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Author Archives: atsiko

Should Authors Respond to Reviews of Their Books

Quite randomly, I stumbled onto a web of posts and tweets detailing an incident of an author commenting on a review of one of their books, being taken to task for it, and then spending what I see as way too much time further entangling themselves in the resulting kerfluffle.  I won’t name this author, because I’m not posting clickbait.  I read both sides of the argument, and while I sided mostly with the reviewer whose space was invaded, I do think some of the nuance on both sides that was over-shadowed by this author’s bad behavior offers valuable insight into both review and more general netiquette.

First, I want to establish some premises:

  1. Posting to the internet is a public act.  That’s true if your post is public rather than on a private blog or Twitter account, say.  But it ignores the complexities of human social interaction.  If I’m having a chat with my friends at IHOP (Insert your franchise pseudo-diner of choice), we’re in public.  So it’s a public act.  But not quite!  If some random patron three tables down were to start commenting on our nastily engaging discussion of who should fuck who in the latest, greatest reverse harem anime, we would probably consider that quite rude.  In fact, we have lots of terms for that sort of thing: butting in, nosy, etc.  I think a valid analogy could be made for the internet.  Sure my Tweet stream is public, but as a nobody with no claim to fame or blue checkmark, it’d be quite a shock for the POTUS to retweet some comment of mine about the economy or the failings of the folks in Washington.  The line can be a bit blurrier if I run a popular but niche politics blog, or if I have a regional news show on the local Fox affiliate.  But just because you can read what I wrote doesn’t mean I expect, much less desire, a response from you.
  2. My blog/website is my (semi-)private space.  Yours is yours.  I own the platform, I decide the rules.  You can write whatever you want on your blog.  Your right to write whatever you want on mine is much less clear-cut.
  3. You have institutional authority over your own work.  While most authors may not feel like they have much power in the publishing world, as the “creator”, they have enormous implied power in the world of fandom and discussion of their own specific work, or maybe even someone else’s, if they’re well-known friends of Author X, say.  If I criticize the War in Vietnam or Iraq, and a four-star general comes knocking on my door the next day, you better fucking believe I’m gonna be uncomfortable.  An author may not have a battalion of tanks at their disposal, but they sure as hell have presence, possibly very intimidating presence if they are well-known in the industry or for throwing their weight around in fandom.

Given these basic premises which I hope I have elaborated on specifically enough, I have some conclusions about what I would consider good standard netiquette.  I won’t say “proper” because I have no authority in this area, nor does anyone, really, to back up such a wording.  But a “reasonable standard of” at least I can make logical arguments for.

  1. Say what you want on your own platform.  And you can even respond to what other people have said, especially if you are not an asshole and don’t name names of people who are not egregious offenders of social norms or who haven’t made ad hominem attacks.
  2. Respect people’s bubbles.  We have a concept of how close to stand to someone we’re in a discussion with in real life, for example, that can be a good metaphor for on what platforms we choose to respond.  Especially as regards critique, since responding to negative comments about oneself is something we know from past experience can be fraught with dangerous possibilities.  I would posit that a person’s private blog is reasonably considered part of their personal space.  A column on a widely-read news site might be considered more public,but then  you have to weigh the consideration of news of your bad behavior being far more public and spreading much faster.You should not enter it without a reasonable expectation of a good reception.  If there is a power imbalance between you and the individual whose space you wish to enter, we have rules for that.  real-world analogies.  For example, before you enter someone’s house you knock or ring the doorbell.  A nice email to the specified public contact email address asking if they would mind if you weighed in is a fairly innocuous way to open communications, and can save face on both sides by avoiding exposing one or the other to the possible embarrassment of being refused or the stress of refusing a local celebrity with no clear bad intentions.
  3. Assume permission is required unless otherwise explicitly  stated.  This one gets its own bullet point, because I think it’s the easiest way to avoid the most trouble.  A public pool you might enter without announcing your presence.  Would you walk into a stranger’s house without knocking? One would hope not.
  4. Question your reasons for engaging.  Nobody likes to be  called sexist.  Or racist.  Or shitty at doing their research.  Or bad at writing.  But reactionary  defenses against what could be construed as such an assertion do not in my mind justify an author wading into a fan discussion.  Or a reader discussion, if one considers “fan” as having too much baggage.  An incorrect narrative fact is likely  to be swiftly corrected by other readers or fans.  Libel or slander is probably best dealt with legally.  A reviewer is not your editor.  You should probably not be quizzing them for advice on how to improve your writing, or story-telling, or world-building.  Thanking a reviewer for a nice review might be best undertaken as a link on your own blog.  They’ll see the pingback, and can choose to engage or not.  At best, one might pop in to provide a link to their own blog where they provide answers  to questions raised in the post in question or a general discussion of the book they may wish to share with those who read the review.  But again, such a link would probably be best following a question on whether any engagement by the author might be appreciated.

