pattern recognition,

We always write that abuse is instilling doubt in order to maintain control. Part of this instillation of doubt is turning you into the villain, turning you into the responsible party for what’s happening to you in the relationship, turning you into the fundamentally bad person whose thoughts, feelings, and behaviors need to be corrected.
—  Michael Schreiner
The human talent for pattern recognition is a two-edged sword. We’re especially good at finding patterns, even when they aren’t really there. Something known as false pattern recognition. We hunger for significance, for signs that our personal existence is of special meaning to the universe. To that end, we’re all too eager to deceive ourselves and others, to discern a sacred image in a grilled cheese sandwich or find a divine warning in a comet.
—  Neil deGrasse Tyson, Cosmos: A Spacetime Odyssey 

Universe Is Made Of Math, Cosmologist Says

Scientists have long used mathematics to describe the physical properties of the universe. But what if the universe itself is math? That’s what cosmologist Max Tegmark believes.

In Tegmark’s view, everything in the universe — humans included — is part of a mathematical structure. All matter is made up of particles, which have properties such as charge and spin, but these properties are purely mathematical, he says. And space itself has properties such as dimensions, but is still ultimately a mathematical structure.

“If you accept the idea that both space itself, and all the stuff in space, have no properties at all except mathematical properties,” then the idea that everything is mathematical “starts to sound a little bit less insane,” Tegmark said in a talk given Jan. 15 here at The Bell House. The talk was based on his book “Our Mathematical Universe: My Quest for the Ultimate Nature of Reality” (Knopf, 2014).

Nature is full of math

The idea follows the observation that nature is full of patterns, such as the Fibonacci sequence, a series of numbers in which each number is the sum of the previous two numbers. The flowering of an artichoke follows this sequence, for example, with the distance between each petal and the next matching the ratio of the numbers in the sequence.

The nonliving world also behaves in a mathematical way. If you throw a baseball in the air, it follows a roughly parabolic trajectory. Planets and other astrophysical bodies follow elliptical orbits.

“There’s an elegant simplicity and beauty in nature revealed by mathematical patterns and shapes, which our minds have been able to figure out,” said Tegmark, who loves math so much he has framed pictures of famous equations in his living room.

One consequence of the mathematical nature of the universe is that scientists could in theory predict every observation or measurement in physics. Tegmark pointed out that mathematics predicted the existence of the planet Neptune, radio waves and the Higgs boson particle thought to explain how other particles get their mass.

Some people argue that math is just a tool invented by scientists to explain the natural world. But Tegmark contends the mathematical structure found in the natural world shows that math exists in reality, not just in the human mind.

And speaking of the human mind, could we use math to explain the brain?

Mathematics of consciousness

Some have described the human brain as the most complex structure in the universe. Indeed, the human mind has made possible all of the great leaps in understanding our world.

Someday, Tegmark said, scientists will probably be able to describe even consciousness using math. (Carl Sagan is quoted as having said, “the brain is a very big place, in a very small space.”)

“Consciousness is probably the way information feels when it’s being processed in certain, very complicated ways,” Tegmark said. He pointed out that many great breakthroughs in physics have involved unifying two things once thought to be separate: energy and matter, space and time, electricity and magnetism. He said he suspects the mind, which is the feeling of a conscious self, will ultimately be unified with the body, which is a collection of moving particles.

But if the brain is just math, does that mean free will doesn’t exist, because the movements of particles could be calculated using equations? Not necessarily, he said.

One way to think of it is, if a computer tried to simulate what a person will do, the computation would take at least the same amount of time as performing the action. So some people have suggested defining free will as an inability to predict what one is going to do before the event occurs.

But that doesn’t mean humans are powerless. Tegmark concluded his talk with a call to action: “Humans have the power not only to understand our world, but to shape and improve it.”

You're reading too much into that!

At some point in most fandom conversations, someone will leap in and say, “You’re reading too much into that.” I’m sure you’ve all seen it, you may have even done it.

I’m so tired of it.

It’s a really useless argument in the form it’s usually offered in – illogical, intolerant, and ignorant. This post breaks down why it’s a weak argument, just so I can get the rant out of my brain and let it go.

