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Thursday, April 18, 2019

Foundation names Dracut one of best school systems for music | Lowell Sun

The sounds of Dracut High School's string orchestra filled every corner of the room on a recent Tuesday morning with Robin Mallory at the helm, notes Amaris Castillo, reporter for The Lowell Sun.

Orchestra Director Robin Mallory conducts Dracut High School's string orchestra on April 2. Dracut Public Schools was recently named one of the Best Communities for Music Education from the NAMM Foundation. NAMM stands for National Association of Music Merchants.
Photo: SUN/Amaris Castillo
"Here we go, ba-dam!" the orchestra director said as the student musicians performed a medley of songs featured in the Academy Award-winning film "La La Land."

Over the next hour, Mallory would periodically pause the ninth- to 12th-grade students to give them instruction and perfect their collective sound.

Mallory's leadership at Dracut High is just one facet of music education within Dracut Public Schools, which was recently named one of the Best Communities for Music Education from the NAMM Foundation. NAMM stands for National Association of Music Merchants. The signature program recognizes and celebrates school districts and schools for their support and commitment to music education and efforts to assure access to music for all students as part of a well-rounded education, according to the NAMM Foundation's website...

In an email Zolezzi said the survey administered by The Music Research Institute at the University of Kansas evaluates schools and districts "based on funding, staffing of highly qualified teachers, commitment to standards, and access to music instruction."
Coordinator of Performing Arts Carolyn Cardella submitted the survey on Dracut Public Schools' behalf with the support of Superintendent of Schools Steven Stone. It is one of 14 communities in Massachusetts to be recognized.

"I'm extremely proud of the staff and the students," Cardella said recently. "I don't feel that I can claim any credit for it because it's the programs that they've had in place that they've been doing for many years now. I just helped them get recognized for it."

Source: Lowell Sun

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Wednesday, April 17, 2019

Peeking into the Black Box of Artificial Intelligence | Technology - BBN Times

While artificial intelligence (AI) applications are becoming increasingly capable of solving even the most complex of our problems requiring human-like cognition, the black box of artificial intelligence makes it difficult for us to understand how these systems actually go about solving these problems, as BBN Times reports.  

Photo: BBN Times
Although humans had always known about the existence of fire, it was only when we learned to control or “tame” fire that we really kickstarted the journey of rapid technological progress and evolution we currently find ourselves in. Now, over a million years later, we find ourselves at a similar juncture—albeit faced with an entity that we created instead of a natural phenomenon. The creation of artificial intelligence, undoubtedly, is a step into an era of unprecedented growth unlike any we’ve seen before. But, a true leap can only be achieved once we “tame” the technology, as it were, by first illuminating the black box of artificial intelligence that will enable us to better control the outcomes affected by the technology. 

Our brain, the apotheosis of human evolution and the most vital of our organs, also happens to be the most complex and enigmatic things known to us. Similarly, artificial intelligence, which represents the pinnacle of human technological development, is equally perplexing—despite the fact that it has been created by us. To be fair to ourselves, there is a lot we do know about our brain and can predict with some certainty how it reacts to different stimuli...

Deep Neural Networks: The Working of the Black Box of Artificial Intelligence 
Deep neural networks use multiple layers of algorithms that analyze data and classify or cluster items. Since these neural networks are designed to function in ways similar to our brains, they also gain the ability to classify objects like we do—through experience. A human baby learns to differentiate between objects as it grows by observing them and learning to label them based on what it is taught by its parents. Similarly, a deep learning algorithm learns through training data that gets fed to it so that the algorithm gains “experience”. But this isn’t where the similarity between the human brain and a deep learning algorithm ends. Have you ever noticed that we gain the ability to identify different breeds of cats and dogs as “cats” and “dogs” even when we’ve never seen some breeds before? We don’t need to see every breed of dogs there is to be able to identify one when we see it for the first time. This phenomenon is called ‘generalization’, where we identify and memorize certain distinctive features of dogs (or any other entity) and use those features to generally identify a dog as one, even when we see a totally new breed with radically different features. The similar ability to generalize is also seen in AI agents who can use what they learn from one dataset to generalize across new sets of similar input.

Source: BBN Times

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Lithium–ion battery book written by machine learning algorithm | Books - Chemistry World

A book written entirely by machine-learning algorithms has been published by Springer Nature, inform Frances Addison, Digital Content Assistant at Chemistry World.

Photo: Getty Images
It discusses current research in lithium–ion batteries and is pulled from more than 150 research articles published between 2016 and 2018. The team responsible wanted the book to demonstrate the current abilities of machine learning algorithms, and to identify problem areas that need to be improved.

Lithium–ion batteries is an area of fast moving research, with many articles published each year. To help researchers keep up with recent advances without needing to sift through vast quantities of literature, Springer Nature wanted to produce a manuscript that summarised all of the research automatically...

To give an accurate representation of the abilities of current machine learning technology, the book has not been copy-edited. This both highlights the tremendous accomplishment of the algorithm – large passages of the book read well without any obvious mistakes – as well as some of the flaws. Sentences and paragraphs have crept in where the algorithm has generated sentences that falter or are grammatically incoherent.  

Beta Writer, Lithium-Ion Batteries:
A Machine-Generated Summary of Current Research. Springer Nature, 2019. 