Overall, I think I’ve suggested a good protocol for an author tojoin in fan or reader discussions without causing consternation or full on flame wars, and at a cost barely more than a couple minutes to shoot an email.

 
 

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Machine “Translation” and What Words Mean in Context

One of the biggest commonly known flaws of mahcine translation is a computer’s inability to understand differing meaning in context.  After all, a machine doesn’t know what a “horse” is.  It knows that “caballo” has (roughly) the same meaning in Spanish as “horse” does in English.  But it doesn’t know what that meaning is.

And it certainly doesn’t know what it means when we say that someone has a “horse-face”(/”face like a horse”).

 

But humans can misunderstand meaning in context, too.  For example, if you don’t know how “machine translation” works, you’d think that machines could actually translate or produce translations.  You would be wrong.  What a human does to produce a translation is not the same as what a machine does to produce a “translation”.  That’s why machine and human translators make different mistakes when trying to render the original meaning in the new language.

 

A human brain converts words from the source language into meaning and the meaning back into words in the target language.  A computer converts words from the source language directly to words in the target language, creating a so-called “literal” translation.  A computer would suck at translating a novel, because the figures of speech that make prose (or poetry) what they are are incomprehensible to a machine.  Machine translation programs lack the deeply associated(inter-connected) knowledge base that humans use when producing and interpreting language.

 

A more realistic machine translation(MT) program would require an information web with connections between concepts, rather than words, such that the concept of horse would be related to the concepts of leg, mane, tail, rider, etc, without any intervening linguistic connection.

Imagine a net of concepts represented as data objects.  These are connected to each other in an enormously complex web.  Then, separately, you have a net of linguistic objects, such as words and grammatical patterns, which are overlaid on the concept net, and interconnected.  The objects representing the words for “horse” and “mane” would not have a connection, but the objects representing the concept of meaning underlying these words would have, perhaps, a “has-a” connection, also represented by a connection or “association” object.

In order to translate between languages like a human would, you need your program to have an approximation of human understanding.  A famous study suggested that in the brain of a human who knows about Lindsay Lohan, there’s an actual “Lindsay” neuron, which lights up whenever you think about Lindsay Lohan.  It’s probably lighting up right now as you read this post.  Similarly, in our theoretical machine translation program information “database”, you have a “horse” “neuron” represented by our concept object concept that I described above.  It’s separate from our linguistic object neuron which contains the idea of the word group “Lindsay Lohan”, though probably connected.

Whenever you dig the concept of horse or Lindsay Lohan from your long-term memory, your brain sort of primes the concept by loading it and related concepts into short-term memory, so your “rehab” neuron probably fires pretty soon after your Lindsay neuron.  Similarly, our translation program doesn’t keep it’s whole data-set in RAM constatnly, but loads it from whatever our storage medium is, based on what’s connected to our currently loaded portion of the web.

Current MT programs don’t translate like humans do.  No matter what tricks or algorithms they use, it’s all based on manipulating sequences of letters and basically doing math based on a set of equivalences such as “caballo” = “horse”.  Whether they do statistical analysis on corpuses of previously-translated phrases and sentences like Google Translate to find the most likely translation, or a straight0forward dictionary look-up one word at a time, they don’t understand what the text they are matching means in either language, and that’s why current approaches will never be able to compare to a reasonably competent human translator.

