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marleen_ueberall

Humans Are the World's Best Pattern-Recognition Machines, But for How Long? - Big Think - 0 views

  • Not only are machines rapidly catching up to — and exceeding — humans in terms of raw computing power, they are also starting to do things that we used to consider inherently human
  • Quite simply, humans are amazing pattern-recognition machines. They have the ability to recognize many different types of patterns - and then transform these "recursive probabalistic fractals" into concrete, actionable steps.
  • Intelligence, then, is really just a matter of being able to store more patterns than anyone else
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  • Artificial intelligence pioneer Ray Kurzweil was among the first to recognize how the link between pattern recognition and human intelligence could be used to build the next generation of artificially intelligent machines.
  • where human "expertise" has always trumped machine "expertise."
  • It turns out patterns matter, and they matter a lot.
  • The more you think about it, the more you can see patterns all around you. Getting to work on time in the morning is the result of recognizing patterns in your daily commute
  • it's really just a matter of recognizing the right patterns faster than anyone else, and machines just have so much processing power these days it's easy to see them becoming the future doctors and lawyers of the world.
  • The future of intelligence is in making our patterns better, our heuristics stronger.
  • One thing is clear – being able to recognize patterns is what gave humans their evolutionary edge over animals.
  • How we refine, shape and improve our pattern recognition is the key to how much longer we'll have the evolutionary edge over machines.
demetriar

How Pattern Recognition Gives You an Edge | Anna Clark - 0 views

  • Although pattern recognition is commonly associated with computer science and engineering, it also applies to nature, people and social systems. In fact, even animals and babies are born with the ability to recognize patterns. Sharpening our pattern recognition ability helps us cultivate vision, which is crucial for gaining an edge in a rapidly changing world.
  • (Unfortunately, technology also allows powerful interests to recognize patterns in big data to manipulate voters and consumers, but that's another story.)
  • We can become slaves to patterns. Extrapolate this tendency broadly and you can see how a society becomes fixed in its ways.
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  • Pattern recognition only serves as an edge when you know how to use it to your advantage.
  • A kaleidoscope of perspectives also adds luster to life, which sometimes gets dulled by the force of our own habits.
katedriscoll

Pattern Recognition - Rob Thomas - 0 views

  • The science of pattern recognition has been explored for hundreds of years, with the primary goal of optimally extracting patterns from data or situations, and effectively separating one pattern from another. Applications of pattern recognition are found everywhere, whether it’s categorizing disease, predicting outbreaks of disease, identifying individuals (through face or speech recognition), or classifying data. In fact, pattern recognition is so ingrained in many things we do, we often forget that it’s a unique discipline which must be treated as such if we want to really benefit from it.
dicindioha

BBC - Future - The tricks being played on you by UK roads - 0 views

  • When you walk or drive in the UK, you’re being nudged by dozens of hidden messages embedded in the roads and pavements.
  • He suffers from a rare inherited condition that leaves him only able to make out vague colour contrasts around him. Yet he is able to safely pick his way through the hectic city streets, thanks to dozens of hidden messages embedded in our roads and pavements that few of us even notice are there.
  • This subtle form of communication is not just confined to the pavement, either: increasingly, motorists and cyclists are also unknowingly being told what to do.
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  • A horizontal pattern of raised lines going across the pavement tells blind pedestrians they are on the footpath side; raised lines running along the direction of travel indicate the side designated for cycles. A wide, raised line divides the two.
  • Because the raised bumps are unpleasant to ride across, cyclists instinctively are drawn toward the tramline pattern which runs in the same direction as they are traveling.
  • Elsewhere, it is possible to find raised, rounded ribs running across pavement, creating a corduroy pattern. They look like they might be there to provide additional grip; in fact, they are sending a warning to anyone who stands on them about what is ahead.
  • The idea is to guide people through busy areas and around objects by drawing them along these raised lines.
  • They found that uncertainty about the layout of the road ahead is a powerful way of getting drivers to slow down.
  • triangles painted along the edge of each road – create an impression of a narrower road for example, and make drivers more cautious.
  • They have been painting boxes onto the road that use a clever combination of white and dark paint to create the illusion of a speed hump.
  • In India, they have taken things even further by painting deliberate optical illusions to give the impression that obstacles are in the road ahead.
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    This article talks about basically human perception and pattern recognition, and how this helps people who do not have all senses, like being blind. Bumps and grooves in the roads we walk on tell us, without us realizing it, what side we should be on and where there are stairs or platforms. It is interesting that there are patterns with these, as mentioned in the article, but everyday pedestrians do not really notice these patterns, and yet they are there to help us. Another interesting thing was the use of perception, and creating illusions of speed bumps or things in the road to get drivers to slow down. Here they play with perception to create an illusion of a speed bump and make traffic safer. sometimes what we think of as our perception incapabilities actually help us without realizing it.
tongoscar

