take a risk on with your acquisitions budget. Their chance is really good.’” Archer, now a writer in Boulder, Colorado, insists that she and Jockers, now an English professor at the University of Nebraska-Lincoln, are “literature-friendly” and want good books to succeed.

Andrew Weber, the global chief operating officer for Macmillan Publishers—whose St. Martin’s Press is publishing *The Bestseller Code—thinks algorithms should be viewed as an additional piece of information, rather than as an excuse to fire the editors. “Whether it’s in acquisition, whether it’s in pricing, whether it’s in marketing, whether it’s in distribution, there just seem to be many, many, many opportunities to improve the quality of our decision-makingand therefore hopefully our results—*by bringing data into the equation,” says Weber. “I would say we are still in the early days of that journey, but that’s the direction we’re headed.”

Archer and Jockers watched eagerly to see which novel would be their algorithm’s favorite. It turned out to be The Circle, a 2013 technothriller by Dave Eggers about working for a massively powerful Internet company. The Circle spent multiple weeks on both The New York Times hardcover fiction and paperback trade fiction bestseller lists. A movie version starring Emma Watson and Tom Hanks is expected in theaters this year.

Link to the rest at Wired

It appears that PG missed this when it first appeared in 2016.

He suspects the almost-universal phobia towards computers, algorithms, quantitative analysis, sophisticated metrics, etc., among the indwellers of traditional publishing is related to the widespread incidence of innumeracy among English majors.

Worship of The Golden Gut is the state religion of this group. For them, no collection of numbers and formulae can ever replace The Hunch. That’s one reason why so many books fail to earn out their advances, how many mega-sellers are first rejected by every major publisher before stumbling into the market and finding success.

Indie authors include a much wider slice of humanity than either publishers or traditionally-published authors. That diversity of talent and background combined with Amazon’s relentless pursuit of customers and, thus, numbers, analytics, categories, sub-categories and sub-sub categories fosters the creation of niches within niches all the way down to the micro-reader level.

PG just checked a random book on the Zon and discovered that it encouraged drill-down and discovery as follows:

Books
* Mystery, Thriller & Suspense
*Thrillers & Suspense
* Suspense

With broad categories mentioned:

Book Fiction Moods

Book Mystery Characters

Some Authors:

Author

(PG is not certain how much of this collection of information is presented as result of PG’s and Mrs. PG’s past buying habits.)

Finally, if you prefer, you could check out 383 different categories, series, spinoffs, heroes/heroines, etc., etc., etc., (including, 盗墓笔记, El cementerio de los libros, Svartåsen and Die Krimi-Serie in den Zwanzigern as follows:

