#this is 'this person's access to photoshop should be permanently restricted'

[skitskatdacat63]

Podium on Sunday? 👀

[script-a-world]

My story is going to place in prehistoric times and I cannot find any information on the existence or status of plus sized people that I believe is neutral and not fat-shaming. Most sources say there weren't any, since better diet and a lot more exercise, but I doubt that, to be honest. Should I just say screw it and add plus sized characters anyway or would you suggest finding scientific sources first?

Mod Miri Note: Hi folks, there’s a lot of talk in this post about body size which I can be triggering for some readers, and with tumblr’s tag system being pretty unreliable, I just wanted to put up a quick warning in case that would be an issue for any of our followers who may want to skip this post. 

Feral: Yes. If you want to include plus sized characters, include plus sized characters. First of all, waist size is not actually a great indicator of physical fitness level. Second of all, at some point in prehistory humans evolved and when we did that, we evolved to store fat; this was likely for a reason. And third of all, no one is going to care if you do or do not find "scientific proof". The truth is, people have been people for as long as there have been people.

Tex: I would suggest to first figure out why you are defining things in the term "plus sized" - Google's Ngram Viewer finds that this wasn't in public circulation until almost 1950, which means that the vernacular would be entirely different the further back you go into the past. Wikipedia's article on "Plus-size clothing" indicates that the origins for this size group in fashion had comparatively very recent roots.

"Plus-size", "curvy", "big and tall", "stout"- these are all euphemisms to refer to a body type that is considered larger than the normal range. Human bodies are delicately-organized organic machines, and while they can tolerate a wide variety of stressors, they can only tolerate any given stressor for a certain amount of time before it damages the body - sometimes permanently, and fatally, if it's allowed to go unchecked.

The human body is built to be within a certain weight range for given heights - despite the flaws of the BMI, with its difficulty in telling apart muscle from fat (and which type of fat), it's still a good tool when used in conjunction with other diagnostic tests. To be overweight and to be obese are separated by very thin lines, and is better discussed in @ucsdhealthsciences' post "Fat but Fit: a pleasing myth or something else? ".

Given the comorbidities of being either overweight or one of the three grades of obesity, carrying more fat on your body than your body can safely tolerate is quite literally dangerous for your health. Prehistoric peoples rarely had the luxury of idleness or having someone transport them instead of walking (or even riding a horse/similar animal). Walking  in and of itself is ridiculously good for your health, to the point where exercising in the form of a gym or even manual labor can be a marginal part of one's exercise routine if someone has a choice about it.

I don't know why you doubt that a better diet and more exercise wouldn't reduce the occurrence of overweight/obese individuals - excess weight from specifically white fat has serious detrimental effects on the body and has a tendency to kill people off:

- "Study in mice suggests drug to turn fat 'brown' could help fight obesity"] from the University of Cambridge- Wikipedia- University of Virginia Health System - National Institute of Diabetes and Digestive and Kidney Diseases - "The Definition and Prevalence of Obesity and Metabolic Syndrome"  by Atilla Engin  - "Prevalence of polycystic ovary syndrome in Chinese obese women of reproductive age with or without metabolic syndrome"  by Liang, Peiwen et al.- ittybittykittykisses, archived version - Stanford Health Care - PDF "Mechanisms, Pathophysiology, and Management of Obesity"  by Steven B. Heymsfield, M.D., and Thomas A. Wadden, Ph.D.- "Review of Childhood Obesity: From Epidemiology, Etiology, and Comorbidities to Clinical Assessment and Treatment"  by Seema Kumar, MD and Aaron S. Kelly, PhD- "A Proposal of the European Association for the Study of Obesity to Improve the ICD-11 Diagnostic Criteria for Obesity Based on the Three Dimensions Etiology, Degree of Adiposity and Health Risk" by J Hebebrand et al.- "Health Effects of Overweight and Obesity in 195 Countries over 25 Years"  by The GBD 2015 Obesity Collaborators - "Study of nearly 300,000 people challenges the 'obesity paradox'"  from the European Society of Cardiology

The Archaeology News Network has an article  about prehistoric obesity, and how it relates to fat storage in humans - the mutation of the uricase gene that was originally meant to help ancient humans survive famines and seasonal periods of low food. "Evolutionary history and metabolic insights of ancient mammalian uricases" by James T. Kratzer et al backs this idea up and goes into some further detail. "Archeologia dell’alimentazione umana [PDF]", or "Archaeology of nutrition" in English, by F. Gregorio and M. Sudano (abstract also provided in English) talks about how the human genotype has changed as diet and sedentary levels shifted.