A Pattern Recognition Theory of Mind | Praxis - 0 views

  • the pace of improvement in technology would become a runaway phenomenon that would transform all aspects of human civilization.
  • the structure and functioning of the human brain is actually quite simple, a basic unit of cognition repeated millions of times. Therefore, creating an artificial brain will not require simulating the human brain at every level of detail. It will only require reverse engineering this basic repeating unit.
  • our memories are organized in discrete segments. If you try to start mid-segment, you’ll struggle for a bit until your sequential memory kicks in.
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  • your memories are sequential, like symbols on a ticker tape. They are designed to be read in a certain direction and in order.
  • your memories are nested. Every action and thought is made up of smaller actions and thoughts.
  • the cortical column, a basic structure that is repeated throughout the neocortex. Each of the approximately 500,000 cortical columns is about two millimeters high and a half millimeter wide, and contains about 60,000 neurons (for a total of about 30 billion neurons in the neocortex).
  • The human brain has evolved to recognize patterns, perhaps more than any other single function. Our brain is weak at processing logic, remembering facts, and making calculations, but pattern recognition is its deep core capability.
  • The neocortex is an elaborately folded sheath of tissue covering the whole top and front of the brain, making up nearly 80% of its weight.
  • For our purposes, the most important thing to understand about the neocortex is that it has an extremely uniform structure.
  • The basic structure and functioning of the human brain is hierarchical. This may not seem intuitive at first. It sounds like how a computer works.
  • Mountcastle also believed there must be smaller sub-units, but that couldn’t be confirmed until years later. These “mini-columns” are so tightly interwoven it is impossible to distinguish them, but they constitute the fundamental component of the neocortex. Thus, they constitute the fundamental component of human thought.
  • The basic structure of a PR has three parts: the input, the name, and the output.
  • The first part is the input – dendrites coming from other PRs that signal the presence of lower-level patterns
  • The third part is the output – axons emerging from the PR that signal the presence of its designated pattern.
  • When the inputs to a PR cross a certain threshold, it fires. That is, it emits a nerve impulse to the higher-level PRs it connects to. This is essentially the “A” PR shouting “Hey guys! I just saw the letter “A”!” When the PR for “Apple” hears such signals for a, p, p again, l, and e, it fires itself, shouting “Hey guys! I just saw “Apple!” And so on up the hierarchy.
  • “neurons that fire together, wire together,” which emphasizes the plasticity of individual neurons and is known as the Hebbian Theory, may be incorrect.
Javier E

Never Forgetting a Face - NYTimes.com - 1 views

  • Face-matching today could enable mass surveillance, “basically robbing everyone of their anonymity,” he says, and inhibit people’s normal behavior outside their homes.
  • Dr. Atick says the technology he helped cultivate requires some special safeguards. Unlike fingerprinting or other biometric techniques, face recognition can be used at a distance, without people’s awareness; it could then link their faces and identities to the many pictures they have put online. But in the United States, no specific federal law governs face recognition.
  • some casinos faceprint visitors, seeking to identify repeat big-spending customers for special treatment. In Japan, a few grocery stores use face-matching to classify some shoppers as shoplifters or even “complainers” and blacklist them.
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  • Facebook researchers recently reported how the company had developed a powerful pattern-recognition system, called DeepFace, which had achieved near-human accuracy in identifying people’s faces.
  • To work, the technology needs a large data set, called an image gallery, containing the photographs or video stills of faces already identified by name. Software automatically converts the topography of each face in the gallery into a unique mathematical code, called a faceprint. Once people are faceprinted, they may be identified in existing or subsequent photographs or as they walk in front of a video camera.
  • Dr. Atick has been working behind the scenes to influence the outcome. He is part of a tradition of scientists who have come to feel responsible for what their work has wrought.
  • Is faceprinting as innocuous as photography, an activity that people may freely perform? Or is a faceprint a unique indicator, like a fingerprint or a DNA sequence, that should require a person’s active consent before it can be collected, matched, shared or sold?
  • A private high school in Los Angeles also has an FST system. The school uses the technology to recognize students when they arrive — a security measure intended to keep out unwanted interlopers. But it also serves to keep the students in line.“If a girl will come to school at 8:05, the door will not open and she will be registered as late,” Mr. Farkash explained. “So you can use the system not only for security but for education, for better discipline.”
  • As with many emerging technologies, the arguments tend to coalesce around two predictable poles: those who think the technology needs rules and regulation to prevent violations of civil liberties and those who fear that regulation would stifle innovation. But face recognition stands out among such technologies: While people can disable smartphone geolocation and other tracking techniques, they can’t turn off their faces.
  • To maintain the status quo around public anonymity, he says, companies should take a number of steps: They should post public notices where they use face recognition; seek permission from a consumer before collecting a faceprint with a unique, repeatable identifier like a name or code number; and use faceprints only for the specific purpose for which they have received permission. Those steps, he says, would inhibit sites, stores, apps and appliances from covertly linking a person in the real world with their multiple online personas.
katedriscoll

