Helge Scherlund's eLearning News

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Game On: Why College Admission Is Rigged and How to Beat the System | Books - Macmillan

Check out this book entitled Game On: Why College Admission Is Rigged and How to Beat the System by Susan F. Paterno, director of the journalism program at Chapman University.

Game On:
Why College Admission Is Rigged and How to Beat the System

Director of the Chapman journalism program—and mother of four recent college grads—Susan F. Paterno leads you through the admissions process to help you and your family make the best decision possible.

How is it possible that Harvard is more affordable for most American families than their local state university? Or that up to half of eligible students receive no financial aid? Or that public universities are rejecting homegrown middle- and working-class applicants and instead enrolling wealthy out-of- state students? College admission has escalated into a high-stakes game of emotional and financial survival. How is the deck stacked against you? And what can you do about it?

READ THE FULL EXCERPT →

Source: Macmillan 

Future artificial intelligence will happen at the edge | Opinion - IOL

 “Edge computing” has become a buzzword just like “Internet of Things” (IoT) and “cloud computing” in the past. In addition, the COVID-19 pandemic has tremendously accelerated the adoption of edge computing by Professor Louis CH Fourie, technology strategist.

Photo: IOL

According to the 2021 State of the Edge Report by the Linux Foundation, specifically digital health care, manufacturing, and retail business will increase their use of edge computing in the coming years, pushing enterprise-generated data created and processed outside the cloud from 10% to 75% by 2022....

Edge computing

Edge computing refers to computation and data storage that are located close to where it is needed and is done at or near the source of the data, instead of relying on the centrally located cloud at one of the major data centres to do all the processing work...

Edge artificial intelligence (AI)

Edge computing is a very powerful paradigm shift, but it is even more powerful when combined with AI. Most AI processes are carried out in the cloud and need considerable processing capacity. Edge AI, however, requires very little or even no cloud infrastructure beyond the initial training phase. Edge AI only requires a microprocessor and sensors to process the data and make predictions in real time.

Read more... 

Source: IOL

Will AI Make Interpreters and Sign Language Obsolete? | Innovation - Interesting Engineering

Arificial intelligence is changing how we view language— and how we're making it more accessible, according to Jenn Halweil, Chief Story Engineer and Skylar Walters, Research Intern at GoBeyond Lab.

Photo: Markus Spiske/Unsplash In the age of the internet, people are being drawn closer and closer— you can Snapchat your friend from Turkey, video call your parents on their fancy vacation, send a quick text to your old pen pal (now your new keyboard pal) in Japan. 

But as the world is drawn closer together, our attention spans are becoming more and more commodified. We spend hours scrolling through Instagram, while spending less time engaging with each other directly. 

Ironically, artificial intelligence is now changing that...

Technology has incredible potential to bring people together, but when people are left out, whether as a result of disabilities, race, ethnicity, or otherwise, it can be a divisive and isolating force. Thanks to natural language processing, we’re starting to fill in these gaps between people to build a more accessible future. 

Read more... 

Source: Interesting Engineering 

The danger of anthropomorphic language in robotic AI systems | AI - Brookings Institution

Cindy M. Grimm, professor in the School of Mechanical, Industrial, and Manufacturing Engineering at Oregon State University argues, When describing the behavior of robotic systems, we tend to rely on anthropomorphisms. 

A visitor puts her hand against the glass in front of “Nexi” robot during the “ROBOTS” exhibition at the Hong Kong Science Museum in Hong Kong on May 8, 2021. The exhibition explores the 500-year story of humanoid robots and the artistic and scientific quest to understand what it means to be human.
Photo: Miguel Candela / SOPA Images/Sip via Reuters Connect

Cameras “see,” decision algorithms “think,” and classification systems “recognize.” But the use of such terms can set us up for failure, since they create expectations and assumptions that often do not hold, especially in the minds of people who have no training in the underlying technologies involved. This is particularly problematic because many of the tasks we envision for robotic technologies are typically ones that humans currently do (or could do) some part of. The natural tendency is to describe these tasks as a human would using the “skills” a human has—which may be very different from how a robot performs the task. If the task specification relies only on “human” specifications—without making clear the differences between “robotic” skills and “human” ones—then the chance of a misalignment between the human-based description of the task and what the robot actually does will increase.