Perhaps you're thinking of the Venus figurines as an example of "plus size"? But that's still not quite right - many of these figurines are meant to display what fertile women look like, especially pregnant ones (peak fertility for a great many cultures, but also a temporary state for women), and real-life steatopygian body types are mostly restricted to either parts of Africa or parts of India, often by tribe.

In China, and I believe parts of Asia with similar cultures, fat under the chin heralds many good things  - possibly because it meant you weren't starving and thus had enough food to be considered wealthy. Your mileage will vary on that, because China and many other cultures frown upon consumption unto excess for a variety of reasons.

People with more weight on them than average for their population, historically, have access to more food - which means ruling families, wealthy people - and once it was invented, (wealthy) farmers. But many cultures that were around in prehistory didn't have those kinds of societal structures, and pre-agricultural societies were inherently on the thin side because they were nomadic (which meant lots of walking), and had a diet primarily of gathered fruits/vegetables and whatever meat they could hunt down. It's usually the carbohydrates and other complex sugars in processed grains, such as breads, noodles, and bread-beers, that incite weight gain which is difficult to slough off, so it's something you need to keep in mind when worldbuilding your prehistoric societies.

If you want these kinds of body types in your worldbuilding, that's fine, but I would recommend that you don't try to view the past through the context of the present - life was very different back then, for very legitimate reasons, in ways that are neither wholly good nor wholly bad.

Saphira: Tex effectively nailed it, but I realize that you are likely writing "Plus-sized" characters into your narrative for representative purposes. You see how people under that title are treated in our current era, and you want to give them a more positive experience through your story. This is benevolently spirited, and so I understand your frustration with the situation. Being that history is not giving you a foothold for your vision, it's time to try another method.

Let's take a look at the Venus Figurines! They were made to represent women with bounty of life within them (as they were pregnant). They were also structures that represent faith. It gives us a fun, and positive, perspective on figures who are plus-sized. If we add a few degrees of separation, we get a foothold! First step: Pregnant people are plus sized. Second Step: Plus-sized means fertility and life. Third step: Anyone representing that plus-size is a bringer of fertility and life.

If Humans didn't have that plus-size due to their lifestyle and resources, then they may have idealized it. Look at how the renaissance models their women. They are plump and wealthy. Would not the people in your era feel similarly? Would they seek out, would they dream of, someone with that stature? Would they have a divine figure with those attributes? "This Venus figure represents a woman who is pregnant." "This Venus figure is not a pregnant woman, for it does not give birth to human children. Instead, it gives birth to vibrant fields, fresh water and honeybees."

If you are using divines or magic itself, you can find ways to representing plus-sizes in more creative ways. If you are working in a natural world, you can represent them with faith, or impressions of other creatures (like the bounty of a fruit, or the strength of a bear). Honestly, if we can worship skinniness through the art of Photoshop, others can worship the equally idealistic forms of the plus-size and all the wealth it represents in a pre-historic era.

Constablewrites: Another thing to remember about the Venus figurines is that recent scholarship has argued that they aren't just pregnant women, but they're self-portraits of pregnant women. That is, what was generally assumed to have been created by someone else *koff* men *koff* as an idealized depiction may have in fact been a way for women to explore and understand their own changing bodies. Perspective is critical when talking about beauty standards.

And Tex's point about the connection between economic status and beauty really needs to be underscored. You can see the point in history where a white person with a suntan went from being someone who worked outdoors (which meant they were poor and therefore undesirable) to being someone who could travel somewhere sunny and lounge around outside (which meant they were rich and therefore desirable). People are inclined to look for a mate whose children will be healthy, well cared for, and prosperous; the outward indicators of that status, whatever they might be in a given society, end up being conflated with an abstract idea of beauty.