Patternicity: Finding Meaningful Patterns in Meaningless Noise - Scientific American - 0 views

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    This article really dives deeper in what pattern recognition is and how it effects us.
manhefnawi

Are Smart People More Likely to Believe Stereotypes? | Mental Floss - 0 views

  • There are many different kinds of intelligence, each reliant on its own set of skills and abilities. One such ability is pattern recognition, without which we’d have trouble recognizing faces, learning languages, or reading other people’s emotions. Because it’s so central to our cognitive and social functioning, pattern recognition is sometimes used by researchers as a shorthand for overall intelligence.
  • Finding that higher pattern detection ability puts people at greater risk to detect and apply stereotypes, but also to reverse them, implicates this ability as a cognitive mechanism underlying stereotyping,” co-author Jonathan Freeman said in the statement.
Javier E

E.D. Hirsch Jr.'s 'Cultural Literacy' in the 21st Century - The Atlantic - 0 views

  • much of this angst can be interpreted as part of a noisy but inexorable endgame: the end of white supremacy. From this vantage point, Americanness and whiteness are fitfully, achingly, but finally becoming delinked—and like it or not, over the course of this generation, Americans are all going to have to learn a new way to be American.
  • What is the story of “us” when “us” is no longer by default “white”? The answer, of course, will depend on how aware Americans are of what they are, of what their culture already (and always) has been.
  • The thing about the list, though, was that it was—by design—heavy on the deeds and words of the “dead white males” who had formed the foundations of American culture but who had by then begun to fall out of academic fashion.
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  • Conservatives thus embraced Hirsch eagerly and breathlessly. He was a stout defender of the patrimony. Liberals eagerly and breathlessly attacked him with equal vigor. He was retrograde, Eurocentric, racist, sexist.
  • Lost in all the crossfire, however, were two facts: First, Hirsch, a lifelong Democrat who considered himself progressive, believed his enterprise to be in service of social justice and equality. Cultural illiteracy, he argued, is most common among the poor and power-illiterate, and compounds both their poverty and powerlessness. Second: He was right.
  • A generation of hindsight now enables Americans to see that it is indeed necessary for a nation as far-flung and entropic as the United States, one where rising economic inequality begets worsening civic inequality, to cultivate continuously a shared cultural core. A vocabulary. A set of shared referents and symbols.
  • So, first of all, Americans do need a list. But second, it should not be Hirsch’s list. And third, it should not made the way he made his. In the balance of this essay, I want to unpack and explain each of those three statements.
  • If you take the time to read the book attached to Hirsch’s appendix, you’ll find a rather effective argument about the nature of background knowledge and public culture. Literacy is not just a matter of decoding the strings of letters that make up words or the meaning of each word in sequence. It is a matter of decoding context: the surrounding matrix of things referred to in the text and things implied by it
  • That means understanding what’s being said in public, in the media, in colloquial conversation. It means understanding what’s not being said. Literacy in the culture confers power, or at least access to power. Illiteracy, whether willful or unwitting, creates isolation from power.
  • his point about background knowledge and the content of shared public culture extends well beyond schoolbooks. They are applicable to the “texts” of everyday life, in commercial culture, in sports talk, in religious language, in politics. In all cases, people become literate in patterns—“schema” is the academic word Hirsch uses. They come to recognize bundles of concept and connotation like “Party of Lincoln.” They perceive those patterns of meaning the same way a chess master reads an in-game chessboard or the way a great baseball manager reads an at bat. And in all cases, pattern recognition requires literacy in particulars.
  • Lots and lots of particulars. This isn’t, or at least shouldn’t be, an ideologically controversial point. After all, parents on both left and right have come to accept recent research that shows that the more spoken words an infant or toddler hears, the more rapidly she will learn and advance in school. Volume and variety matter. And what is true about the vocabulary of spoken or written English is also true, one fractal scale up, about the vocabulary of American culture.
  • those who demonized Hirsch as a right-winger missed the point. Just because an endeavor requires fluency in the past does not make it worshipful of tradition or hostile to change.
  • radicalism is made more powerful when garbed in traditionalism. As Hirsch put it: “To be conservative in the means of communication is the road to effectiveness in modern life, in whatever direction one wishes to be effective.”
  • Hence, he argued, an education that in the name of progressivism disdains past forms, schema, concepts, figures, and symbols is an education that is in fact anti-progressive and “helps preserve the political and economic status quo.” This is true. And it is made more urgently true by the changes in American demography since Hirsch gave us his list in 1987.
  • If you are an immigrant to the United States—or, if you were born here but are the first in your family to go to college, and thus a socioeconomic new arrival; or, say, a black citizen in Ferguson, Missouri deciding for the first time to participate in a municipal election, and thus a civic neophyte—you have a single overriding objective shared by all immigrants at the moment of arrival: figure out how stuff really gets done here.
  • So, for instance, a statement like “One hundred and fifty years after Appomattox, our house remains deeply divided” assumes that the reader knows that Appomattox is both a place and an event; that the event signified the end of a war; that the war was the Civil War and had begun during the presidency of a man, Abraham Lincoln, who earlier had famously declared that “a house divided against itself cannot stand”; that the divisions then were in large part about slavery; and that the divisions today are over the political, social, and economic legacies of slavery and how or whether we are to respond to those legacies.
  • But why a list, one might ask? Aren’t lists just the very worst form of rote learning and standardized, mechanized education? Well, yes and no.
  • it’s not just newcomers who need greater command of common knowledge. People whose families have been here ten generations are often as ignorant about American traditions, mores, history, and idioms as someone “fresh off the boat.”