It’s also why current “artificial intelligence” programs will never achieve true human-like general intelligence.  So, even your best current chatbot has to use tricks like pretending to be a Ukranian teenager with bad English skills on AIM to pass the so-called Turing test.  A side-walk artist might draw a picture perfect crevasse that seems to plunge deep into the Earth below your feet.  But no matter how real it looks, your elevation isn’t going to change.  A bird can;t nest in a picture of tree, no matter how realistically depicted.

Calling what Google Translate does, or any machine “translation” program does translation has to be viewed in context, or else it’s quite misleading.  Language functions properly only in the proper context, and that’s something statistical approaches to machine translation will never be able to imitate, no matter how many billions of they spend on hardware or algorithm development.  Could you eventually get them to where they can probably usually mostly communicate the gist of a short newspaper article?  Sure.  Will you be able to engage live in witty reparte with your mutually-language exclusive acquaintance over Skype?  Probably not.  Not with the kind of system we have now.

Those crude, our theoretical program with knowledge web described above might take us a step closer, but even if we could perfect and polish it, we’re still a long way from truly useful translation or AI software.  After all, we don;t even understand how we do these things ourselves.  How could we create an artificial version when the natural one still eludes our grasp?

 

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The “Next Big Thing” Generation

So, a common topic in many of the writing communities I used to frequent was “the next big thing”.  Generally, what genre of book was going to be the next Twilight vampire romance or Hunger Games dystopia.  I had a lot of fun with those discussions, but only recently have I really stopped to consider how damaging the “next big thing” mindset is.  Not only to literature, but to any field and to our characters as people.

First, it’s damaging to the quality and diversity of books coming out.  If everyone is chasing the next “popular” genre, they aren’t writing, reading, or accepting for publication many good books who just happen to not be the next big thing or who are part of the last big thing.  Even though 90% of the books in the genre of the last big thing were crap, and 7% of the rest were mediocre.

Which ties into my next issue: This attitude creates a hunger for similar books, despite quality or whether the reader would like to try something else because it creates a comfort zone for the reader.  They know they like dystopia because they liked Hunger Games, so they’re more willing to take a chance on another dystopia than a high fantasy or Mundane SF.  (Mundane SF itself having once been the next big thing, thus the proper noun moniker.)

But this is a false comfort zone for many reasons.  The reader may not actually like dystopia, but just that one book.  They may like dystopia but ignore other things they would also really enjoy to keep from having to stray outside their comfort zone.  They may gorge on so many dystopias that they learn to see the flaws in the genre finally,  and therefore ignore a wonderful dystopia down the line, because they’ve moved onto their next big thing.

Or, if they’re jumping on the bandwagon, they may perceive all of YA, say, as mediocre dystopias or obsessed with love triangles.  Perhaps they think all epic fantasy is ASOIAF, which they disliked, and so they don’t take the chance on other works.  For example, maybe they watched the TV show, and aren’t fans of gratuitous sexposition, and so they don’t read the books or similar books because they don’t want to get buried in another avalanche of incest and prostitutes.

Many authors have stories of agents or publishers telling them they have a great book, but they missed the window, or it doesn’t fit with whatever the next big thing is, and so they can’t sell it.  Or they already have ten of these, and even though 8 of them are sub-par, they can’t cancel the contract and pick up this new book.

Or perhaps they like the book, but everyone acquiring fantasy stories right now wants ASOIAF, not comedic contemporary fantasies, or low-key urban fantasies in the original mode without kick-ass leather-wearing, tattoo-bearing heroines with troubled backstories and seriously poor taste in lovers.

And the same can be said for things besides commercial fiction.  Google+ was going to be the next big thing in social media.  Then it was Ello.  Tinder was the next big thing in online dating, and it spawned dozens of clones.  Social media itself is something of a successful next big thing in human interaction and the Internet.  Object-Oriented programming was the next big thing in software design, and yet now the backlash has been going on for years.

