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Thursday, April 25, 2019

Dragonfly 4.0 Is Here! the Engine of Scientific Imaging | Deep Learning - AiThority

Based in Montreal, Canada, Object Research Systems (ORS) Inc., is excited to announce the release of Dragonfly 4.0, which brings major enhancements and improvements to image processing and analysis workflows, as AIT News Desk reports. 
 

Designed for researchers and engineers in the fields of material and life sciences, Dragonfly provides qualitative and quantitative tools for material characterization, surface analysis, process evaluation, quality control testing or any analysis function that requires a high degree of accuracy. With the ability to handle large datasets, Dragonfly allows for extensible workflows, sophisticated 2D, 3D, 4D, nD visualizations, thorough segmentation routines, hyperspectral functions and deep learning capabilities.
Read more...

Source: AiThority

What is machine learning and why should I care? | Tow Center - Columbia Journalism Review

You may not realize it, but you’ve probably already used machine learning technology in your journalism, explains Nicholas Diakopoulos, assistant professor at Northwestern University School of Communication, author of the forthcoming book "Automating the News: How Algorithms are Rewriting the Media" on automation and algorithms in news media.
 
Photo: Adobe Stock

Perhaps you used a service like Trint to transcribe your interviews, punched in some text for Google to translate, or converted the Mueller Report into readable text. And if you haven’t used it yourself, machine learning is probably at work in the bowels of your news organization, tagging text or photos so they can be found more easily, recommending articles on the company website or social media to optimize their reach or stickiness, or trying to predict who to target for subscription discounts.

Machine learning has already infiltrated some of the most prosaic tasks in journalism, speeding up and making possible stories that might otherwise have been too onerous to report. We’re already living the machine-learning future. But, particularly on the editorial side, we’ve only begun to scratch the surface.

To be clear: I’m not here to hype you on a fabulous new technology. Sorry, machine learning is probably not going to save the news industry from its financial woes. But there’s nonetheless a lot of utility for journalists to discover within it. What else can machine learning do for the newsroom? How can journalists use it to enhance their editorial work in new ways? And what should they be wary of as they take up these powerful new tools?...

Finally, because of the wide variety of machine-learning approaches available, part of the challenge for journalism is figuring out which techniques are appropriate (and useful) for particular journalistic tasks. One way to tackle this challenge would be to invite experts in machine learning to take up residence in newsrooms where they could determine which strains of machine learning could be most useful to the journalists there. Another possibility might be to invite editorial thinkers to do fellowships in computing environments. With more collaboration over time, we can flesh out where and when machine learning is most useful in journalism, and thus broaden the capacities of even the largest newsrooms to investigate the secrets hidden in the vastness of digital data.

In summary, I’m bullish on the capabilities and opportunities that machine learning presents to editorial work, but also cautious enough to remind readers that machine learning is not the answer to every journalistic task. The grand challenge moving forward is to experiment with when and where the different flavors of machine learning truly do bring new editorial value, and when, in fact, we may just want to rely on good ol’ human learning.
Read more... 

Recommended Reading

Automating the News:
How Algorithms Are Rewriting the Media
Source: Columbia Journalism Review

Most people now think artificial intelligence poses a threat to the human race, study claims | Science - Daily Mail

  • Poll of 1,004 U.S. voters found that 57 percent believe AI is a 'threat to humanity'
  • Of that group, some 16 percent of respondents say AI is a 'very serious threat'
  • Findings underscore the increasing skepticism around AI around the country

The number of people who fear artificial intelligence is on the rise, reports Annie Palmer, Daily Mail.

Of the 57 percent who consider AI a threat to humanity, some 16 percent of them doubled down even further and indicated they believe it's a 'very serious threat,' Rasmussen found
Photo: Getty Images/iStockphoto

A new poll of 1,004 registered voters in the U.S. found that 57 percent of them believe AI is a 'threat to the human race.'

The findings demonstrate the increasing skepticism around AI, which has made its way into many of the devices we use today, from cars to cellphones.

The survey was conducted from April 17th to 18th by political analyst and pollster Scott Rasmussen and market research firm HarrisX.  

In addition to the 57 percent who believe AI is a threat, approximately 43 percent disagree and believe it's not something to be worried about.

