A Ben Affleck flop inspired this script-reading robot

The process used to create a major motion picture hasn’t changed much in a century. Someone has an idea that they turn into a screenplay, which is then edited, developed and handed to a director, who brings it to life. The only difference now is that there’s plenty more focus-grouping, audience analysis and number crunching to ensure each film is a hit. Except that doesn’t really work, since 2016 alone has seen scores of movies unceremoniously crash and burn. But maybe that will change with ScriptBook, an algorithm that its creators say can spot most turkeys before they’ve even been made.

The Belgian startup was born out of one of Hollywood’s greatest catastrophes: the Ben Affleck–Jennifer Lopez train wreck Gigli. ScriptBook CEO Nadira Azermai was a college student when she got the chance to intern on the film for a couple of weeks. Inspired by the film’s failure, she wrote her thesis in applied economics on a way of using machine learning to develop a tool that would enable producers to avoid box office bombs. And then, in her own words, she “left it [the idea] in my bottom draw to go work for a bank” for a few years.

When she decided to revisit the idea, it took her (and her burgeoning team) a year of research and development. The finished product was ScriptBook, a machine-learning platform that — so Azermai claims — knows what makes a good screenplay. “In the first six months, we did a lot of exploration, taking 4,000 scripts and 10,000 movies with metadata to see what parameters came out,” she said. The result is an algorithm that knows what has worked before and can judge a screenplay against 220 parameters that are used to calculate its theoretical financial performance.

The sort of report a studio executive using ScriptBook could expect to receive.

Some of the insights were derived from common sense as well as the established “rules” of screenwriting sold by Robert Mckee, Syd Field and Blake Snyder. That means following Joseph Campbell’s monomyth structure, ensuring that your lead character is sympathetic and goes on a hero’s journey. But likability was a hard substance to quantify, and one that ScriptBook’s algorithm initially struggled with.

Azermai cited Die Hard as an example, since, on paper, “the lead character — he’s not a scumbag, but he’s an unlikeable, disgruntled cop.” So, to teach ScriptBook, “we hired people to annotate the data set and answer questions on if the main character was likable.” Once the system had looked at the human input, it can then classify these traits automatically, as is the case with most deep learning systems.

Scripbook isn’t about picking winners so much as it is about avoiding losers, which is a huge issue for even a big studio. “We did an impact analysis” on the slate of major studio movies released in 2014 and 2015, says Azermai. “ScriptBook would only have green-lit 42 out of 70,” with only a handful of false positives, but she claims that her product avoided the biggest flops. And saving studio cash could be a big business: the cumulative deficits caused by 2016’s ten biggest flops — as charted by Forbes — was a whopping $100.9 million.

Azermai references the 2015 remake of Point Break as evidence of the sheer power of the platform that she’s put together. A fan of the original film, she ran the screenplay for the remake as soon as she got her hands on it. The algorithm, however, determined — months before release — that the film would gross only $31 million in the US. In her telling, the result “made me really doubt our system,” because the remake seemed like a slam dunk. When the film debuted that December, its domestic gross, as calculated by BoxOfficeMojo, was just $28.8 million — more of a flop than even her system could determine.

There’s a boatload of ifs and buts, but if ScriptBook works, then Azermai believes she could have a massively successful product. After all, spending a million dollars on script analysis is chump change compared with eating a hundred times that in losses. Even if the studio was used only 20 or so times a year, that’s still enough for ScriptBook’s creators to kick back and relax. If you look at some of the studios’ lineups (oh hey, Warner Bros.) for the next few years, it’s clear that there’s a need for this sort of QA checking.

Nadira Azermai and her team at ScriptBook.

ScriptBook isn’t the only game in town: Tools such as ScripThreads can analyze a screenplay and visualize its storyline and character interaction, while Slated offers screenplay analysis based on the pooled review scores of three unnamed studio development team employees. But Azermai’s product is the only one that offers an apparently concrete prediction of a movie’s potential success.

The platform will be launching in the near future, and while its initial pitch will be to studios, it won’t stay that way. Azermai told Engadget that the company is “working on” a more limited tool that’ll be offered to screenwriters. Rather than the more detailed financial analysis, it’ll offer a generic metric of a script’s quality and likelihood of success. Thankfully, Azermai promises that it’ll also be cheap enough for most dirt-poor typewriter junkies to afford.

ScriptBook’s claims are big and broad, and if it works, it certainly has the potential to upend the way movies are made. The only problem, for now, is that it’s nearly impossible to demonstrate or prove that the results it produces are legitimate — for instance, Slash Film decried its claims as “complete and utter B.S.” Azermai isn’t worried about the “older creatives,” who are skeptical, because it’s Hollywood’s decision makers — the accountants — who will determine the product’s success.

There are still a thousand unanswered questions as to how ScriptBook actually works, and few are currently forthcoming. We were allowed a day to play around with the firm’s embryonic user interface, but any attempt to test the system with a fresh screenplay was resisted. All the same, the company is getting ready to unleash itself upon an unsuspecting world, and if we see the quantity of flops decreasing in five years or so, we’ll know who to thank.

Twitter CEO Jack Dorsey Says a Form of Editing is Needed

In a conversation on Twitter this morning that followed a call for ideas to improve the Twitter platform, Twitter CEO Jack Dorsey said he believes some form of editing function is needed on the social network.

Twitter is one of the few social networks where editing content that’s been shared is not possible, despite Twitter users having long desired the feature. On social networks like Facebook and Instagram, editing content that’s already been posted to fix spelling and other errors is possible.

The original question posed to Dorsey suggested Twitter users with badges verifying identity be allowed to edit, but Dorsey said editing should be a feature available for all Twitter users, not just those that have been verified. In additional tweets, Dorsey said an editing feature is being considered, and he asked whether a short editing window would be sufficient for correcting mistakes or if editing should be allowed at any time.

@howardlindzon not sure why you’re quoting this tweet but yes, a form of edit is def needed. But for everyone, not just those w badges

— 🚶🏽jack (@jack) December 29, 2016

It’s not clear if and when Dorsey’s feelings on an edit function will translate into an actual edit feature implemented on Twitter, but Twitter has been making a lot of positive changes in recent months and Dorsey says the company is “thinking a lot” about editing and how it would work on Twitter.

Back in September, Twitter implemented a change to its character limit, making it so photos, videos, GIFs, polls, and quoted tweets no longer count towards the 140-character limit. According to Dorsey, Twitter is also exploring better tweet storm tools, improved search relevance, better conversation threading, a more consistent response to hate speech and more transparency, and improvements to direct messages.

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Here’s a Detailed Aerial Photograph of Apple Campus 2

Apple’s spaceship-shaped campus in Cupertino, California is nearing completion, and most of the ring-shaped main structure and auxiliary buildings have been finished.

We’ve seen monthly drone updates of the location during the construction period, letting us keep an eye on Apple’s progress, and now SkyIMD has created a neat high-resolution aerial mosaic that gives an incredibly detailed overall view of the nearly-finished campus.

Click here to see full high-resolution image on Imgur
The image depicts the main spaceship building that is the highlight of the campus, with its massive curved glass windows and huge built-in glass doors that open up into a cafeteria area. The aerial photo, composed of ten 100-megapixel images captured with a PhaseOne iXA-RS1000, was made on December 22.

Duncan Sinfield, who has shared Apple Campus 2 drone videos with MacRumors for several months, has also uploaded an updated video captured on Christmas morning that shows the progress Apple has made on landscaping in recent weeks.

Apple plans to have the campus finished by the beginning of 2017, with employees moving in during the first quarter, but landscaping work will not be finished until the middle of the year.

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