1900-Zombie-Thriller (1)
2A Cotten Stone Mystery (1)
3A Department Q Novel (1)
4A Jonathan Grave Thriller (2)
5A Topsail Island novel (1)
6Aaron Falk (2)
7Against Series / Raines of Wind Canyon (1)
8Agatha Raisin Sammelband (1)
9Agent Juliet (1)
10Agent Pendergast (4)
11Alex Cross (4)
12Alex Delaware (13)
13Alex Devlin (1)
14Alex Hawke (6)
15Alex McKnight (1)
16Alexandra Cooper (5)
17Alfonzo (1)
18Ali Reynolds Series (15)
19All Souls Trilogy (1)
20Allison McNeil Series (1)
21Alo Nudger (1)
22Amos Decker (5)
23An Elvis Cole Novel (3)
24An FBI Thriller (1)
25An Isaiah Coleridge Novel (1)
26An Under Suspicion Novel (1)
27Anderswelt John Sinclair Spin-off (18)
28Andreas Gruber Erzählbände (1)
29Anna Pigeon Mysteries (1)
30Annie Carter Series (3)
31Ash Henderson (2)
32Asher Benson (1)
33Auftrag: Mord! (3)
34Beartooth, Montana (1)
35Ben Abbott Mysteries (1)
36Ben Hope (20)
37Blood on Snow (2)
38Bob Lee Swagger Novels (4)
39Breaking Free (1)
40Camel Club (2)
41Cape Charade (3)
42Carl Mørck (1)
43Carriage House (5)
44Carson Ryder (9)
45Casey Woods (1)
46Cat Who… (1)
47Cate Austin (1)
48Charlie Chan Mystery (1)
49Chefinspektor Tony Braun (2)
50Cherokee Pointe (1)
51Chet and Bernie Mystery (16)
52Chronicles of The One (7)
53Cold Justice (1)
54Commandant Martin Servaz (1)
55Commissario Brunetti (8)
56Conrad Yeats Adventure (1)
57Cork O’Connor (17)
58Cork O’Connor Mystery Series (12)
59Cotton Malone (2)
60Covert-One (1)
61Crissa Stone (1)
62Cutler (2)
63D.I. Callanach (1)
64Dagny Gray (1)
65Dalziel & Pascoe (1)
66Dalziel and Pascoe (14)
67盗墓笔记 (1)
68Dark Iceland (1)
69Dave Gurney (1)
70Dave Robicheaux (8)
71David Stein (1)
72David Wolf (1)
73DCI Matilda Darke (1)
74Dead series (1)
75Detective Erika Foster (2)
76Detective Josie Quinn (2)
77Detective Mark Heckenburg (3)
78Detective Max Rupert (2)
79Detektei Lessing Kriminalserie (3)
80DI Fawley (2)
81Die ARES-Reihe (2)
82Die Cormoran-Strike-Reihe (1)
83Die Dead-Silencer-Saga (1)
84Die Irene-Huss-Krimis (1)
85Die Krimi-Serie in den Zwanzigern (23)
86Dirk Pitt (1)
87Dismas Hardy (15)
88Divine (1)
89Dr. Lazlo Kreizler (1)
90Dr. Marissa Blumenthal (1)
91Dr. Samantha Owens series (1)
92Drake Ramsey (2)
93DS Heckenburg (6)
94DS Imogen Grey (2)
95Dunkle Begierde (1)
96Dynam (1)
97Ed Eagle Novel (2)
98Ein Fall für Engel und Sander (2)
99Ein FBI Thriller mit Dillon Savich und Lacey Sherlock (3)
100Ein Jack-Reacher-Roman (1)
101Ein Mike-Köstner-Thriller (1)
102El cementerio de los libros olvidados (1)
103EL SECRETO DE LOS ARTISTAS (1)
104Emma Fern (4)
105Enrico Mancini (2)
106Essex Witch Museum Mystery (2)
107Eve Diamond Mystery (1)
108Eve Duncan (2)
109Event Group Thriller (1)
110Fatal Insomnia Medical Thrillers (6)
111FBI Profiler (1)
112Final Theory (1)
113Fiona Griffiths Crime Thriller Series (1)
114Forensic Instincts (1)
115Fort Aldamo (57)
116Frank Wallerts Fälle (7)
117Frankenstein (1)
118Franz Eberhofer (3)
119G. F. Unger Sonder-Edition (102)
120G.F. Unger Classic-Edition (11)
121Gabriel Allon (1)
122Geisterjäger John Sinclair (6)
123Gideon Crew (2)
124Giordano Bruno (1)
125Go-get-’em Women (1)
126Good Lawyer (3)
127Grant County (3)
128Graveyard Falls (1)
129Griffin Powell (1)
130Guardian (1)
131Hackberry Holland (3)