Seeing false patterns

First, it is entirely possible to read too much into a text. Let’s get that out of the way right up front. Human brains are really good at recognising patterns – it’s one of our superpowers, and it’s what allows us to forward-plan for winter, and do science, and create art. But it has a downside, and that is that we can sometimes see false patterns – things which are coincidental, rather than true patterns. It’s because of this very thing that science must be repeatable to be considered valid – one finding, in one small-scale study, could just be a false pattern, or a miss-attributed one.

So this possibility of seeing a false pattern, which is really coincidental rather than a true pattern, is what the argument “You’re reading too much into that” is based on.

The problem is that this argument is rarely used to actually mean that the person is seeing a false pattern. Instead, it’s trotted out as an insult – “You’re reading too much into that, because you’re delusional” is what is usually meant, and it’s often underpinned by misogynist, racist or homophobic thinking. For instance: “Only a crazy slash fangirl would read queerness into the text,” which hits both sexism and homophobia at the same time.

How do I know it’s meant in this insulting way, rather than in the sense that someone is seeing a false pattern? Because the person trotting out this shutdown rarely bothers to give any evidence that the pattern is false. They just assume it must be, because they are sure their own mainstream reading is correct.

It’s lazy thinking, based on unacknowledged assumptions about how the world works, and that really grates on me, just as much as the normalised homophobia, racism, and sexism which underpin that kind of thinking do. But that’s not the only thing wrong with this argument. Oh, no. There’s more!

Texts are constructions, not natural phenomena

Texts are not natural phenomena that “just happen”. They are not schools of fish, or tree rings, or clouds. Texts are constructed. They are deliberate. They are made things, like a bridge, or a dress, or a tube of toothpaste.

Can you imagine someone saying, “You’re reading too much into that,” if someone says, “Hey, that bridge wobbles when it’s windy”? Or “You’re reading too much into that,” when someone says, “This toothpaste tastes different to usual, they must have changed the formula”?

Because that’s basically what people are doing when they say it about texts.

You might think the person is seeing a false pattern in those two hypothetical situations, but in that case you’d probably feel you needed to put forward another plausible explanation, rather than just saying they are wrong. (Although some people might still say, “You’re wrong, and also stupid because you’re a girl,” right up until the bridge falls down or the toothpaste is recalled.)

If you’re a reasonable person, you might argue the bridge is designed to wobble, or it’s just a visual illusion, or maybe the person drank orange juice right before cleaning their teeth and that’s why the toothpaste tastes funny. You won’t just say, “You’re reading too much into that,” as though it’s completely impossible there is a pattern you haven’t noticed yet.

There’s this weird belief in the West that somehow stories aren’t really made things, and don’t follow the same rules as a bridge or toothpaste in terms of how we critique them. It’s based on a long, long history of art criticism, mainly arising from a bunch of privileged white men whining because no-one liked their art. You might think their arguments are valid, and that’s okay (although I don’t agree), but if you have no idea what I’m talking about, you might want to stop and think about why you read texts the way you do. Where did you learn it from? Why do you think it’s right? Why do you think the way other people read is wrong?

Anyway, the history and politics of how we read texts are not the only reasons this argument is weak.

Writers have human brains

This assumption that “You’re reading too much into that” is also based on an anti-intellectual reading position. This is the idea that no writer would go to the bother to seed complex ideas, subtext or patterns into their text, and the corresponding idea that texts aren’t worth reading on this level.

That is such an entirely insulting notion on so many levels.

As a writer, I can tell you we can, and do, put this kind of planning into texts. Not necessarily every text, or all the time. But yes, it’s a thing that happens. What’s more, when you do a close reading of a text with an author present, and point out you noticed those patterns, they are fucking delighted. And will often tell you in great detail why they put it in.

In addition to that, we create these texts with our pattern-recognising brains. We will put patterns in without realising it too, because that’s how our brains work. More than once, I’ve read my first drafts back (or beta read those of others), and realised that there was a major theme in there that I hadn’t been aware of while writing. I usually tease it out further in re-writes, because my storybrain knew what it was doing by putting it in there.