Designing, procuring, and evaluating AI and robotic systems that are safe, effective, and behave in predictable ways represents a central challenge in contemporary artificial intelligence, and using a systematic approach in choosing the language that describes these systems is the first step toward mitigating risks associated with unexamined assumptions about AI and robotic capabilities. Specifically, actions we consider simple need to be broken down and their components carefully mapped to their algorithmic and sensor counterparts, while avoiding the pitfalls of anthropomorphic language. This serves two purposes. First, it helps to reveal underlying assumptions and biases by more clearly defining functionality. Second, it helps non-technical experts better understand the limitations and capabilities of the underlying technology, so they can better judge if it meets their application needs...

One could argue that the two statements “The robot sees an apple” and “The robot detects an object that has the appearance of an apple” are pretty much the same, but in their assumptions of cognitive ability, they are very different. “See” carries with it a host of internal models and assumptions: Apples are red or green, fit in the hand, smell like apples, crunch when you bite them, are found on trees and fruit bowls, etc. We are used to seeing apples in a wide variety of lighting conditions and varying view points—and we have some notion of the context in which they are likely to appear. We can separate out pictures of apples from paintings or cartoons. We can recognize other objects in a scene that tell us if something is likely to be an apple or another red object. In other words, we bring an entire internal representation of what an apple is when looking at an image—we don’t just see the pixels. “Detect,” on the other hand, connotes fewer internal assumptions and evokes, instead, the image of someone pointing a sensor at an apple and having it go “ding.” This is more akin to how a robot “sees” and how it internally represents an apple. A sensor (the camera) is pointed at the apple, and the numeric distribution of pixel values is examined. If the pixel values “match” (numerically) the previously-learned examples of pixel distributions for images labeled as “apples,” the algorithm returns the symbol “apple.” How does the algorithm get this set of example pixel distributions? Not by running around and picking up objects and seeing if they smell and taste like apples, but from millions of labeled images (thank you, Flickr). These images are largely taken with good lighting and from standard viewpoints, which means that the algorithm struggles to detect an apple in bad lighting and from odd angles, nor does it know how to distinguish between an image that matches its criteria of being an apple but isn’t one. Hence, it is more accurate to say that the robot has detected an object that has the appearance of an apple.

Read more... 

Source: Brookings Institution

Miami middle school students study STEM, robotics during summer vacation | Miami-Dade County - WPLG Local 10

Middle school students across Miami-Dade County are embarking on a summer learning program to learn about STEM by Hatzel Vela, Reporter at WPLG Local 10.

Photo: Screenshot from Local10.com's Video.

It’s called the Verizon Innovative Learning Program — and it’s finally all in-person.

The program is a free, month-long extensive STEM program for about one hundred young students...

The lack of person-to-person interaction, the online learning is arguably responsible for what many are calling the “COVID gap,” a pandemic-related academic setback for even the smartest kids, like those in this group.

Read more... 

Source: WPLG Local 10

Cybersecurity is the next frontier for AI and ML | The Machine - VentureBeat

This story originally appeared on Raffy.ch. Copyright 2021

Raffael Marty, technology executive, entrepreneur observes , Before diving into cybersecurity and how the industry is using AI at this point, let’s define the term AI first. 

Photo: Shutterstock

Artificial intelligence (AI), as the term is used today, is the overarching concept covering machine learning (supervised, including deep learning, and unsupervised), as well as other algorithmic approaches that are more than just simple statistics. These other algorithms include the fields of natural language processing (NLP), natural language understanding (NLU), reinforcement learning, and knowledge representation. These are the most relevant approaches in cybersecurity.

Given this definition, how evolved are cybersecurity products when it comes to using AI and ML?...