Sometimes a next big thing is a great thing.  But the mentality of always hunting for the next big thing is not.  And despite the pressure from our capitalist economy, it might be better in the long term to look for alternatives.  And it is capitalism that is a major driver of this obsession, because history shows even mediocre products can ride the wave of a predecessor to make big money.  Following a successful formula is a bit of a dream situation for many producers of entertainment or products.  That’s why Walmart and most other chains have their own brand version of most popular products, from medicine to housewares to groceries.  The next big thing trend might make some people a decent amount of money in the short-term, but it has long-term effects that have created a sort of creativity pit that we’ll have a hard time climbing out of any time in the near future.  And in the short term, the people who don’t manage to catch the wave, as wonderful as their contributions to literature or software or society may be, are left choking on the dust.

 
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Posted by on January 19, 2017 in atsiko, Uncategorized

 

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Hiatus: Again

So, as I hate my life and happiness and am currently in the process of working on a video game project, including the coding and a narrative arc that could probably be comfortably condensed into 47 fantasy trilogies, schedule posting on the Chimney will be on indefinite hiatus.  That does not mean I won’t be posting.  I probably will.  But it will be sporadic and all post series are on hiatus.

I’m having a hell of a fun time, so though I am a bit sad that I won’t be ramping back up my posting schedule, I’m not too sad.

 
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Posted by on December 15, 2016 in atsiko, Blogging

 

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Magic’s Pawn

One of my favorite styles of magic, though not often see is not a clever way for the protagonist to control the forces of magic, but a system where the forces of magic control the protagonist.  I suppose an ancient prophecy ca work kind of like this or a higher being giving direction, but I’m talking a more concrete and local form of control, yet exercised by a more abstract force.

The forces of magic involved don’t necessarily have to be sentient or intelligent in the way a human is or, even an animal although they could be.  Honestly, I think not being so makes the situation all the more interesting.

Think of the way a bee is involved in an ecosystem: generally as a pollinator.  Now imagine that a human (probably a mage or this world’s equivalent, but not necessarily) has been incorporated into the magical ecosystem of the world in the same way.  Some force of magic has evolved to encourage certain behaviors in human mages that are beneficial to the magic of the world that force of magic is part of.

Perhaps there is a cycle sort of like the water cycle that benefits from humanity in chaos, and so the magic has evolved ways to create that chaos through empowering some mage or person.  The specific actions of the person are irrelevant to the magic, as long as they cause a great upheaval.  The system may not even care if humans would describe this pawn of magic as “evil” or “good”.

Humanoid characters are almost always portrayed as exerting control over the magic of their world, but they are rarely shown to have been integrated into the system–as we are integrated into nature, even despite our control of it–despite what is portrayed in the world’s history as thousands or even millions of years of coexistence.

Where are the magical world equivalents of modern climate change?  There are apocalypses sort of like nuclear bomb analogs.  Mercedes Lackey’s Winds series, for example, with it’s effects on the world of the end of the war depicted in her Gryphon’s series.  But rarely if ever are there subtle build-ups of all the interference caused by humans harnessing magical forces.  Not even on the local level like the magical equivalent of the flooding and ecological damage caused by damning rivers, or the water shortages caused by different political entities failing to cooperate on usage rights of the local river.

I would love to read (or write!) some fantasy exploring a closer relationship between man and magic than simply human master and magical servant/slave.

 

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Magic and Science and How Twins are Different People

Something that in my experience drives many (identical) twins crazy is how many people assume they look alike physically so they must be just alike in other ways.  Interests, hobbies, sexuality, gender, religion, whatever.  Twins may look the same superficially, but underneath they are as different as any two other people.  Or any non-twin siblings if you want to be pedantic about nature and nurture.

Fantasy and Science Fiction are like the Twins of Literature.  Whenever someone tries to talk about genre lines or the difference between science and magic, the same old shit gets trotted out.  Clarke’s Law and all that.  Someone recently left a comment on this very blog saying magic is just a stand-in for science.  My friend!  Boy do we have a lot to talk about today.  While it’s certainly true that magic can serve many of the same functions as science (or technology) in a story, the two are fundamentally different in both themselves and the uses to which they are most often put.  Sure they’re both blonde, but technology like red-heads, and magic is more into undercuts.