  • The more serious challenge, for Americans new and old, is to make a common culture that’s greater than the sum of our increasingly diverse parts. It’s not enough for the United States to be a neutral zone where a million little niches of identity might flourish; in order to make our diversity a true asset, Americans need those niches to be able to share a vocabulary. Americans need to be able to have a broad base of common knowledge so that diversity can be most fully activated.
  • as the pool of potential culture-makers has widened, the modes of culture creation have similarly shifted away from hierarchies and institutions to webs and networks. Wikipedia is the prime embodiment of this reality, both in how the online encyclopedia is crowd-created and how every crowd-created entry contains links to other entries.
  • so any endeavor that makes it easier for those who do not know the memes and themes of American civic life to attain them closes the opportunity gap. It is inherently progressive.
  • since I started writing this essay, dipping into the list has become a game my high-school-age daughter and I play together.
  • I’ll name each of those entries, she’ll describe what she thinks to be its meaning. If she doesn’t know, I’ll explain it and give some back story. If I don’t know, we’ll look it up together. This of course is not a good way for her teachers to teach the main content of American history or English. But it is definitely a good way for us both to supplement what school should be giving her.
  • And however long we end up playing this game, it is already teaching her a meta-lesson about the importance of cultural literacy. Now anytime a reference we’ve discussed comes up in the news or on TV or in dinner conversation, she can claim ownership. Sometimes she does so proudly, sometimes with a knowing look. My bet is that the satisfaction of that ownership, and the value of it, will compound as the years and her education progress.
  • The trouble is, there are also many items on Hirsch’s list that don’t seem particularly necessary for entry into today’s civic and economic mainstream.
  • Which brings us back to why diversity matters. The same diversity that makes it necessary to have and to sustain a unifying cultural core demands that Americans make the core less monochromatic, more inclusive, and continuously relevant for contemporary life
  • it’s worth unpacking the baseline assumption of both Hirsch’s original argument and the battles that erupted around it. The assumption was that multiculturalism sits in polar opposition to a traditional common culture, that the fight between multiculturalism and the common culture was zero-sum.
  • As scholars like Ronald Takaki made clear in books like A Different Mirror, the dichotomy made sense only to the extent that one imagined that nonwhite people had had no part in shaping America until they started speaking up in the second half of the twentieth century.
  • The truth, of course, is that since well before the formation of the United States, the United States has been shaped by nonwhites in its mores, political structures, aesthetics, slang, economic practices, cuisine, dress, song, and sensibility.
  • In its serious forms, multiculturalism never asserted that every racial group should have its own sealed and separate history or that each group’s history was equally salient to the formation of the American experience. It simply claimed that the omni-American story—of diversity and hybridity—was the legitimate American story.
  • as Nathan Glazer has put it (somewhat ruefully), “We are all multiculturalists now.” Americans have come to see—have chosen to see—that multiculturalism is not at odds with a single common culture; it is a single common culture.
  • it is true that in a finite school year, say, with finite class time and books of finite heft, not everything about everyone can be taught. There are necessary trade-offs. But in practice, recognizing the true and longstanding diversity of American identity is not an either-or. Learning about the internment of Japanese Americans does not block out knowledge of D-Day or Midway. It is additive.
  • As more diverse voices attain ever more forms of reach and power we need to re-integrate and reimagine Hirsch’s list of what literate Americans ought to know.
  • To be clear: A 21st-century omni-American approach to cultural literacy is not about crowding out “real” history with the perishable stuff of contemporary life. It’s about drawing lines of descent from the old forms of cultural expression, however formal, to their progeny, however colloquial.
  • Nor is Omni-American cultural literacy about raising the “self-esteem” of the poor, nonwhite, and marginalized. It’s about raising the collective knowledge of all—and recognizing that the wealthy, white, and powerful also have blind spots and swaths of ignorance
  • What, then, would be on your list? It’s not an idle question. It turns out to be the key to rethinking how a list should even get made.
  • the Internet has transformed who makes culture and how. As barriers to culture creation have fallen, orders of magnitude more citizens—amateurs—are able to shape the culture in which we must all be literate. Cat videos and Star Trek fan fiction may not hold up long beside Toni Morrison. But the entry of new creators leads to new claims of right: The right to be recognized. The right to be counted. The right to make the means of recognition and accounting.
  • It is true that lists alone, with no teaching to bring them to life and no expectation that they be connected to a broader education, are somewhere between useless and harmful.
  • This will be a list of nodes and nested networks. It will be a fractal of associations, which reflects far more than a linear list how our brains work and how we learn and create. Hirsch himself nodded to this reality in Cultural Literacy when he described the process he and his colleagues used for collecting items for their list, though he raised it by way of pointing out the danger of infinite regress.
  • His conclusion, appropriate to his times, was that you had to draw boundaries somewhere with the help of experts. My take, appropriate to our times, is that Americans can draw not boundaries so much as circles and linkages, concept sets and pathways among them.
  • Because 5,000 or even 500 items is too daunting a place to start, I ask here only for your top ten. What are ten things every American—newcomer or native born, affluent or indigent—should know? What ten things do you feel are both required knowledge and illuminating gateways to those unenlightened about American life? Here are my entries: Whiteness The Federalist Papers The Almighty Dollar Organized labor Reconstruction Nativism The American Dream The Reagan Revolution DARPA A sucker born every minute
Javier E