How AI is used in security

Generally, I see the correct application of AI in the supervised machine learning camp where there is a lot of labeled data available: malware detection (telling benign binaries from malware), malware classification (attributing malware to some malware family), document and website classification, document analysis, and natural language understanding for phishing and BEC detection. There is some early but promising work being done on graph (or social network) analytics for communication analysis. But you need a lot of data and contextual information that is not easy to get your hands on. Then, there are a couple of companies that are using belief networks to model expert knowledge, for example, for event triage or insider threat detection. But unfortunately, these companies are a dime a dozen.

Read more... 

Source: VentureBeat 

Art and the Algorithm: Computer Program Predicts Painting Preferences | Informatics - Technology Networks

This article has been republished from the following materials. Note: material may have been edited for length and content. For further information, please contact the cited source.

New study offers insight into how people make aesthetic judgments by California Institute of Technology

Impressionist painting by Worthington Whittredge.
Photo:  Smithsonian American Art Museum, L.E. Katzenbach Fund
Do you like the thick brush strokes and soft color palettes of an impressionist painting such as those by Claude Monet? 

Or do you prefer the bold colors and abstract shapes of a Rothko? Individual art tastes have a certain mystique to them, but now a new Caltech study shows that a simple computer program can accurately predict which paintings a person will like.

The new study, appearing in the journal Nature Human Behaviour, utilized Amazon's crowdsourcing platform Mechanical Turk to enlist more than 1,500 volunteers to rate paintings in the genres of impressionism, cubism, abstract, and color field. The volunteers' answers were fed into a computer program and then, after this training period, the computer could predict the volunteers' art preferences much better than would happen by chance...

In this case, the deep-learning approach did not include any of the selected low- or high-level visual features used in the first part of the study, so the computer had to "decide" what features to analyze on its own.

"In deep-neural-network models, we do not actually know exactly how the network is solving a particular task because the models learn by themselves much like real brains do," explains Iigaya. "It can be very mysterious, but when we looked inside the neural network, we were able to tell that it was constructing the same feature categories we selected ourselves." These results hint at the possibility that features used for determining aesthetic preference might emerge naturally in a brain-like architecture.

Read more...

Additional resources

Reference: Iigaya K, Yi S, Wahle IA, Tanwisuth K, O’Doherty JP. Aesthetic preference for art can be predicted from a mixture of low- and high-level visual features. Nat Hum Behav. 2021;5(6):743-755. doi: 10.1038/s41562-021-01124-6

Source: Technology Networks  

33 New Skills You Can Learn on LinkedIn Learning This Week | New courses - LinkedIn Learning Blog

Each week presents an opportunity to learn new skills to help us navigate this unique moment in our lives and careers, Rachel Parnes reports.

Photo: LinkedIn Learning BlogAt LinkedIn Learning, we want to provide the online learning courses you need to learn those skills. Each week we add to our 16,000+ course library. This past week we added 33 courses. What can you expect from the new additions? 

Whether you’re learning to get started as a full-stack web developer or honing your AWS skills, we’ve got you covered on those topics and more. Check out one of the 33 new courses this week.

Looking for resources to help you get your next job? We can help with that too. Find courses that map to the top in-demand jobs, free until December 31, 2021, at opportunity.Linkedin.com.   

The new courses now available on LinkedIn Learning are:

Read more... 

Source: LinkedIn Learning Blog

Composing with geometry: This Venezuelan guitarist makes music using a compass and a ruler | Music & Nightlife - Miami Herald

Lorena Cespedes, Colombian student at Florida International University majoring in journalism says,Aureo Puerta Carreño makes geometry his muse. The Venezuelan guitarist, 28, created a method to compose music, using geometric patterns. 

Venezuelan guitarist Aureo Puerta Carreño uses geometry to compose music.
Photo: Handout

Musicians and mathematicians have applauded his work. His compositions have been played at guitar festivals in the United States, and in 2020 he was named composer-in- residence by the Miami Symphony Orchestra.