132Harrison Investigation (2)
133Harry Bosch (4)
134Harry Palmer (1)
135Hart and Drake (8)
136Hector Cross Series (1)
137Hercule Poirot (20)
138High Country Heroes (2)
139Hold On! (1)
140Holly Barker (1)
141Honeymoon Series James Patterson (1)
142I Heart (1)
143If I Run (4)
144In Death (2)
145Inspector Barbarotti (2)
146Inspector Lynley (3)
147Inspector Montalbano (2)
148Inspector Montalbano Mysteries (1)
149IQ (1)
150Iron Lace (1)
151Isas Requiem (1)
152Jack Noble (1)
153Jack Paris (1)
154Jack Reacher (2)
155Jack Sigler Thrillers (Chess Team) (1)
156Jack Stapleton & Laurie Montgomery series (1)
157Jacqueline Kirby (1)
158Jake Brigance (7)
159Jake Ransom (1)
160James Blake (2)
161Jane Harper Horror Novels (2)
162Jane Hawk (2)
163Jericho Quinn Thriller (8)
164Jerry Cotton Sammelband (5)
165Jerry Cotton Sammelbände (14)
166Jerry Cotton Sonder-Edition (84)
167Jerry Cotton Sonder-Edition Sammelbände (3)
168Jet (4)
169Joanna Stafford (1)
170Joe Dillard Series (1)
171Joe Pickett Series (2)
172Joe Pike series (1)
173Joe Sixsmith (3)
174Johannes-Hornoff-T… (1)
175John Reeves (2)
176John Sinclair Collection (18)
177John Sinclair Gespensterkrimi (1)
178John Sinclair Gespensterkrimi Collection (9)
179John Sinclair Großband (13)
180John Sinclair Sammelband (8)
181John Sinclair Sonder-Edition (67)
182John Sinclair Sonder-Edition Sammelband (7)
183Joona Linna (2)
184Judith Kepler (1)
185Jungle Beat (7)
186Karin Slaughter Thriller-Bundle (2)
187Kate Brannigan (4)
188Kate Ivory (14)
189Kate Maddox (2)
190Kathryn-Dance-Thri… (1)
191Kay Scarpetta (11)
192Kick Lannigan (2)
193Kimmo-Joentaa-Reihe (1)
194King and Maxwell (9)
195Kirstmann und Freytag (1)
196Kitt Lundgren (1)
197Kolt Raynor (1)
198Lassiter 2101-2200 (3)
199Lassiter 2201-2300 (10)
200Last Option Search Team (3)
201Last Stand (1)
202Leo Demidow (1)
203Leverage (2)
204Liam Devlin series (1)
205Lizzie Martin (2)
206Logan McRae (5)
207Logan McRae Collection (2)
208Louis Kincaid (1)
209Louise Rick series (2)
210Lucy Clayburn (3)
211Lucy Guardino FBI Thrillers (3)
212luebbe digital ebook (5)
213Luke Carlton (1)
214Luna Maiwald Rügenkrimi (1)
215Maddrax (4)
216Marc Dane (1)
217Marcus (1)
218Maura Ryan (2)
219Maximum Ride: The Manga (2)
220Maximum Security (1)
221Medical Thrillers (Gerritsen) (1)
222Mercy Kilpatrick (1)
223Mia Quinn (1)
224Michael Bennett (3)
225Michael Herne (1)
226Midwife (2)
227Miss Marple Mysteries (1)
228Mississippi (2)
229Mitchell & Associates (4)
230Monster Hunter International (1)
231Nameless Detective (3)
232Natalie King, Forensic Psychiatrist (1)
233Nick Hall (2)
234Night Soldiers (1)
235Nils Trojan (1)
236Nomad (1)
237NYPD Red (2)
238Odd Thomas (2)
239Operation: Midnight (1)
240OPSIG Team Black Series (1)
241P.I.D. (2)
242Penn Cage Novels (2)
243Peter Decker & Rina Lazarus (4)
244Peter Decker/Rina Lazarus (4)
245Petra Connor (1)
246Pilgrim (3)
247Predator & Prey (1)
248Prey (5)
249Privatdetektiv Marten Hendriksen (1)
250Private (2)
251Promise Falls Trilogy (1)
252Raines of Wind Canyon (2)
253Random House Large Print (3)
254Relatively Dead Mysteries (1)
255Richard “Dick” Moonlight (1)
256Rizzoli-&-Isles-Serie (2)
257Robert Langdon (1)
258Robicheaux (7)
259Rocky Mountain Bounty Hunters (1)
260Rocky Mountain K9 Unit (4)