 

First, not to keep pushing the lie that science is cold and emotionless, but a prime use of science (not technology!) in literature is to influence the world through knowledge of the world’s own inner workings.  (Technology does not require knowledge in its use, often, but rather only in its construction.)  One of the major differences is that most (but not all) magic in stories requires knowledge to use it.  You have to know how the magic works, or what the secret words are.  Whereas tech is like flipping the light switch.  A great writer once said what makes it science fiction is that you can make the gadget and pass it to the average joe across the engineering bay and he can use it just fine, but magic requires a particular person.  I can pass out a million flame-throwers to the troops, but I can’t just pass you a fireball and expect you not to get burned.  That’s one aspect to look at, although these days, magitech and enchanted objects can certainly play the role of mundane technology fairly well.

Second, magic is about taking our inner workings and thought processes and imposing them on top of the universe’s own rule.  From this angle, what makes magic distinct from technology is that a magic conflict is about the inner struggle and the themes of the narrative and how they can be used to shape the world.  Certainly tech can play this role, twin to how magic can be made to act like tech.  But it’s much less common out in the real world of literature.

 

There are two kinds of magic system:  One is the explicit explanation of how the magic works according to the word of god(the author), and the other is a system that the characters inside the world, with their incomplete knowledge impose on top of the word of god system.  So this group uses gestures to cast spells, and this group reads a spellbook, but they are both manifestations of the same basic energy.

So magic is the power to impose our will on the world whereas science/technology is powerful through its understanding of the uncaring laws of the universe.

Then, of course, are the differences in terms of how authors use them in the narrative.  Magic has a closer connection, in my opinion, to the theme aspect of literature.  It can itself be a realization of the theme of a story.  Love conquers all as in Lily Potter protecting her infant son from the dark lord at the cost of her life.  Passion reflected in the powers of the fire mage.  Elemental magic gives a great example.  Look at the various associations popular between elementalists’ characters and the element they wield.  Cold and impersonal ice mages, loving and hippy-ish earth mages.  This analogical connection is much more difficult to achieve with technology.

 

There’s a lot of debate these days about “scientific” magic versus numinous magic, and whether or not magic must have rules or a system.  But even systematically designed magic is not the same as technology, though it can be made to play similar roles, such as solving a plot puzzle.  But think:  The tricks to magic puzzles are thematic or linguistic.  The Witch-king of Angmar is said to be undefeatable by any man.  The trick to his invulnerability is the ambiguity of the words of the prophecy.  One could argue that a woman is not a man, and therefore not restricted by the prophecy.  We have no idea how the “magic” behind the protection works on a theoretical basis.  Does it somehow check for Y-chromosomes?  But that’s not the point.  The thematic significance of the semantic ambiguity is more important.  In science fiction, it’s the underlying workings that matter.  Even if we don’t explain warp drive, there’s no theme or ambiguity involved.  It gets you there in such and such time and that’s it.  Or, in an STL universe, lightspeed is the limit and there’s no trick to get around it.

You can’t use science or technology the same way as Tolkien did with that prophecy nearly as easily.  Imagine magic is hammer, and science is a sword.  Sure I can put a nail in with the sword, but it’s a bitch and a half compared to just using a hammer.  Just because I can put in that nail with that sword, it doesn’t mean that sword is really a hammer.  Just because I can have magic that appears to follow a few discoverable and consistent rules to achieve varying but predictable effects doesn’t mean it’s the same thing as real-world science.  Maybe the moon always turns Allen into a werewolf on the 1st of the month, but I’ll be codgled if you can do the same thing with science.

Whether magic or science or both are most suited to your story or the other way around depends on your goals for that individual story.  Do you need magic or fantasy elements to really drive home your theme?  Do you need technology to get to the alien colony three stars down?  Magic can evaporate all the water in a six mile radius without frying every living thing around.  Science sure as hell can’t.  Not even far-future science that we can conceive of currently.  They can both dry a cup, although we’re wondering why you’re wasting your cosmic talents when you could just use a damn paper towel.

Science can dress up as magic and fool your third-grade substitute teacher, and science can dress up as magic and fool the local yokels in 13th century Germany.  But even if you put a wedding dress on a horse, it’s still a horse, and throwing hard science trappings onto a magic system doesn’t change it’s nature.