Feral: As Tex, Saphira, and Constable pointed out "plus sized" has a wide definition (and can mean as small as an American size 10 depending on the brand), and it's important to also remember that "prehistory" has a wide definition - specifically a 3 million+ year definition. Prehistory covers everything from the first stone tools 3.3 million years ago to maybe somewhere around 5,300 years ago. Kinda. Prehistory means "before written record" and runs through the Stone Age, Bronze Age, and Iron Age, which all end in different places at different times.

So, what this means is that depending on which epoch your civilization falls under, there may absolutely be the necessary agriculture and division of social class that have been brought up.  Narrowing down when and where you are trying to base your worldbuilding in will help you as you develop you characters and do further research on  a variety of issues that may come up.

Another thing to consider is that you're probably not going to be describing your characters as "plus-sized" in your story (and if you did, all your readers would have different concepts about what that actually means), so the clearer your idea of what the characters' body shape (aka "where mass tends to accumulate"), the easier I think it will be for you to describe the character to your reader in a way that expresses what you specifically mean when you're thinking "plus sized." The fashion designer Justine Leconte has a great video to teach people how to recognize different body types using celebrities [Youtube]. It is geared towards fashion and what to wear based on your body type, but the knowledge is still helpful.

You might have seen this post on Tumblr with the body shapes of all the greatest athletes in the world that might also be helpful for you. But ultimately, I stand by my original point. This is a topic that no matter what you choose to do and what evidence you use to back up your choice, some of your audience is going to have a problem with it. So, just create your world and characters as you see them.

[mathematicianadda]

A Few Thoughts about Deep Fakes

Someone from the House Permanent Select Committee on Intelligence recently contacted me about a hearing they’re having on the subject of deep fakes. I can’t attend the hearing, but the conversation got me thinking about the subject of deep fakes, and I made a few quick notes….

What You See May Not Be What Happened

The idea of modifying images is as old as photography. At first, it had to be done by hand (sometimes with airbrushing). By the 1990s, it was routinely being done with image manipulation software such as Photoshop. But it’s something of an art to get a convincing result, say for a person inserted into a scene. And if, for example, the lighting or shadows don’t agree, it’s easy to tell that what one has isn’t real.

What about videos? If one does motion capture, and spends enough effort, it’s perfectly possible to get quite convincing results—say for animating aliens, or for putting dead actors into movies. The way this works, at least in a first approximation, is for example to painstakingly pick out the keypoints on one face, and map them onto another.

What’s new in the past couple of years is that this process can basically be automated using machine learning. And, for example, there are now neural nets that are simply trained to do “face swapping”:

In essence, what these neural nets do is to fit an internal model to one face, and then apply it to the other. The parameters of the model are in effect learned from looking at lots of real-world scenes, and seeing what’s needed to reproduce them. The current approaches typically use generative adversarial networks (GANs), in which there’s iteration between two networks: one trying to generate a result, and one trying to discriminate that result from a real one.

Today’s examples are far from perfect, and it’s not too hard for a human to tell that something isn’t right. But even just as a result of engineering tweaks and faster computers, there’s been progressive improvement, and there’s no reason to think that within a modest amount of time it won’t be possible to routinely produce human-indistinguishable results.

Can Machine Learning Police Itself?

OK, so maybe a human won’t immediately be able to tell what’s real and what’s not. But why not have a machine do it? Surely there’s some signature of something being “machine generated”. Surely there’s something about a machine-generated image that’s statistically implausible for a real image.

Well, not naturally. Because, in fact, the whole way the machine images are generated is by having models that as faithfully as possible reproduce the “statistics” of real images. Indeed, inside a GAN there’s explicitly a “fake or not” discriminator. And the whole point of the GAN is to iterate until the discriminator can’t tell the difference between what’s being generated, and something real.

Could one find some other feature of an image that the GAN isn’t paying attention to—like whether a face is symmetric enough, or whether writing in the background is readable? Sure. But at this level it’s just an arms race: having identified a feature, one puts it into the model the neural net is using, and then one can’t use that feature to discriminate any more.

There are limitations to this, however. Because there’s a limit to what a typical neural net can learn. Generally, neural nets do well at tasks like image recognition that humans do without thinking. But it’s a different story if one tries to get neural nets to do math, and for example factor numbers.

Imagine that in modifying a video one has to fill in a background that’s showing some elaborate computation—say a mathematical one. Well, then a standard neural net basically doesn’t stand a chance.