261Ryan Archer (1)
262Sakura Warrior – Reihe (1)
263Sally Harrington (1)
264Sam Berger Series (1)
265Sam Capra Mysteries (2)
266Samson (1)
267San Francisco (1)
268Sandhamn Murders (2)
269Sanela Beara (1)
270Sarah Pauli (2)
271Scarlet Falls (1)
272Scope (2)
273Sean Dillon (5)
274Search and Rescue (4)
275Second Opportunities (1)
276Selena Alvarez/Regan Pescoli (1)
277Shane Schofield (1)
278Sharon McCone (3)
279Sharpe & Donovan (2)
280Shaw and Katie James (7)
281Sigma Force (7)
282Simon Vaughn (2)
283Sisterhood (3)
284Six Stories (2)
285Skink (1)
286Smoky Barrett (3)
287Smoky Barrett Sammelband (1)
288Soko Hamburg – Ein Fall für Heike Stein (18)
289Sonderermittler der Krone (5)
290Spilling CID (1)
291Split Second (1)
292Stalking Jack the Ripper (1)
293Stephanie Plum (4)
294Stephanie Plum Between the Numbers/Holiday Novels (1)
295Stillhouse Lake (6)
296Stone Barrington (7)
297Stranger Things Novels (2)
298Superintendent Battle (4)
299Svartåsen (1)
300Talisman (5)
301Tall, Dark & Dangerous (1)
302Temperance Brennan (6)
303Teodor Szacki (2)
304Texas Rangers (2)
305Texas Trilogy (2)
306The Annie Graham series (1)
307The Avalon Chronicles (3)
308The Awakening Series (1)
309The Bening Files (2)
310The Bill Hodges Trilogy (3)
311The Blaine Trilogy (1)
312The Butlers (6)
313The Cal O’Connor Series (1)
314The Cards in the Deck (2)
315The Cat Who… (23)
316The Cemetery of Forgotten Series (1)
317The China Thrillers (3)
318The Clifton Chronicles (10)
319The Color of Distance (1)
320The Commandant Camille Verhoeven Trilogy (2)
321The Cooper & Fry Series (1)
322The Cousins War (4)
323The Dark Iceland Series (1)
324The Dark Tower (6)
325The Death Trilogy (3)
326The End Series (1)
327The Flovent and Thorson Thrillers (1)
328The Immune (4)
329The Kate Lange Thriller Series (2)
330The Keepers (3)
331The Men Of The Sisterhood (1)
332The Mitch Rapp Prequel Series (8)
333The Mitch Rapp Series (31)
334The Oxygen Thief Diaries (2)
335The Paul Chavasse Novels (2)
336The Pieter Van In Mysteries (1)
337The Psychic Detectives Series (1)
338The Restoration Series (5)
339The Retreat (2)
340The Roth Trilogy (3)
341The Sara Winthrop Thriller Series (1)
342The Scot Harvath Series (45)
343The Sean Coleman Thriller series (1)
344The Talisman (5)
345The Tallow Series (1)
346The Warm Bodies Series (1)
347Thomas Eickhoff ermittelt (1)
348Thomas Kell (3)
349Thomas Knight (1)
350Tina Boyd (5)
351Todeslächeln (2)
352Tom Thorne (2)
353Tom Thorne series (1)
354Tommy and Tuppence (6)
355Tracers Series (1)
356Troubleshooters (1)
357Turbulent Desire Series (2)
358Twin Ports (1)
359Ty Hauck (3)
360Under Suspicion (1)
361Undercover Cops (1)
362Unit 51 (1)
363V.I. Warshawski Novels (2)
364Vampire Chronicles (1)
365Vampire Federation (1)
366Vintage Contemporaries (1)
367Virgil Flowers (1)
368Wayward Pines (6)
369Wegner & Hauser – Hamburg: Mord (2)
370Wegners erste Fälle (8)
371Wegners schwerste Fälle (9)
372Will Lee Novels (1)
373Will Robie (2)
374Will Trent/Atlanta Series (1)
375Will-Trent-Serie (1)
376William Sandberg (1)
377Wired (2)
378Wired & Dangerous (1)
379Wishbone (1)
380Women’s Murder Club (9)
381World War I (1)
382World’s Scariest Places Occult & Supernatural Crime Series (7)
383Wyman Ford (7)