“I compose my music through geometry, and for this, I only use a compass and a ruler,” he said. “It is a system that I invented six years ago, by which a matrix of hexagons becomes my canvas, where I am going to write the notes. In short, I can put music to any object I want.”...

“But the squares on the paper did not help me to place the 12 notes of our musical tonal system, since a square only has four sides,” he said. “One day watching a program about the importance of bees, the hexagon came to mind, and that was the thing that led to the discovery of the geometric pattern on which music is based.”...

“In the academy, we learn with the traditional method,” said Vicky Beltran, a student. “Professor Puerta has taught us with his method a few times, and it has been fun. If he writes all the notes on the hexagon’s left side, we know that we are playing a happy song, and if it is on the right side, we are playing a sad song.” 

Read more... 

Source: Miami Herald

These Are the 10 Hardest Math Problems That Remain Unsolved | Science - Popular Mechanics

The smartest people in the world can't crack them. Maybe you'll have better luck.

Photo: Popular Mechanics

For all of the recent strides we've made in the math world—like a supercomputer finally solving the Sum of Three Cubes problem that puzzled mathematicians for 65 years—we're forever crunching calculations in pursuit of deeper numerical knowledge. Some math problems have been challenging us for centuries, and while brain-busters like these hardest math problems that follow may seem impossible, someone is bound to solve 'em eventually. Maybe.  

For now, you can take a crack at the hardest math problems known to man, woman, and machine.

Read more... 

Source: Popular Mechanics

What Can You Do With A Master In Business Analytics? | FinTech - BusinessBecause

Considering a Master’s in Business Analytics? Here are five paths you could take when you graduate by Imogen Brighty Potts, Editorial Assistant.

Business Analytics Masters courses focus on applying data to real world problems | © MITSloan

If you want to become a tech-savvy professional, without sacrificing a solid grounding in business, a Master in Business Analytics could be the right program for you. 

Roles in big tech and data that require this level of knowledge are emerging all the time. A 2020 Microsoft report predicted that the number of technology-focused jobs would grow from 41 million in 2020 to 190 million in 2025.

This growth is opening up new opportunities for ambitious Master in Business Analytics grads. But which of these career paths are the best? 

Here are five exciting career paths that you could follow as a Master in Business Analytics alum. We’ve also scoured Glassdoor to find out what salaries and perks these careers command.

Read more... 

Source: BusinessBecause 

Meet Kathleen Lonsdale, the physicist and prison reformer who cracked benzene’s code | Science Heroes - Massive Science

Josseline Ramos-Figueroa, PhD Student in Chemistry observes, Lonsdale assembled her own X-ray crystallography laboratory from scratch to solve a century-old mystery.

A pamphlet written by Kathleen Lonsdale called “Prison for Women,” an account of her time imprisoned
Photo: Via Wikimedia

“I had never heard of Kathleen Lonsdale until today,” a professor wrote to me in a recent email. Though I’m a chemist, I hadn’t either. 

A physicist by training, Kathleen Lonsdale is most famous for revealing the shape of the benzene ring — a molecular scaffold with unusual chemical properties that was considered a mystery to chemists for many years. She was the first to uncover the benzene ring’s dimensions and atomic structure. Lonsdale, who was recently commemorated by English Heritage with a London Blue Plaque on the 50th anniversary of her death, also played a fundamental role in establishing X-ray crystallography — technology discovered in the 20th century that allowed scientists to “see” atoms and their spatial arrangement within a molecule. The technique was later critical in the structural studies of a vast number of molecules.

Lonsdale was brilliant, hardworking, and adaptable. Born on January 28, 1903, in Newbridge, Ireland, Lonsdale was the youngest of ten children. Her love for math and physics started during her late school years... 

It was a remarkable achievement at a time where all calculations had to be done by hand. But she didn’t stop there. Lonsdale next studied the structure of hexachlorobenzene, another benzene derivative, using an additional mathematical analysis known as the Fourier series. This work was well received by Ingold, who said, “The calculations must have been dreadful, but one paper like this brings more certainty into organic chemistry than generations of activity by us professionals.”