Will it be easy to tell that it’s getting it wrong? It could be. If one’s dealing with public-key cryptography, or digital signatures, one can certainly imagine setting things up so that it’s very hard to generate something that is correct, but easy to check whether it is.

But will this kind of thing show up in real images or videos? My own scientific work has actually shown that irreducibly complex computation can be quite ubiquitous even in systems with very simple rules—and presumably in many systems in nature. Watch a splash in water. It takes a complex computation to figure out the details of what’s going to happen. And while a neural net might be able to get something that basically looks like a splash, it’d be vastly harder for it to get the details of a particular splash right.

But even though in the abstract computational irreducibility may be common, we humans, in our evolution and the environments we set up for ourselves, tend to end up doing our best to avoid it. We have shapes with smooth curves. We build things with simple geometries. We try to make things evolvable or understandable.  And it’s this avoidance of computational irreducibility that makes it feasible for neural nets to successfully model things like the visual scenes in which we typically find ourselves.

One can disrupt this, of course. Just put in the picture a display that’s showing some sophisticated computation (even, for example, a cellular automaton). If someone tries to fake some aspect of this with a neural net, it won’t (at least on its own) feasibly be able to get the details right.

I suspect that in the future of human technology—as we mine deeper in the computational universe—irreducible computation will be much more common in what we build. But as of now, it’s still rare in typical human-related situations. And as a result, we can expect that neural nets will successfully be able to model what’s going on well enough to at least fool other neural nets.

How to Know What’s Real

So if there’s no way to analyze the bits in an image to tell if it’s a real photograph, does that mean we just can’t tell? No. Because we can also think about metadata associated with the image—and about the provenance of the image. When was the image created? By whom? And so on.

So let’s say we create an image. How can we set things up so that we can prove when we did it? Well, in modern times it’s actually very easy. We take the image, and compute a cryptographic hash from it (effectively by applying a mathematical operation that derives a number from the bits in the image). Then we take this hash and put it on a blockchain.

The blockchain acts as a permanent ledger. Once we’ve put data on it, it can never be changed, and we can always go back and see what the data was, and when it was added to the blockchain.

This setup lets us prove that the image was created no later than a certain time. If we want to prove that the image wasn’t created earlier, then when we create the hash for the image, we can throw in a hash from the latest block on our favorite blockchain.

OK, but what about knowing who created the image? It takes a bit of cryptographic infrastructure—very similar to what’s done in proving the authenticity of websites. But if one can trust some “certificate authority” then one can associate a digital signature to the image that validates who created it.

But how about knowing where the image was taken? Assuming one has a certain level of access to the device or the software, GPS can be spoofed. If one records enough about the environment when the image was taken, then it gets harder and harder to spoof. What were the nearby Wi-Fi networks? The Bluetooth pings? The temperature? The barometric pressure? The sound level? The accelerometer readings? If one has enough information collected, then it becomes easier to tell if something doesn’t fit.

There are several ways one could do this. Perhaps one could just detect anomalies using machine learning. Or perhaps one could use actual models of how the world works (the path implied by the accelerometer isn’t consistent with the equations of mechanics, etc.). Or one could somehow tie the information to some public computational fact. Was the weather really like that in the place the photo was said to be taken? Why isn’t there a shadow from such-and-such a plane going overhead? Why is what’s playing on the television not what it should be? Etc.

But, OK, even if one just restricts oneself to creation time and creator ID, how can one in practice validate them?

The best scheme seems to be something like how modern browsers handle website security. The browser tries to check the cryptographic signature of the website. If it matches, the browser shows something to say the website is secure; if not, it shows some kind of warning.

So let’s say an image comes with data on its creation time and creator ID. The data could be metadata (say EXIF data), or it could be a watermark imprinted on the detailed bits in the image. Then the image viewer (say in the browser) can check whether the hash on a blockchain agrees with what the data provided by the image implies. If it does, fine. And the image viewer can make the creation time and creator ID available. If not, the image viewer should warn the user that something seems to be wrong.

Exactly the same kind of thing can be done with videos. It just requires video players computing hashes on the video, and comparing to what’s on a blockchain. And by doing this, one can guarantee, for example, that one’s seeing a whole video that was made at a certain time.