Communication Re-Imagined with Emotion Ai

From ReadWrite:

There has long been a chasm between what we perceive artificial intelligence to be and what it can actually do. Our films, literature, and video game representations of “intelligent machines,” depict AI as detached but highly intuitive interfaces. We will find communication re-imagined with emotion AI.

. . . .

As these artificial systems are being integrated into our commerce, entertainment, and logistics networks, we are witnessing emotional intelligence. These smarter systems have a better understanding of how humans feeland why they feel that way.

The result is a “re-imagining” of how people and businesses can communicate and operate. These smart systems are drastically improving the voice user interface of voice-activated systems in our homes. AI is improving not only facial recognition but changing what is done with that data.

. . . .

Humans use thousands of subverbal cues when they communicate. The tone of their voice, the speed at which someone speaks– these are all hugely important parts of a conversation but aren’t part of the “raw data” of that conversation.

New systems designed to measure these verbal interactions are now able to look at emotions like anger, fear, sadness, happiness, or surprise based on dozens of metrics related to specific cues and expressions. Algorithms are being trained to evaluate the minutia of speech in relation to one another, building a map of how we read each other in social situations.

Systems are increasingly able to analyze the subtext of language based on the tone, volume, speed, or clarity of what is being said. Not only does this help these systems to identify the gender and age of the speaker better, but they are growing increasingly sophisticated in recognizing when someone is excited, worried, sad, angry, or tired. While real-time integration of these systems is still in development, voice analysis algorithms are better able to identify critical concerns and emotions as they get smarter.

. . . .

The result of this is a striking uptick in the ability of artificial intelligence to replicate a fundamental human behavior. We have Alexa developers actively working to teach the voice assistant to hold conversations that recognize emotional distress, the US Government using tone detection technology to detect the symptoms and signs of PTSD in active duty soldiers and veterans and increasingly advanced research into the impact of specific physical ailments like Parkinson’s on someone’s voice.

While done at a small scale, it shows that the data behind someone’s outward expression of emotion can be cataloged and used to evaluate their current mood.

Link to the rest at ReadWrite

Barnes & Noble Takeover Shows Retail Theme Is Technology Change

From Seeking Alpha:

  • Takeover of Barnes & Noble highlights the importance of technology change in media retailing.
  • Lessons from Borders and Blockbuster bankruptcies are still relevant.
  • Loyal customer base supports ongoing Barnes & Noble mall presence.

Barnes & Noble, largest US book retailer with a total of 620 stores, announced plans this month to be acquired by Elliott Management (a $34 billion New York private equity hedge fund) for $683 million (including transfer of debt),

. . . .

The important benefit of this takeover for Barnes & Noble shareholders (as well as Barnes & Noble’s landlords, the Retail REITs) is that this is a takeover in anticipation of a turnaround. Elliott Management also owns UK book retailer Waterstones and plans to put Waterstones successful CEO, John Daunt, in charge of both companies. It appears that Barnes & Noble has found a good home.

With 627 Barnes & Noble stores in the US and 280 Waterstones locations in UK, Elliott Management is facing off against Amazon, online juggernaut that is believed to sell as much as 50% of all new hard copy books as well as a large share of e-books and used books. Barnes & Noble has a successful website allowing loyal customers to purchase books, movies, music, toys, and games, but cannot compete with Amazon in size or selection, customer history or ability to take advantage of cross-selling and financing opportunities.

Still, Barnes & Noble knows their customer base well, having used loyalty programs to reach out to their frequent shoppers and should be able to take advantage of their friendly environment for book lovers at well-established stores. I think we won’t see many Barnes & Noble stores close, at least not at first; we are far more likely to see discounting and special offers at Barnes & Noble. Customers should feel upgraded.

. . . .

Although the greatest threat to Barnes & Noble’s future remains Amazon (both for online sales of hard copy books and e-books sold on Nook), I think the true threat is technology change, as we have seen over the past 12 years of change in the way media is delivered and consumed by today’s shoppers. These 2 retail failures – Blockbuster Video and Borders – still have something to tell us about current retail challenges.

Link to the rest at Seeking Alpha

The Rise of Robot Authors: Is the Writing on the Wall for Human Novelists?

From The Guardian:

Will androids write novels about electric sheep? The dream, or nightmare, of totally machine-generated prose seemed to have come one step closer with the recent announcement of an artificial intelligence that could produce, all by itself, plausible news stories or fiction. It was the brainchild of OpenAI – a nonprofit lab backed by Elon Musk and other tech entrepreneurs – which slyly alarmed the literati by announcing that the AI (called GPT2) was too dangerous for them to release into the wild, because it could be employed to create “deepfakes for text”. “Due to our concerns about malicious applications of the technology,” they said, “we are not releasing the trained model.” Are machine-learning entities going to be the new weapons of information terrorism, or will they just put humble midlist novelists out of business?

. . . .

GPT2 is just using methods of statistical analysis, trained on huge amounts of human-written text – 40GB of web pages, in this case, that received recommendations from Reddit readers – to predict what ought to come next. This probabilistic approach is how Google Translate works, and also the method behind Gmail’s automatic replies (“OK.” “See you then.” “That’s fine!”) It can be eerily good, but it is not as intelligent as, say, a bee.