Read more... 

Source: Massive Science  

What Is Actuarial Science? (+Exams, Jobs, and Salaries) | G2

When it comes to choosing a career, it’s always important to determine a path you already love, inform Mara Calvello, Content Marketing Manager at G2.

Photo: G2For instance, if you don’t enjoy dealing with teenagers, it wouldn’t be a good idea to become a high school teacher.

However, if you’ve always loved math, charts, graphs, and statistics, then going down the path of an actuarial scientist might be the right choice for you. Before you dive in with both feet, first learn more about what a role in actuarial science looks like, and what the road to a career will be like.

Jump ahead if you want to learn about something specific about actuarial science:

What is actuarial science?

Actuarial science is the study of applying mathematical and statistical methods to estimate risk in insurance, finance, and other industries.

If you’re interested in this line of work, know that’ll you have to bunker down, hit the books, and get ready to do some serious studying.

Actuarial science degree

If you’re a person entering college who loves math, finance, statistics, and business, an actuarial science degree may be right for you.

Because of this, college students should major in either economics, finance, math, or statistics. There’s also the option of majoring in actuarial science, which seems like the obvious route, but know that you have options. It’s also wise to take a few computer science courses to expand your knowledge and be more well-rounded in the field.

Read more... 

Source: G2

What an Actuary Does and How to Become One | Education - U.S. News & World Report

Actuarial science involves assessing financial risk and requires mathematical ability, experts say.

Actuaries help to ensure that there are sufficient financial safety nets to guard against financial calamities.
Photo: Getty ImagesSomeone intrigued by the prospect of assessing and managing risk may enjoy a career as an actuary, a business professional whose job involves consistently and accurately predicting the likelihood of misfortune in the midst of uncertainty and its potential financial cost.

 What Actuarial Science Is and Why It Matters

"Actuarial science is about using math to assess what will happen next," Amy Timmons – a Phoenix-based vice president, senior consultant and actuary with Segal, a consulting firm with U.S. and Canadian offices – explained in an email.

What an Actuary Is

Actuaries say they play an important role in society by helping to ensure that there are sufficient financial safety nets to guard against financial calamities...

This in-demand and lucrative profession demands an aptitude for math and statistics. It requires making sense of data and discerning patterns in numbers, so individuals who work in this field need to have strong quantitative skills, an eye for detail and a meticulous approach, actuaries emphasize.

"You need a love of mathematics and numbers – that is core to being an actuary," Timmons says. "Everything else is negotiable. There are actuarial positions for introverts, extroverts, people who like to talk and work with people, people who like to travel, people who want to stay home, people who only want to work with numbers, etc."

Read more... 

Source: U.S. News & World Report

29 Great Catholic Mathematicians You Should Know | Mathematics - National Catholic Register

 “It seems to me almost incredible,” said Pope Benedict XVI in 2006, “that an invention of the human mind and the structure of the universe coincide. Mathematics, which we invented, really gives us access to the nature of the universe and makes it possible for us to use it.”, reports Angelo Stagnaro ("Erasmus"), performs as a stage magician and mentalist and divides his time between Europe and North America. 

Anonymous, “God the Geometer,” ca. 1220
Photo: Wikimedia Commons

Do your eyes glaze over when your kids ask for help on their math homework? There are a lot of Catholics you might want to thank for that before you tear your hair out. In this light, I’ve decided to highlight the accomplishments of several important clerics and lay Catholic mathematicians...

For those interested in learning about the great contributions Catholics have made to the sciences and, indeed, to the laying of the foundations of Western science and civilization, I direct you to these two articles: “A List of 244 Priest-Scientists (From Acosta to Zupi)” and “A Short List of Lay Catholic Scientists.”

Read more... 