How would this work in practice? Probably people often wouldn’t want to see all the raw video taken at some event. But a news organization, for example, could let people click through to it if they wanted. And one can easily imagine digital signature mechanisms that could be used to guarantee that an edited video, for example, contained no content not in certain source videos, and involved, say, specified contiguous chunks from these source videos.

The Path Forward

So, where does this leave us with deep fakes? Machine learning on its own won’t save us. There’s not going to be a pure “fake or not” detector that can run on any image or video. Yes, there’ll be ways to protect oneself against being “faked” by doing things like wearing a live cellular automaton tie. But the real way to combat deep fakes, I think, is to use blockchain technology—and to store on a public ledger cryptographic hashes of both images and sensor data from the environment where the images were acquired. The very presence of a hash can guarantee when an image was acquired; “triangulating” from sensor and other data can give confidence that what one is seeing was something that actually happened in the real world.

Of course, there are lots of technical details to work out. But in time I’d expect image and video viewers could routinely check against blockchains (and “data triangulation computations”), a bit like how web browsers now check security certificates. And today’s “pics or it didn’t happen” will turn into “if it’s not on the blockchain it didn’t happen”.

from Stephen Wolfram Blog http://bit.ly/2X3fQzD from Blogger http://bit.ly/2IEJ0f1

[keygenuine-blog]

Preview Versions of Office 2016 to the Windows Store

NOTE: If you want to use the permanently activation of office 2016,welcome to the below Microsoft Partner to get get genuine key: http://www.keygenuine.com/

With the release today of the Windows 10 S-based Surface Laptop, Microsoft has brought preview versions of Office 2016 to the Windows Store as well.

“Windows 10 S runs the rich desktop Office apps including popular productivity apps like Word, PowerPoint, Excel, and Outlook,” Microsoft notes. “The full suite of Office apps in preview are currently available to download today with Office 365 in the Windows Store for Windows 10 S. On Surface Laptop, you can simply open the Start menu and click on any of the Office app icons like Word, Excel, or PowerPoint to launch the download from the Store.”

In the off chance you’re not aware of what this all means, Surface Laptop is the first PC to ship with Windows 10 S, Microsoft’s restrictive new version of Windows. Excluding the apps bundled in-box, Windows 10 S only runs Windows Store apps, meaning that you can’t install traditional desktop applications like Chrome, iTunes, or Photoshop. But that means you can’t install Office 2016 either, since that suite of applications is designed for desktop PC technologies.

But as Microsoft revealed at the Surface Laptop announcement a month ago, it is bringing those applications to the Windows Store via its Desktop Bridge (“Centennial”) technologies. But this will happen over time, with just four apps today—Outlook, Word, Excel, and PowerPoint 2016—in preview, and as part of Office 365 Personal and Home bundles. (Office 365 for Education Plus and Office 365 Education E5 are coming, too. And Office 365 plans for business customers will also be supported started in 2018.)

Over time, more desktop apps in the Office 2016 suite will be added to the Windows Store, Microsoft says. (It has committed to at least Access, OneNote, and Publisher 2016.) And Microsoft will make standalone Office 2016 suites, like Office Home & Student 2016 and Office Home & Business 2016 available over time. These other apps, suites, and Office 365 bundles should all be out of preview later this year or by early 2018.

For more information, please refer to Microsoft’s Office on Windows 10 S FAQ, which notes a few interesting tidbits:

During the preview period, customers who buy a Surface Laptop (or, later, a Surface Pro) with Windows 10 S will get one year free of Office 365 Personal, a $70 value.

If you already have an Office 365 Home subscription, you can use the free Office 365 Personal offer to extend your existing subscription by 9 months.

Over time, the Office 2016 apps in the Store will be made available to customers in all markets supported by the Windows Store.

The Office 2016 apps in the Store do not currently support Office 365 business plans or volume licenses. (Again, that is coming in 2018.)

The Office 2016 apps in the Store are of course the 32-bit versions that we all use today because they are compatible with a broad range of Office add-ins. (Older COM-based add-ins are not supported, however.)

Windows 10 S users can, of course, use the Office Mobile apps if they’d like. OneNote Mobile is included as part of all Windows 10 product editions, including Windows 10 S.

[brieflyprofoundsandwich]

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