Of the 57 percent who consider it a threat, some 16 percent of them doubled down even further and indicated they believe it's a 'very serious threat.' 

Rasmussen noted that the number of respondents who consider AI a threat has risen three percentage points since November...

They could 'go rogue'
Computer scientist Professor Michael Wooldridge said AI machines could become so intricate that engineers don't fully understand how they work. 


If experts don't understand how AI algorithms function, they won't be able to predict when they fail. 

This means driverless cars or intelligent robots could make unpredictable 'out of character' decisions during critical moments, which could put people in danger. 

Source: Daily Mail 

Women in Maths | Interviews - The Saint

Deputy Features Editor Alice Bessonova speaks with Kamilla Rekvényi, School President of Mathematics and Statistics, and other mathematicians, about the representation of women in the field, highlighting false assumptions about role models and entrenched stereotypes.

How often have you heard the recurring stereotype that mathematics is for boys, and not for girls? That boys are faster at maths? That boys are good at maths and girls are good at reading? That studying maths is difficult for girls?  asks Deputy Features Editor Alice Bessonova, The Saint.
 
Photo: Alice Bessonova
Although nowadays such stereotypes may seem outdated, a study by the University of Washington found that these stereotypes resulted in children applying it to themselves, and made many boys identify themselves with maths, while girls did not.

The gender gap in maths achievement has been widely studied since the 1960s. Since then, the idea that girls are innately worse at maths than boys has been scientifically debunked. However, the gender disparity in quantitative fields remains significant and grows from high school to university. In university-based mathematical research, it is even more pronounced: from 2014 to 2015, data from the London Mathematical Society showed that although 40 per cent of UK mathematics undergraduates were female, only 9 per cent of UK mathematics professors were female.

Historically, although women had been able to achieve notability in mathematics for centuries, as demonstrated by distinguished mathematical figures such as Elena Cornaro Piscopia, Emilie du Châtelet or Sophie Germain, the field remained largely closed to women prior to the twentieth century. Since then, progress has been achieved, albeit at a slow pace. For instance, in 2014, Maryam Mirzakhani was honoured with the Fields Medal, while in 2019, Karen Uhlenbeck won the Abel Prize. Both were the first and only women to win each prize, which are among the most prestigious awards in mathematics. Yet, women still encounter recurrent obstacles in the field, stemming mostly from these deeply embedded cultural attitudes.

Inspired by Kamilla Rekvényi, School President of Mathematics and Statistics and fifth-year student at the University of St Andrews, I turned to some St Andrews students who study mathematics to inquire about the various aspects of how it feels to be a woman in such a male-dominated field...

Additionally, “Teachers should be trained to create a more equal environment in the classroom and to leave aside any biases they have. Young people should be encouraged to take subjects that align with their abilities and interests, regardless of their gender. As well as this, more girls could be encouraged to pursue a career in STEM by making them more aware of women in the field who can act as role models. Personally, I think this would have helped me make a more informed decision when choosing a career path,” emphasised Ms Henry.  
Read more...

Source: The Saint

Product Review for McGraw-Hill’s Redbird Math | Product Review - The Tech Edvocate

Matthew Lynch, Author at The Tech Edvocate recommends, For over half a century, McGraw-Hill has been the gold standard in PreK-12 and higher education curriculum and instruction in the United States. 

Screenshot - Redbird Mathematics
I have a unique history with McGraw-Hill, as I can remember being educated as a K-12 and college student with their textbooks and workbooks. Also, as an elementary school teacher, I used their products to educate and remediate my students. And lastly, as a professor of education, I used McGraw-Hill textbooks to train future teachers and education administrators. I can genuinely say that my relationship with McGraw-Hill products has been full circle.

So, when I was asked to review Redbird Mathematics, I accepted the opportunity. This product is a part of McGraw-Hill Education’s Redbird suite of offerings, which provide personalized learning to elementary-level students in a variety of subjects. Keep reading to find out what I think of Redbird Mathematics.

An overview of Redbird Mathematics
Redbird Mathematics provides students in grades K-7 with a personalized mathematics learning path by leveraging adaptive instruction, gamification, and digital project-based learning. This allows the supplemental platform to deliver precisely what each student needs to develop math fluency and aptitude.