Source: National Catholic Register

The best new summer books: 10 titles that should be on your reading list | Books - The National

These blistering works of fiction, from the likes of Elif Shafak, Paula Hawkins and Leila Slimani, will keep you turning the page, according to Ben East, award-winning arts, culture, travel and sports journalist based in Manchester.

Whether you're avoiding the hot weather by lounging at home, or escaping for a beach day, an enthralling read should be close at hand.

Here, The National has rounded up some of the best new books, out now or coming soon, to help you while away those summer days.

Read more... 

Source: The National

20 best books in 2021, according to Amazon's editors | Books - NBC News

Looking for a new novel? Amazon Books editors just released a list of their favorite books so far that were published this year by Sarah Gelman, Amazon Book Review.

Among Amazon Books editors’ favorite books this year is one described as a “Rubik’s Cube of twists.”  Photo: AmazonAhead of summer reading lists traditionally released around this time (the official start of the season arrives June 20 alongside Father’s Day), Amazon has launched its own books list: the Best Books of the Year So Far.

“The editors collectively read thousands of books each year, passionately debate them, and create editorially curated lists of recommendations each month,” explained Sarah Gelman, Amazon Books’ editorial director. “When the year is halfway through, we comb through the titles that made the cut and select the best of the best. While many of these books end up being bestsellers and customer favorites, we get especially excited about highlighting literary gems customers might not otherwise hear about.” 

Read more... 

Source: NBC News

Math Books you should read in 2021 | Mathematics - Medium

Learn how mathematics influence every aspect of our life, writes Przemek Chojecki, AI entrepreneur with a PhD in mathematics, published in Data Science Rush. 

Math books you should read in 2021. Understand the world we live in through data!

Mathematics is behind all the recent breakthroughs. It’s the reason we can push technology forward every year. We use mathematics even though we might not be aware of it. That’s the reason why everyone should have a basic understanding of how maths really comes into play in a modern world. The following list of books will allow you to get a sense of that without having to get technical details and complicated proofs. 

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Source: Medium

Be there or be square: the strange art of lecturing | Teaching and learning - Times Higher Education

A PowerPoint marathon or a ‘captured’ lecture will always be a pale i mitation of a live experience, in which an expert practitioner taps into ‘the dangerous energy of all those watching eyes’, says Richard Sugg, has lectured in English and cultural history at the universities of Cardiff and Durham.

 Photo: Getty ImagesNine o’clock on a cold, dark, winter’s morning. You are trapped. Two hundred pairs of eyes are staring down intently at you from a height. Deep in the ancient reptile stem of the brain, angry voices shout at you: “Why are 200 people all staring at you from a height? Because they are going to kill you and eat you. Why else?”

In almost 20 years of lecturing – at the universities of Southampton, Cardiff and Durham – they never did. And yet a nagging edge of this fear always remains for many lecturers, even when something alarmingly extraordinary becomes more ordinary over time. The sense that eyes are more of a problem than bodies was pinpointed nicely by a colleague of mine at Southampton. Her solution to lecturing nerves was simple: she took off the glasses she wore for distance vision.

In the early days and weeks of mastering this art, the theory of the carefully written lecture can easily melt under the fierce heat of all those curious eyes. For those who find this a problem, it is a problem of pressure, of too much presence, too much energy, compressed into one space for a brief time.

Who would have guessed how many lecturers would miss all this during the long months of lockdown?...

The furthest extreme of the PowerPoint lecture is an obsessively tech-dominated 50 minutes of images and text in a dark room. At one level, with so much textual content and quotation projected up in cinematic fashion, we already find a reframing of that basic question: are you there? Is the audience listening to you or are they reading a summarised book chapter? After all, if some students find that there is too little of you to bother getting up for a 9am slot, then why shouldn’t they just plead sick and call up the PowerPoint version at a later date?

But the real point is that the students can barely see the lecturer, even if they want to. And if they cannot see your eyes, they are not just losing you. They are losing the excitement of real knowledge, there in your eyes: something really shown, not merely said; something very hard to fake.

Read more... 

Source: Times Higher Education

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