GPT-4 has arrived. It will blow ChatGPT out of the water. - The Washington Post - 0 views

  • GPT-4, in contrast, is a state-of-the-art system capable of creating not just words but describing images in response to a person’s simple written commands.
  • When shown a photo of a boxing glove hanging over a wooden seesaw with a ball on one side, for instance, a person can ask what will happen if the glove drops, and GPT-4 will respond that it would hit the seesaw and cause the ball to fly up.
  • an AI program, known as a large language model, that early testers had claimed was remarkably advanced in its ability to reason and learn new things
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  • hose promises have also fueled anxiety over how people will be able to compete for jobs outsourced to eerily refined machines or trust the accuracy of what they see online.
  • Officials with the San Francisco lab said GPT-4’s “multimodal” training across text and images would allow it to escape the chat box and more fully emulate a world of color and imagery, surpassing ChatGPT in its “advanced reasoning capabilities.”
  • A person could upload an image and GPT-4 could caption it for them, describing the objects and scene.
  • AI language models often confidently offer wrong answers because they are designed to spit out cogent phrases, not actual facts. And because they have been trained on internet text and imagery, they have also learned to emulate human biases of race, gender, religion and class.
  • GPT-4 still makes many of the errors of previous versions, including “hallucinating” nonsense, perpetuating social biases and offering bad advice. It also lacks knowledge of events that happened after about September 2021, when its training data was finalized, and “does not learn from its experience,” limiting people’s ability to teach it new things.
  • Microsoft has invested billions of dollars in OpenAI in the hope its technology will become a secret weapon for its workplace software, search engine and other online ambitions. It has marketed the technology as a super-efficient companion that can handle mindless work and free people for creative pursuits, helping one software developer to do the work of an entire team or allowing a mom-and-pop shop to design a professional advertising campaign without outside help.
  • it could lead to business models and creative ventures no one can predict.
  • sparked criticism that the companies are rushing to exploit an untested, unregulated and unpredictable technology that could deceive people, undermine artists’ work and lead to real-world harm.
  • the company held back the feature to better understand potential risks. As one example, she said, the model might be able to look at an image of a big group of people and offer up known information about them, including their identities — a possible facial recognition use case that could be used for mass surveillance.
  • OpenAI researchers wrote, “As GPT-4 and AI systems like it are adopted more widely,” they “will have even greater potential to reinforce entire ideologies, worldviews, truths and untruths, and to cement them or lock them in.”
  • “We can agree as a society broadly on some harms that a model should not contribute to,” such as building a nuclear bomb or generating child sexual abuse material, she said. “But many harms are nuanced and primarily affect marginalized groups,” she added, and those harmful biases, especially across other languages, “cannot be a secondary consideration in performance.”
  • OpenAI said its new model would be able to handle more than 25,000 words of text, a leap forward that could facilitate longer conversations and allow for the searching and analysis of long documents.
  • OpenAI developers said GPT-4 was more likely to provide factual responses and less likely to refuse harmless requests
  • Duolingo, the language learning app, has already used GPT-4 to introduce new features, such as an AI conversation partner and a tool that tells users why an answer was incorrect.
  • The company did not share evaluations around bias that have become increasingly common after pressure from AI ethicists.
  • GPT-4 will have competition in the growing field of multisensory AI. DeepMind, an AI firm owned by Google’s parent company Alphabet, last year released a “generalist” model named Gato that can describe images and play video games. And Google this month released a multimodal system, PaLM-E, that folded AI vision and language expertise into a one-armed robot on wheels: If someone told it to go fetch some chips, for instance, it could comprehend the request, wheel over to a drawer and choose the right bag.
  • The systems, though — as critics and the AI researchers are quick to point out — are merely repeating patterns and associations found in their training data without a clear understanding of what it’s saying or when it’s wrong.