Right now, novelists don’t seem to have much to fear. Fed the opening line of George Orwell’s Nineteen Eighty-Four – “It was a bright cold day in April, and the clocks were striking thirteen” – the machine continued the narrative as follows: “I was in my car on my way to a new job in Seattle. I put the gas in, put the key in, and then I let it run. I just imagined what the day would be like. A hundred years from now. In 2045, I was a teacher in some school in a poor part of rural China. I started with Chinese history and history of science.”

. . . .

Did the AI do any better with Jane Austen? The opening phrase of Pride and Prejudice – “It is a truth universally acknowledged” – provoked the machine to gabble on: “that when a nation is in a condition of civilization, that it is in a great measure the business of its leaders to encourage the habits of virtue, and of industry, and of good order among its people.” This does sound rather like some 19th-century political bloviator, even if a slightly broken version. (The second “that” is redundant, and it should read “in great measure” without the indefinite article.)

. . . .

Is there greater cause to worry further down the literary food chain? There have for a while already been “AI bots” that can, we hear, “write” news stories. All these are, though, are giant automated plagiarism machines that mash together bits of news stories written by human beings. As so often, what is promoted as a magical technological advance depends on appropriating the labour of humans, rendered invisible by AI rhetoric. When a human writer commits plagiarism, that is a serious matter. But when humans get together and write a computer program that commits plagiarism, that is progress.

. . . .

The makers’ announcement that this program is too dangerous to be released is excellent PR, then, but hardly persuasive. Such code, OpenAI warns, could be used to “generate misleading news articles”, but there is no shortage of made-up news written by actual humans working for troll factories. The point of the term “deepfakes” is that they are fakes that go deeper than prose, which anyone can fake. Much more dangerous than disinformation clumsily written by a computer are the real “deepfakes” in visual media that respectable researchers are eagerly working on right now. When video of any kind can be generated that is indistinguishable from real documentary evidence – so that a public figure, for example, can be made to say words they never said – then we’ll be in a world of trouble.

. . . .

Perhaps a more realistic hope for a text-only program such as GPT2, meanwhile, is simply as a kind of automated amanuensis that can come up with a messy first draft of a tedious business report – or, why not, of an airport thriller about famous symbologists caught up in perilous global conspiracy theories alongside lissome young women half their age. There is, after all, a long history of desperate artists trying rule-based ruses to generate the elusive raw material that they can then edit and polish. The “musical dice game” attributed to Mozart enabled fragments to be combined to generate innumerable different waltzes, while the total serialism of mid-20th‑century music was an algorithmic approach that attempted as far as possible to offload aesthetic judgments by the composer on to a system of mathematical manipulations.

. . . .

But until robots have rich inner lives and understand the world around them, they won’t be able to tell their own stories. And if one day they could, would we even be able to follow them? As Wittgenstein observed: “If a lion could speak, we would not understand him”. Being a lion in the world is (presumably) so different from being a human in the world that there might be no points of mutual comprehension at all. It’s entirely possible, too, that if a conscious machine could speak, we wouldn’t understand it either.

Link to the rest at The Guardian

PG says, “We have a lot of rain in June. Is the buzz dead better than the couple? The maddening kill crawls into the wealthy box. When does the zesty liquid critique the representative?”

(PG’s comments are courtesy of Random Word Generator, TextFixer and Word Generator.

And also:

After leaving the crumpled planet Abydos, a group of girls fly toward a distant speck. The speck gradually resolves into a contented, space tower.

Civil war strikes the galaxy, which is ruled by Brad Willis, a derelict wizard capable of lust and even murder.

Terrified, an enchanted alien known as Michelle Thornton flees the Empire, with her protector, Chloe Noris.

They head for Philadelphia on the planet Saturn. When they finally arrive, a fight breaks out. Noris uses her giant knife to defend Michelle.

(Plot Generator)

Finally, a blurb for a romance novel:

In this story, a serene police chief ends up on the run with a realistic witch-hunter. What starts as professional courtesy unexpectedly turns into a passionate affair.

(Seventh Sanctum)

Click here, then click the Play button to listen to the blurb

(Natural Readers)

Our Software Is Biased like We Are. Can New Laws Change That?