In my experience, it’s mainly people who don’t write who think this kind of deep structure is accidental or unimportant. They are speaking from ignorance, or perhaps a belief that stories magically appear fully formed in a Word document while the author is off somewhere else, wearing a smoking jacket and brooding.

If only, my friend. If only that were true.

How do I avoid this fallacy?

It’s really simple. Give your reasons for disagreeing instead of just lazily dismissing arguments out of hand. If you think someone is seeing a false pattern, show some evidence that it might be a false pattern.

Alternatively, if it’s not an argument you want to get into right now, agree to disagree – “That’s an interesting take on it, but I read the text differently” – and then move on to the aspect you want to discuss.

If you can’t be bothered doing either of those things, and decide to dismiss their argument out of hand in favour of your own, recognise that you’re being an intolerant troll.

And if you can’t find any evidence that the person is seeing a false pattern… Guess what?

They might actually be right about the pattern being there, and their pattern recognition skills are better, or better educated, than yours.

First demonstration of brain-inspired device to power artificial systems

New research, led by the University of Southampton, has demonstrated that a nanoscale device, called a memristor, could be used to power artificial systems that can mimic the human brain.

Artificial neural networks (ANNs) exhibit learning abilities and can perform tasks which are difficult for conventional computing systems, such as pattern recognition, on-line learning and classification. Practical ANN implementations are currently hampered by the lack of efficient hardware synapses; a key component that every ANN requires in large numbers.

In the study, published in Nature Communications, the Southampton research team experimentally demonstrated an ANN that used memristor synapses supporting sophisticated learning rules in order to carry out reversible learning of noisy input data.

Memristors are electrical components that limit or regulate the flow of electrical current in a circuit and can remember the amount of charge that was flowing through it and retain the data, even when the power is turned off.

Lead author Dr Alex Serb, from Electronics and Computer Science at the University of Southampton, said: “If we want to build artificial systems that can mimic the brain in function and power we need to use hundreds of billions, perhaps even trillions of artificial synapses, many of which must be able to implement learning rules of varying degrees of complexity. Whilst currently available electronic components can certainly be pieced together to create such synapses, the required power and area efficiency benchmarks will be extremely difficult to meet -if even possible at all- without designing new and bespoke ‘synapse components’.

“Memristors offer a possible route towards that end by supporting many fundamental features of learning synapses (memory storage, on-line learning, computationally powerful learning rule implementation, two-terminal structure) in extremely compact volumes and at exceptionally low energy costs. If artificial brains are ever going to become reality, therefore, memristive synapses have to succeed.”

Acting like synapses in the brain, the metal-oxide memristor array was capable of learning and re-learning input patterns in an unsupervised manner within a probabilistic winner-take-all (WTA) network. This is extremely useful for enabling low-power embedded processors (needed for the Internet of Things) that can process in real-time big data without any prior knowledge of the data.

Co-author Dr Themis Prodromakis, Reader in Nanoelectronics and EPSRC Fellow in Electronics and Computer Science at the University of Southampton, said: “The uptake of any new technology is typically hampered by the lack of practical demonstrators that showcase the technology’s benefits in practical applications. Our work establishes such a technological paradigm shift, proving that nanoscale memristors can indeed be used to formulate in-silico neural circuits for processing big-data in real-time; a key challenge of modern society.

“We have shown that such hardware platforms can independently adapt to its environment without any human intervention and are very resilient in processing even noisy data in real-time reliably. This new type of hardware could find a diverse range of applications in pervasive sensing technologies to fuel real-time monitoring in harsh or inaccessible environments; a highly desirable capability for enabling the Internet of Things vision.”

We have no idea, now, of who or what the inhabitants of our future might be. In that sense, we have no future. Not in the sense that our grandparents had a future, or thought they did. Fully imagined cultural futures were the luxury of another day, one in which ‘now’ was of some greater duration. For us, of course, things can change so abruptly, so violently, so profoundly, that futures like our grandparents’ have insufficient 'now’ to stand on. We have no future because our present is too volatile. … We have only risk management. The spinning of the given moment’s scenarios. Pattern recognition
—  ― William Gibson, Pattern Recognition