  • GPT-4, the fourth “generative pre-trained transformer” since OpenAI’s first release in 2018, relies on a breakthrough neural-network technique in 2017 known as the transformer that rapidly advanced how AI systems can analyze patterns in human speech and imagery.
  • The systems are “pre-trained” by analyzing trillions of words and images taken from across the internet: news articles, restaurant reviews and message-board arguments; memes, family photos and works of art.
  • Giant supercomputer clusters of graphics processing chips are mapped out their statistical patterns — learning which words tended to follow each other in phrases, for instance — so that the AI can mimic those patterns, automatically crafting long passages of text or detailed images, one word or pixel at a time.
  • In 2019, the company refused to publicly release GPT-2, saying it was so good they were concerned about the “malicious applications” of its use, from automated spam avalanches to mass impersonation and disinformation campaigns.
  • Altman has also marketed OpenAI’s vision with the aura of science fiction come to life. In a blog post last month, he said the company was planning for ways to ensure that “all of humanity” benefits from “artificial general intelligence,” or AGI — an industry term for the still-fantastical idea of an AI superintelligence that is generally as smart as, or smarter than, the humans themselves.
Javier E

Scientists See Advances in Deep Learning, a Part of Artificial Intelligence - NYTimes.com - 1 views

  • Using an artificial intelligence technique inspired by theories about how the brain recognizes patterns, technology companies are reporting startling gains in fields as diverse as computer vision, speech recognition and the identification of promising new molecules for designing drugs.
  • They offer the promise of machines that converse with humans and perform tasks like driving cars and working in factories, raising the specter of automated robots that could replace human workers.
  • what is new in recent months is the growing speed and accuracy of deep-learning programs, often called artificial neural networks or just “neural nets” for their resemblance to the neural connections in the brain.
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  • With greater accuracy, for example, marketers can comb large databases of consumer behavior to get more precise information on buying habits. And improvements in facial recognition are likely to make surveillance technology cheaper and more commonplace.
  • Modern artificial neural networks are composed of an array of software components, divided into inputs, hidden layers and outputs. The arrays can be “trained” by repeated exposures to recognize patterns like images or sounds.
  • “The point about this approach is that it scales beautifully. Basically you just need to keep making it bigger and faster, and it will get better. There’s no looking back now.”
sissij

Color of 2017? Pantone Picks a Spring Shade - The New York Times - 0 views

  • Not just any old green, of course: Pantone 15-0343, colloquially known as greenery, which is to say a “yellow-green shade that evokes the first days of spring.”
  • That is, the Color of the Year for 2017.
  • “This is the color of hopefulness, and of our connection to nature. It speaks to what we call the ‘re’ words: regenerate, refresh, revitalize, renew. Every spring we enter a new cycle and new shoots come from the ground. It is something life affirming to look forward to.”
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  • Certainly the psychology of color ranges from the obvious (red represents aggression; pink is swaddling and calms people) to the chiaroscuro.
  • a combination of yellow and blue, or warmth and a certain cool,” she said. “It’s a complex marriage.”
  • You could argue that the selection is something of a self-fulfilling prophecy, except the point is that the products are already there (otherwise they couldn’t be marketed so immediately), which supports Pantone’s contention that it has identified a burgeoning trend.
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    I found this article very interesting because it talks about the different impression color can give us. Take the example in this article, the color of the year is greenery because it gives people a refreshing feeling. This is related to how we assign different meaning to things based on our pattern recognition. Since we always see color green in the nature, so it very easy for us to relate green with new life and energy. They way Ms. Eiseman said about color is also very interesting. She saw colors with significant meaning and though green is the kid of the complex marriage between blue and yellow. She even personified the colors. This shows how we tends to assign human properties to completely lifeless objects. --Sissi (12/9/2016)
Adam Clark