From The Wall Street Journal:

Lawyers for Eric Loomis stood before the Supreme Court of Wisconsin in April 2016, and argued that their client had experienced a uniquely 21st-century abridgment of his rights: Mr. Loomis had been discriminated against by a computer algorithm.

Three years prior, Mr. Loomis was found guilty of attempting to flee police and operating a vehicle without the owner’s consent. During sentencing, the judge consulted COMPAS (aka Correctional Offender Management Profiling for Alternative Sanctions), a popular software system from a company called Equivant. It considers factors including indications a person abuses drugs, whether or not they have family support, and age at first arrest, with the intent to determine how likely someone is to commit a crime again.

The sentencing guidelines didn’t require the judge to impose a prison sentence. But COMPAS said Mr. Loomis was likely to be a repeat offender, and the judge gave him six years.

An algorithm is just a set of instructions for how to accomplish a task. They range from simple computer programs, defined and implemented by humans, to far more complex artificial-intelligence systems, trained on terabytes of data. Either way, human bias is part of their programming. Facial recognition systems, for instance, are trained on millions of faces, but if those training databases aren’t sufficiently diverse, they are less accurate at identifying faces with skin colors they’ve seen less frequently. Experts fear that could lead to police forces disproportionately targeting innocent people who are already under suspicion solely by virtue of their appearance.

. . . .

No matter how much we know about the algorithms that control our lives, making them “fair” may be difficult or even impossible. Yet as biased as algorithms can be, at least they can be consistent. With humans, biases can vary widely from one person to the next.

As governments and businesses look to algorithms to increase consistency, save money or just manage complicated processes, our reliance on them is starting to worry politicians, activists and technology researchers. The aspects of society that computers are often used to facilitate have a history of abuse and bias: who gets the job, who benefits from government services, who is offered the best interest rates and, of course, who goes to jail.

“Some people talk about getting rid of bias from algorithms, but that’s not what we’d be doing even in an ideal state,” says Cathy O’Neil, a former Wall Street quant turned self-described algorithm auditor, who wrote the book “Weapons of Math Destruction.”

“There’s no such thing as a non-biased discriminating tool, determining who deserves this job, who deserves this treatment. The algorithm is inherently discriminating, so the question is what bias do you want it to have?” she adds.

. . . .

An increasingly common algorithm predicts whether parents will harm their children, basing the decision on whatever data is at hand. If a parent is low income and has used government mental-health services, that parent’s risk score goes up. But for another parent who can afford private health insurance, the data is simply unavailable. This creates an inherent (if unintended) bias against low-income parents, says Rashida Richardson, director of policy research at the nonprofit AI Now Institute, which provides feedback and relevant research to governments working on algorithmic transparency.

The irony is that, in adopting these modernized systems, communities are resurfacing debates from the past, when the biases and motivations of human decision makers were called into question. Ms. Richardson says panels that determine the bias of computers should include not only data scientists and technologists, but also legal experts familiar with the rich history of laws and cases dealing with identifying and remedying bias, as in employment and housing law.

Link to the rest at The Wall Street Journal

Boom Time for Used Booksellers?

As PG was opening a couple of packages of hardcopy books for Mrs. PG (she does read a lot of ebooks, but, in some cases, used books are less expensive and some books she wants in hardcopy to share with family and/or friends), it occurred to him that Amazon has almost certainly given used booksellers an opportunity to reach a far wider group of prospective purchasers than were ever available to them in physical used bookstores.

Most of the hardcopy used books that arrive in the mail come well-packaged and most are clearly packed by more sophisticated equipment than a roll of stamps and a stack of envelopes.

So, is PG correct about Amazon and used booksellers?

Has the ability to sell to a much wider online audience affected the pricing of used books?

Has the used book business undergone consolidation with small used bookstores closing and selling their inventory to large, online-focused used booksellers?

Are there people who are paid by larger used booksellers to be scouts for large quantities of available used books?

Real-Time Continuous Transcription with Live Transcribe

Not necessarily to do with books, but two of PG’s offspring are hearing-impaired, so he follows topics like this. He’s also interested in developments in artificial intelligence, so it’s a double win for him.

