The height of intelligence | Dean Burnett | Science Tall people are smarter. This is a phenomenon with scientific research to back it up. It's a small effect, it's not an absolute; I'm not saying Andre the Giant was the intellectual superior of Robert Hooke, you'll still find plenty of smarter-than-average shorter people, and many tall people who clearly … aren't. But the effect does appear to be persistent. There are numerous explanations for this. Are the genes that determine height and intelligence associated? Or perhaps people who were both taller and smarter get more mating opportunities, making it an evolved tendency? But claims like this again bring up the question of what intelligence is. How do we even measure intelligence? Still, IQ tests are often used, and inform a lot of what we know (or think we know) about intelligence. How many scientists does it take to change a light bulb? Intelligence also has a strong cultural context. There's also a well-known example of Cole et al and their dealings with the remote Kpelle tribe.
The top 10 funding application errors Many charities see their applications for funding be rejected The Directory of Social Change estimates that ineligible applications made to the largest trusts in 2010 equated to seven years of wasted effort. This pointless exertion seems not to have lessened since then. According to the latest figures from the Big Lottery Fund, 46 per cent of applications to its Reaching Communities programme between May and July this year were ineligible. So where are charities going wrong? 1. "If only they had read our eligibility criteria, they would clearly see we don't fund that" is a perennial complaint from funders. The trust also gets a lot of applications from people who want to run welfare projects, even though it clearly states in its entry criteria that it does not fund such schemes. Comic Relief has received applications on behalf of an HIV project in Tanzania for a fund that operates only in Stoke-on-Trent. 2. 3. 4. 5. 6. 7. Large funders welcome phone calls to discuss potential projects.
Deep Learning Tutorials ě°˝€” DeepLearning v0.1 documentation Deep Learning is a new area of Machine Learning research, which has been introduced with the objective of moving Machine Learning closer to one of its original goals: Artificial Intelligence. See these course notes for a brief introduction to Machine Learning for AI and an introduction to Deep Learning algorithms. Deep Learning is about learning multiple levels of representation and abstraction that help to make sense of data such as images, sound, and text. For more about deep learning algorithms, see for example: The tutorials presented here will introduce you to some of the most important deep learning algorithms and will also show you how to run them using Theano. Theano is a python library that makes writing deep learning models easy, and gives the option of training them on a GPU. The algorithm tutorials have some prerequisites. The code is available on the Deep Learning Tutorial repositories. The purely supervised learning algorithms are meant to be read in order: LSTM network
Visualizing Algorithms The power of the unaided mind is highly overrated… The real powers come from devising external aids that enhance cognitive abilities. —Donald Norman Algorithms are a fascinating use case for visualization. But algorithms are also a reminder that visualization is more than a tool for finding patterns in data. #Sampling Before I can explain the first algorithm, I first need to explain the problem it addresses. Light — electromagnetic radiation — the light emanating from this screen, traveling through the air, focused by your lens and projected onto the retina — is a continuous signal. This reduction process is called sampling, and it is essential to vision. Sampling is made difficult by competing goals. Unfortunately, creating a Poisson-disc distribution is hard. You can see from these dots that best-candidate sampling produces a pleasing random distribution. Here’s how it works: For each new sample, the best-candidate algorithm generates a fixed number of candidates, shown in gray. #Sorting
Why We Need to Redefine Intelligence - HBR IdeaCast An interview with Scott Barry Kaufman adjunct assistant professor of psychology at New York University and author of Ungifted: Intelligence Redefined. Download this podcast SARAH GREEN: Welcome to the HBR IdeaCast from Harvard Business Review. I’m Sarah Green. SCOTT BARRY KAUFMAN: Thank you. SARAH GREEN: So I thought we would just start with why redefine intelligence? SCOTT BARRY KAUFMAN: Yeah, it’s a great question. But what I’ve done in trying to look at all different kinds of minds and ways that we can achieve success in the real world once we get out of school, and the importance of things such as inspiration, and motivation, and engagement in something that personally interests you– what I started to notice was a repeating pattern over and over again. It’s almost like there’s a lot of intellectual capacity hidden in a lot of people. SCOTT BARRY KAUFMAN: I absolutely will. So they may be adding another intelligence. What I argue for is the shift to the personal developmental level.
Home Bayes' Theorem Bayes' Theorem for the curious and bewildered; an excruciatingly gentle introduction. Your friends and colleagues are talking about something called "Bayes' Theorem" or "Bayes' Rule", or something called Bayesian reasoning. They sound really enthusiastic about it, too, so you google and find a webpage about Bayes' Theorem and... It's this equation. That's all. So you came here. Why does a mathematical concept generate this strange enthusiasm in its students? Soon you will know. While there are a few existing online explanations of Bayes' Theorem, my experience with trying to introduce people to Bayesian reasoning is that the existing online explanations are too abstract. Or so they claim. And let's begin. Here's a story problem about a situation that doctors often encounter: What do you think the answer is? Next, suppose I told you that most doctors get the same wrong answer on this problem - usually, only around 15% of doctors get it right. Do you want to think about your answer again?
Aliasing - Wikipedia, la enciclopedia libre Properly sampled image of brick wall. Aliasing can occur in signals sampled in time, for instance digital audio, and is referred to as temporal aliasing. Aliasing can also occur in spatially sampled signals, for instance digital images. Aliasing in spatially sampled signals is called spatial aliasing. Description Aliasing example of the A letter in Times New Roman. When a digital image is viewed, a reconstruction is performed by a display or printer device, and by the eyes and the brain. An example of spatial aliasing is the Moiré pattern one can observe in a poorly pixelized image of a brick wall. Temporal aliasing is a major concern in the sampling of video and audio signals. In video or cinematography, temporal aliasing results from the limited frame rate, and causes the wagon-wheel effect, whereby a spoked wheel appears to rotate too slowly or even backwards. Bandlimited functions Bandpass signals Sampling sinusoidal functions = 1. = 0.9 and = 0.1. are and is where ).
The Future of Intelligence Cadell Last, Adam Ford By Cadell Last Human intelligence, like everything related to biological systems, is an evolving phenomenon. It has not been static in the past, and will not persist in its current form into the future. The human-version of intelligence has made our species the most powerful agent of change ever produced by the earth's biosphere. Therefore, understanding its evolutionary past should be a primary concern for evolutionary theorists. Clearly the human ability to engage in these novel behaviours is dependent on the human brain. a comparatively short period of evolutionary time, hominid brain size exploded. Before the emergence of our genus, apes had existed for approximately 18 million years. Recent studies, like those conducted on the 2.5 million-year-old Australopithecus africanus skull known as Taung Child suggest that human-like brain growth had already started in the precursor species to Homo. The Explosion Global Brain A) how energy-intensive they are
Read 700 Free eBooks Made Available by the University of California Press The University of California Press e-books collection holds books published by UCP (and a select few printed by other academic presses) between 1982-2004. The general public currently has access to 770 books through this initiative. The collection is dynamic, with new titles being added over time. Readers looking to see what the collection holds can browse by subject. The curators of the site have kindly provided a second browsing page that shows only the publicly accessible books, omitting any frustrating off-limits titles. The collection’s strengths are in history (particularly American history and the history of California and the West); religion; literary studies; and international studies (with strong selections of Middle Eastern Studies, Asian Studies, and French Studies titles). Sadly, you can’t download the books to an e-reader or tablet. Rebecca Onion is a writer and academic living in Philadelphia. Related Content: 30 Free Essays & Stories by David Foster Wallace on the Web