Why Conspiracy Theorists Are So Obsessed With JFK's "Umbrella Man" - 1 views

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    Our evolved tendency for pattern recognition and looking for significance in events screams that this anomaly must have a compelling explanation, and since it is associated with the assassination of a president, it must be a sinister one.
sissij

Want to Get From A to B Safer? The Color of Your Car Matters | Big Think - 2 views

  • If you’ve taken to the United States streets anytime lately, you may have noticed that most public school buses are a very particular shade of yellow. That shade is called National School Bus Glossy Yellow in Canada and the US, and it was specially designed by Dr. Frank Cyr.
  • It makes sense that yellow taxi cabs are safer than the blue ones.
  • What’s more, while the majority of those who are color blind have trouble distinguishing red from green, they can still see yellow just fine.
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  • Yellow is easy to see in the dim lights of early morning or late evening, and because it's seen across both the green and red cones in the eye, it pops in our vision faster than other colors.
  • Furthermore, the drivers tend to drive at similar speeds, so the color of the cabs isn’t attracting certain driver personalities. It is mostly linked to the color of the cab.
  • The long-standing association of yellow being the color of cabs means many people purchase cars that are specifically not yellow, because of the connection, but they will purchase blue cars. People are more careful around the yellow vehicle for the same reason they are careful around the school bus: they know what the color means.
  • Of course, this is all a short-term worry: we won't be at the mercy human error for much longer.
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    I think this is very interesting that even the color of a car can be associated with the accident rate of the taxi. The yellow color on the taxi make use of the pattern recognition in human mind as people tends to make connection between yellow and caution. I really like this idea because it shows that sometimes the fallacies in our logic can benefit us in the modern society. It is not totally useless. --Sissi (3/15/2017)
katedriscoll

Suhas Dara Blogs: "All knowledge depends on the recognition of patterns and anomalies."... - 0 views

  • In the study of TOK in DP-1 (11th grade), I have learnt about the ways of knowing, and two of the areas of knowledge - natural sciences and human sciences. Of all the discussions and explorations done into these areas of knowledge, there can be patterns observed in the methods of experimentation, data collection, data analysis and also assumptions being made when generalizing situations. In some of the above points, human sciences is similar to natural sciences, while in the others, the ideologies and working is different.
  • Natural sciences and human sciences for instance both use experiments as a form of data collection but the methods and outputs are different. Natural scientists have lesser moral values to take care of compared to human scientists such as psychologists. Psychologists are directly dealing with humans and hence need to take more ethical implications into consideration. Secondly, human scientists conduct experiments on a large set of people - not limited to one race or gender unless it is required. Natural scientists do not require survey type data. Here, a single scientist conducts the experiments. Both the types of experiments are empirical based though, direct experimentation is more in natural sciences while human sciences are more observation based. But experiments in human sciences have more unpredictable results due to what is known as the Hawthorne effect. This effect explains that when a particular group comes to know that they are under observation for a experiment or an analysis, they tend to be more productive. These cause errors in results of human science experiments especially the ones of psychology.
Javier E