 

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AI and AlphaGo: Why It’s Not the Big Deal It’s Made Out to Be

I’d like to open this post by admitting I am not a Go master.  I’ve played a few times, watch Hikaru no GO when nothing else was on.  But that’s about it.  However, I don’t need to be an expert at the game to point out the flaw in some of the press coverage.  I suspect actual AI researchers already know what I mean.

The first thing to remember is that AlphaGo is a deep-learning program built on a neural network.  What that means is that rather than an artificial intelligence program, AlphaGo is an artificial learning program.  Public perception of AI is still focused on artificial intelligence, but the field has now expanded to cover many related or tangential or component areas of study.  AlphaGo also has some form of reasoning ability.  But this ability is solely related to Go.  You cannot generalize it’s algorithms to other tasks.  In fact, DeepMind even admits there are better programs out there to play Chess.  Chess and Go are both “perfect information”(PI) games.  You can if you so choose know everything about a given game of Chess or Go by looking at the board.  You know all the rules and the position of all the pieces.  PI games are a very popular area of AI research, because programs can do a lot with them.  The information can be reduced to a very small set of states and rules, which is ideal for computers to excel at.  The trick of course is to teach the computer the best set of tactics for taking those rules and the initial state of the game, and trading states with another player to get to the win state.  And yet, even in two PI games, the best AI solution to a player capable of competing with the best of humans is different for each game.

I like to call this specific intelligence, although the more popular terms are weak AI or narrow AI, a kind of non-sentient intelligence focused on solving one task or a narrow range of tasks. But even that is a bit of a misnomer.  After all, the machines aren’t truly smart, just impressively programmed dumb machines.

However, a learning program like AlphaGo comes a bit closer to true intelligence(though not sentience) by being able to take the initially programmed rules and knowledge and extrapolate from them on its own to do things it wasn’t explicitly hard-coded to do by the programmers.  It’s incredibly impressive.  But it’s not “AI” in the way most layfolk think of it.  It’s not general intelligence, even a crude version.  It’s a very sophisticated piece of specific intelligence.

 

 

But there’s a second flaw in the coverage.  Besides the great deal of mystique that’s built up around Go, which isn’t an issue of AI, although some of it is misplaced–for example, another lifeform does not “almost certainly play Go” whereas Chess is too human specific–there’s the issue that even as a powerful example of narrow AI, AlphaGo does not–as stated by some professional players–“play go just like a human but better”.  There has been much talk of its unorthodox tactics, or its algorithm’s focus on win-rate over all else.  Some have even said it made moves “only God could have made”–a common expression of a perfect move.

 

But the real truth is this: much like how genetic code, a style of coding in which a computer is given basic building blocks of code and tasked to mix them up until it finds a closer to optimal solution, AlphaGo has no idea it is playing go.  As far as AlphaGo knows, it’s just trading ones and zeroes around until it finds the desired sequence.  The ways in which a human player attempts to reach the winning board position are inherently different than the way a computer does, because they aren’t really pursuing the same goal.

 

We’re not particularly closer to strong or general AI than we were before.  Go isn’t truly so different from any other PI game.  AlphaGO has not learned intuition.  It’s merely played millions of games of Go subtly adjusting the value it places on a given set of stone positions on the board as it goes until more and more the win-rate increases to the point it wins the game.  Although the process is superficially similar to the way a human learns the game, the lack of framing devices such as vision used by humans has taught it to value entirely different things, and unlike a human, a computer has a perfect memory to go with the perfect information, and it is incapable of making an error.

After that, we can consider the psychological warfare aspect of multi-player games.  AlphaGo may be able to beat anyone Lee Se-dol could, but it cannot judge its opponents experience and thus alter its strategy to beat that player faster or more elegantly.  Instead, it will always play the same way every time, and react no differently to a master making three opening moves than to a novice making the same.  But where a human might see those moves and be able to make a variety of plays depending on their intuition of the players skill or likely next move, AlphaGo will continue to inexorably play exactly the move that will have the highest chance of victory against any and all players, rather than the one with the highest chance of victory against a specific individual.

 
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Posted by on March 15, 2016 in atsiko, Science Fact

 

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