From The Google AI Blog:

The World Health Organization (WHO) estimates that there are 466 million people globally that are deaf and hard of hearing. A crucial technology in empowering communication and inclusive access to the world’s information to this population is automatic speech recognition (ASR), which enables computers to detect audible languages and transcribe them into text for reading. Google’s ASR is behind automated captions in Youtube, presentations in Slides and also phone calls. However, while ASR has seen multiple improvements in the past couple of years, the deaf and hard of hearing still mainly rely on manual-transcription services like CART in the US, Palantypist in the UK, or STTRin other countries. These services can be prohibitively expensive and often require to be scheduled far in advance, diminishing the opportunities for the deaf and hard of hearing to participate in impromptu conversations as well as social occasions. We believe that technology can bridge this gap and empower this community.

Today, we’re announcing Live Transcribe, a free Android service that makes real-world conversations more accessible by bringing the power of automatic captioning into everyday, conversational use. Powered by Google Cloud, Live Transcribe captions conversations in real-time, supporting over 70 languages and more than 80% of the world’s population. You can launch it with a single tap from within any app, directly from the accessibility icon on the system tray.

Link to the rest at The Google AI Blog

 

The Future of Music, Where Middlemen Have Met Their Match

From OZY:

“Hey, Dad. I want to show you a song.”

The speaker was my 16-year-old daughter. Music for her? Primarily visual and to be enjoyed in video clips. Video clips that did not always feature videos. Sometimes it was just some clip art and the music. But no record store, no record album, no tape — reel-to-reel, eight track, cassette or otherwise — and finally no compact disc. And she’s not alone in how she’s digging on the music she digs on.

According to Nielsen’s music report, digital and physical album sales declined (again) last year — from about 205 million in 2016 to 169 million copies in 2017 — down 17 percent. Over the past five years, right up to Nielsen’s mid-year report, sales had fallen by roughly 75 percent. That decline is coinciding with a streaming juggernaut that continues to grow. How much so? Last year streaming skated, quite easily, beyond 400 billion streams. You include video streams and you have figures over $618 billion. You look back at the year before and you see a 58 percent increase in audio streams.

While this buoyed the damned-near-moribund music industry to the tune of 12.5 percent growth from 2016 to last year, the music business is now, as it has been, all about discovering the music that can generate all of those streams. And that’s where things get curious because record labels that are used to creating heat now have to go places where the heat is being created to stay viable and vibrant.

. . . .

With a number of presently high-profile artists — Odd Future, Lil Yachty, Post Malone, etc. — being “discovered” on places like SoundCloud over the past five years, entire communities of music fans can beat both the hype and the Spotify/Pandora/SiriusXM radio/Amazon algorithms that suggest if you liked this, you might also like that, by starting there, and branching out. First stop: Instagram.

“People come in all the time and play me stuff from their IG feeds,” says Mark Thompson, founder of Los Angeles-based Vacation Vinyl (that sells, yes, primarily vinyl). “So I’m hearing bands that it soon becomes pretty clear have no label, no representation, nothing but an IG feed and maybe some music recorded on their laptops.”

To put this in perspective, in July 2018, Instagram added the music mode in Stories, and just that quickly streaming started to feel … old. Because from the musicians’ mouths to our ears, unmediated music finds its way from the creator to the consumer. Spotify is trying to adapt too — it has over the past year begun to sign deals with independent musicians to give them access to the platform.

. . . .

“It’s free,” she says, having endured speeches about listening to unpaid/stolen music. Since she and her friends don’t ever listen to more than 60 seconds of any song, at least while I am around, this raises the question: Is it a business and is it sustainable in the same way that Apple Music, Tidal, Deezer or iHeartRadio have managed to be?

“Unknown,” says former promoter and music industry executive Mark Weiss. “But the business is where the ears are. And if the business is any damn good it’ll figure out how to stay in the conversation.”

. . . .

Flash-forward to record contracts from the mid-1990s that covered cassette tapes, vinyl, compact discs and “future technologies not yet known.” The digitization of analog music had already changed the landscape for everything from crime to interior design.

Whereas previously you’d have needed a turntable, an amplifier, maybe a preamp, a tape player, a receiver, speakers and a subwoofer to listen to the music that you’d be playing off of tapes, vinyl or CDs, after everything was digitized you just needed a phone and speakers.

Link to the rest at OZY