Gamblers, Scientists and the Mysterious Hot Hand - The New York Times - 0 views

  • Psychologists who study how the human mind responds to randomness call this the gambler’s fallacy — the belief that on some cosmic plane a run of bad luck creates an imbalance that must ultimately be corrected, a pressure that must be relieved
  • The opposite of that is the hot-hand fallacy — the belief that winning streaks, whether in basketball or coin tossing, have a tendency to continue
  • Both misconceptions are reflections of the brain’s wired-in rejection of the power that randomness holds over our lives. Look deep enough, we instinctively believe, and we may uncover a hidden order.
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  • A working paper published this summer has caused a stir by proposing that a classic body of research disproving the existence of the hot hand in basketball is flawed by a subtle misperception about randomness. If the analysis is correct, the possibility remains that the hot hand is real.
  • We mortals can benefit, at least in theory, from islands of predictability — a barely perceptible tilt of a roulette table that makes the ball slightly more likely to land on one side of the wheel than the other
  • The same is true for the random walk of the stock market. Becoming aware of information before it has propagated worldwide can give a speculator a tiny, temporary edge. Some traders pay a premium to locate their computer servers as close as possible to Lower Manhattan, gaining advantages measured in microseconds.
  • Taken to extremes, seeing connections that don’t exist can be a symptom of a psychiatric condition called apophenia. In less pathological forms, the brain’s hunger for pattern gives rise to superstitions (astrology, numerology) and is a driving factor in what has been called a replication crisis in science
  • I know it sounds crazy but when you average the scores together the answer is not 50-50, as most people would expect, but about 40-60 in favor of tails.
  • There is not, as Guildenstern might imagine, a tear in the fabric of space-time. It remains as true as ever that each flip is independent, with even odds that the coin will land one way or the other. But by concentrating on only some of the data — the flips that follow heads — a gambler falls prey to a selection bias.
  • basketball is no streakier than a coin toss. For a 50 percent shooter, for example, the odds of making a basket are supposed to be no better after a hit — still 50-50. But in a purely random situation, according to the new analysis, a hit would be expected to be followed by another hit less than half the time. Finding 50 percent would actually be evidence in favor of the hot hand
  • Dr. Gilovich is withholding judgment. “The larger the sample of data for a given player, the less of an issue this is,” he wrote in an email. “Because our samples were fairly large, I don’t believe this changes the original conclusions about the hot hand. ”
  • Take a fair coin — one as likely to land on heads as tails — and flip it four times. How often was heads followed by another head?
  • For all their care to be objective, scientists are as prone as anyone to valuing data that support their hypothesis over those that contradict it. Sometimes this results in experiments that succeed only under very refined conditions, in certain labs with special reagents and performed by a scientist with a hot hand.
  • We’re all in the same boat. We evolved with this uncanny ability to find patterns. The difficulty lies in separating what really exists from what is only in our minds.
Javier E

Computers Jump to the Head of the Class - NYTimes.com - 0 views

  • Tokyo University, known as Todai, is Japan’s best. Its exacting entry test requires years of cramming to pass and can defeat even the most erudite. Most current computers, trained in data crunching, fail to understand its natural language tasks altogether. Ms. Arai has set researchers at Japan’s National Institute of Informatics, where she works, the task of developing a machine that can jump the lofty Todai bar by 2021. If they succeed, she said, such a machine should be capable, with appropriate programming, of doing many — perhaps most — jobs now done by university graduates.
  • There is a significant danger, Ms. Arai says, that the widespread adoption of artificial intelligence, if not well managed, could lead to a radical restructuring of economic activity and the job market, outpacing the ability of social and education systems to adjust.
  • Intelligent machines could be used to replace expensive human resources, potentially undermining the economic value of much vocational education, Ms. Arai said.
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  • “Educational investment will not be attractive to those without unique skills,” she said. Graduates, she noted, need to earn a return on their investment in training: “But instead they will lose jobs, replaced by information simulation. They will stay uneducated.” In such a scenario, high-salary jobs would remain for those equipped with problem-solving skills, she predicted. But many common tasks now done by college graduates might vanish.
  • Over the next 10 to 20 years, “10 percent to 20 percent pushed out of work by A.I. will be a catastrophe,” she says. “I can’t begin to think what 50 percent would mean — way beyond a catastrophe and such numbers can’t be ruled out if A.I. performs well in the future.”
  • A recent study published by the Program on the Impacts of Future Technology, at Oxford University’s Oxford Martin School, predicted that nearly half of all jobs in the United States could be replaced by computers over the next two decades.
  • Smart machines will give companies “the opportunity to automate many tasks, redesign jobs, and do things never before possible even with the best human work forces,” according to a report this year by the business consulting firm McKinsey.
  • Advances in speech recognition, translation and pattern recognition threaten employment in the service sectors — call centers, marketing and sales — precisely the sectors that provide most jobs in developed economies.
  • Gartner’s 2013 chief executive survey, published in April, found that 60 percent of executives surveyed dismissed as “‘futurist fantasy” the possibility that smart machines could displace many white-collar employees within 15 years.
  • Kenneth Brant, research director at Gartner, told a conference in October: “Job destruction will happen at a faster pace, with machine-driven job elimination overwhelming the market’s ability to create valuable new ones.”
  • Optimists say this could lead to the ultimate elimination of work — an “Athens without the slaves” — and a possible boom for less vocational-style education. Mr. Brant’s hope is that such disruption might lead to a system where individuals are paid a citizen stipend and be free for education and self-realization. “This optimistic scenario I call Homo Ludens, or ‘Man, the Player,’ because maybe we will not be the smartest thing on the planet after all,” he said. “Maybe our destiny is to create the smartest thing on the planet and use it to follow a course of self-actualization.”
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