Every teacher-assigned unit of Redbird Mathematics ends with an extended STEM (Science, Technology, Engineering, Mathematics) problem, and 20 of the 56 units end with a digital STEM project focused on the unit’s topic...

Conclusion
It’s no secret that students regularly struggle with math. However, most education experts feel the issue is more about motivation and engagement than ability and aptitude. Enter Redbird Mathematics. After demoing this product, I was impressed by its nuances and advanced features, which work together to help students in grades K-7 develop math fluency and conceptual understanding. Also, it can motivate students with math anxiety to face their fears and frustrations. As students reflect on their mistakes, they will start to see them as a necessary stop on the road to math fluency.

I wholeheartedly recommend this platform to all classroom teachers, administrators, math coaches, etc., who are striving to increase their student’s math fluency, proficiency, and confidence. You won’t be disappointed. If you adopt Redbird Mathematics no longer will your students avoid math, they will embrace it.
Read more...

Source: The Tech Edvocate

Guest Column: We can move education forward with a little STEAM | Opinion - Valley Courier

Ever since the space race in the late 1950s there has been a concern about American students lagging behind the rest of the developed world in Science and Math, argues Dr. Kerry Hart, Interim President of Trinidad State Junior College.


More recently, there has been a push to emphasize science, technology, engineering, and math (STEM) in order for American students to compete globally. And the value of STEM has been put into monetary incentives. During the Obama administration, former President Obama, speaking at a General Electric gas plant, said, “I promise you folks can make a lot more, potentially with skilled manufacturing or the trades than they might with an art history degree.” While this comment only spoke to the monetary value of post-secondary education in manufacturing and trades, it is in stark contrast to a commentary on education made by our second U.S. President, John Quincy Adams. Adams said, “I must study war and politics so that our sons may have liberty to study mathematics and philosophy…in order to give their children the right to study painting, poetry, music, [and] architecture.” The educational vision of John Quincy Adams more than 200 years ago, compared to the reality of today’s market value of education and training expressed by Barrack Obama, gives us pause to ponder where we’ve come from and where we’re going with our educational system. Should we forget art history and advise all of our students to go into the trades; or is there a way to integrate knowledge and skills in order to produce productive, creative, and prosperous citizens?

The commonality between the educational ideas expressed by Presidents Obama and Adams is they perceive education and training as compartmentalized. Obama viewed the trades in one category and art history in another. Adams considered the study of war and politics separate from math and philosophy, and those subjects separate from art, music and architecture...

This inquiry started with Leonardo da Vinci in the late Renaissance and went all the way up to the late twentieth century (the present time of the research). I found, with the exception of two inventors, every scientist that made life-changing contributions to western civilization had an arts background. For example, Leonardo da Vinci was as good of an artist as he was an inventor; and Albert Einstein was an accomplished violinist as well as a scientific genius. My conclusion was that without creative problem solving, such as the creative process developed through the arts, scientists are confined to analyzing the inventions of others.
Read more...  

Source: Valley Courier

Wednesday, April 24, 2019

AI vendors attack data scientist shortage with trainings | Problem solve - TechTarget

Mark Labbe, news writer for SearchEnterpriseAI and SearchBusinessAnalytics says, Internal data science training programs have helped vendors when colleges and universities have failed. Training is helping to fix the data scientist shortage.


The data scientist shortage, caused partially because AI and analytics technologies are constantly changing, and partially because colleges and universities can't keep up with the demand for data science education, is well-documented, and has been a problem for years.

To attack that shortage, data science vendors are developing internal and external training programs that provide education to their own employees and to their clients' employees.

Internal training programs 
Fusemachines, Inc., a New York-based startup founded in 2013, provides AI experts, such as developers, engineers and programmers, to companies looking to build or refine their own AI systems.

Clients request all sorts of work, but right now, recommendation engines for retailers are in particularly high demand, said Steve Rennie, director of research at Fusemachines...

One customer, a United Kingdom-based statistics company, has been working with Cloudera on a project to onboard more statisticians, Brandwein said... 

The New York-based company works with new graduates as well as more seasoned employees. Most clients are almost ready for the modern workforce, but are not quite there yet. New graduates might have a Ph.D. in mathematics, but no experience in machine learning. Older employees, meanwhile, might have much experience with machine learning, but not with using some of the newer machine learning tools.
Read more...

Source: TechTarget  

Actuarial science celebrates success on 60th anniversary | Daily Illini

The actuarial science program is celebrating its 60th anniversary at the University with a Risk Analytics Symposium and an Illinois Actuarial Science Reception on Thursday, May 16., The Daily Illini Staff Report.


The symposium provides practitioners, academics and students a venue to discuss the latest technological development and discoveries, trending industrial research in actuarial science, risk management and advanced analytics at the new Illinois Risk Lab connected to the program.

The Risk Analytics Symposium will be held at the Illini Center in Chicago from 8:30 p.m. to 4 p.m.

Photo: Runhuan Feng
“While there have been lots of conferences on data science, the Risk Analytics Symposium is the first of its kind to focus on advanced analytics applied to uncertainty quantification and risk management,” Runhuan Feng, the head of actuarial science at the University, said in an email...

“The actuarial science group is partnering with mathematics, statistics and finance department administrations to develop a new joint master’s program in Predictive Analytics and Risk Management,” Feng said. “If successful, the new program would enable Illinois to establish itself as one of the innovators in preparing students for the nascent profession of predictive analytics.”
Read more...  

Source: Daily Illini

Tuesday, April 23, 2019

Emotional Intelligence: The Social Skills You Weren't Taught in School | Mind Hacks - Lifehacker

This post originally appeared on Lifehacker and was published February 20, 2019. This article is republished here with permission.

You’re taught about history, science, and math when you’re growing up. Most of us, however, aren’t taught how to identify or deal with our own emotions, or the emotions of others. These skills can be valuable, but you’ll never get them in a classroom, explains Eric Ravenscraft, Freelance writer, editor.

Photo: Lifehacker
What Is Emotional Intelligence?
Measuring emotional intelligence is relatively new in the field of psychology, only first being explored in the mid-80s. Several models are currently being developed, but for our purposes, we’ll examine what’s known as the “mixed model,” developed by psychologist Daniel Goleman. The mixed model has five key areas:
  • Self-awareness: Self-awareness involves knowing your own feelings. This includes having an accurate assessment of what you’re capable of, when you need help, and what your emotional triggers are.
  • Self-management: This involves being able to keep your emotions in check when they become disruptive. Self-management involves being able to control outbursts, calmly discussing disagreements, and avoiding activities that undermine you like extended self-pity or panic.
  • Motivation: Everyone is motivated to action by rewards like money or status. Goleman’s model, however, refers to motivation for the sake of personal joy, curiosity, or the satisfaction of being productive.
  • Empathy: While the three previous categories refer to a person’s internal emotions, this one deals with the emotions of others. Empathy is the skill and practice of reading the emotions of others and responding appropriately.
  • Social skills: This category involves the application of empathy as well as negotiating the needs of others with your own. This can include finding common ground with others, managing others in a work environment, and being persuasive.
You can read a bit more about these different categories here...

Social Skills
Summing up all social skills in one section of an article would do about as much justice to the topic as if we snuck in a brief explainer on astrophysics. However, the tools you develop in the other four areas will help you resolve a lot of social problems that many adults still wrestle with.
Read more...

Source: Lifehacker

The 34 New Skills You Can Now Learn on LinkedIn Learning | New Courses - LinkedIn Learning

Paul Petrone, Editor - LinkedIn Learning suggests, Each week presents a new opportunity for you and your team to learn the skills necessary to take on the next big challenge.

Photo:  Learning Blog - LinkedIn Learning

And, at LinkedIn Learning, we want to do everything we can to help make that happen.

So, each week, we add to our 13,000+ course library. And this past week was no different, as we added 34 new courses covering everything from AWS to mobile development to overcoming your fear of public speaking. 

The new courses now available on LinkedIn Learning are:
Read more... 

Additional resources 
Want to see what else we offer?  
View all of LinkedIn Learning's 13,000+ courses today

Source: LinkedIn Learning (Blog)