Recommended Reading

10 Algorithms Every Machine Learning Enthusiast Should Know by Ambika Choudhury, budding Technical Journalist. 

Source: Chemistry World

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The artificial intelligence field is too white and too male, researchers say | Tech - The Verge

A new report explores AI’s ‘diversity crisis’, insist Colin Lecher, Senior Reporter at The Verge. 

Photo: Alex Castro / The Verge

The artificial intelligence industry is facing a “diversity crisis,” researchers from the AI Now Institute said in a report released today, raising key questions about the direction of the field.

Women and people of color are deeply underrepresented, the report found, noting studies finding that about 80 percent of AI professors are men, while just 15 percent of AI research staff at Facebook and 10 percent at Google are women. People of color are also sidelined, making up only a fraction of staff at major tech companies. The result is a workforce frequently driven by white and male perspectives, building tools that often affect other groups of people. “This is not the diversity of people that are being affected by these systems,” AI Now Institute co-director Meredith Whittaker says.

Worse, plans to improve the problem by fixing the “pipeline” of potential job candidates has largely failed. “Despite many decades of ‘pipeline studies’ that assess the flow of diverse job candidates from school to industry, there has been no substantial progress in diversity in the AI industry,” the researchers write...

Diversity, while a hurdle across the tech industry, presents specific dangers in AI, where potentially biased technology, like facial recognition, can disproportionately affect historically marginalized groups. Tools like a program that scans faces to determine sexuality, introduced in 2017, echo injustices of the past, the researchers write. Rigorous testing is needed. But more than that, the makers of AI tools have to be willing to not build the riskiest projects. “We need to know that these systems are safe as well as fair,” AI Now Institute co-director Kate Crawford says.  

Source: The Verge

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Meet Hypatia, the ancient mathematician who helped preserve seminal texts | Massive Science

The mathematician, astronomer, and philosopher Hypatia is considered the first known female mathematician and one of the “last great thinkers of Alexandria, the sophisticated Ancient Egyptian city.

Brianna Bibel, Biochemistry at Cold Spring Harbor  Laboratory reports, Her dramatic death often overshadows her epic life, but it shouldn’t.

Photo: Matteo Farinella

Why the last? Tension between religious and secular factions seeking control over the city boiled over in the early 400s, leading to her violent murder and turning her into a martyr for scientists, pagans, and atheists.

Hypatia’s death is much better recorded than her life - historians aren’t even sure when she was born (sometime around 350 CE). But there is plenty of evidence that Hypatia was a tremendous scholar.

If you wanted to learn math and astronomy in Alexandria, it helped if your dad was Theon, the last known member of Alexandria’s museum (not a museum in the sense we use the word now but more of a “university”). Theon taught Hypatia and sought her help with some of his commentaries - republications of someone else’s work with notes interpreting and explaining various parts. Commentaries such as these played an important role in preserving and advancing ancient Greek works at a time when such works were seen by many as “pagan” and opposed to Christian ideals. Many historians believe that at least one of the commentaries attributed to her father, the third book of Theon’s version of Ptolemy’s Almagest, an astronomical text used widely until the 16th century, was actually written by Hypatia...

Hypatia was a master networker - she had an “in” with many powerful figures in the ancient world, including the governor of Alexandria, Orestes. This popularity likely spawned jealousy in archbishop Cyril, already in a foul mood due to a feud with Orestes over control of the city. Orestes was a Christian, but he didn’t think the Christian Church should encroach on “civil government.” Cyril, on the other hand, wanted the church to have more control in secular affairs. The argument led to Cyril’s monks trying to assassinate Orestes, but they only succeeded at putting Orestes on high alert. But they didn’t have to look far for an easier target - Hypatia regularly traveled around, giving public lectures proudly espousing “pagan” views.

Source: Massive Science

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The Sexist Trolls Doubting Black Hole Researcher Katie Bouman Need to Learn to Code | Black Hole - VICE

This article originally appeared on VICE US.

Last week, fans of cool astronomical phenomena (read: almost everyone) rejoiced as an international team of scientists released the first ever image of a black hole, continues VICE.

Photo: VICE
For the astrophysicists, software engineers, philosophers, and mathematicians who worked on the Event Horizon Telescope that captured the image, the announcement was an unprecedented milestone.

Their excitement was perhaps best embodied by a photo of one computer scientist on the Event Horizon Telescope team, Katie Bouman, who hid her beaming smile with her hands as she looked at the monumental rendering. Bouman had a lot to smile about—the image was created using petabytes of data that were stitched together using CHIRP, an algorithm that Bouman worked on. And Bouman had long served as a public face for the computer imaging aspect of the Event Horizon Telescope, delivering a TED Talk on the project in 2016.

But within a day of the announcement, online harassers created fake Instagram accounts for Bouman, started angry threads on Reddit and Hacker News asserting that she hadn’t done as much to help the project as she was getting credit for, and produced lengthy YouTube tirades, all with the aim of discrediting her contributions to the project...

In scientific fields that thrive on data, sexism can pass as legitimate when couched in the language of cold, unfeeling numbers and percentage points. But anyone with even a basic understanding of modern computer science should quickly realize how dangerous and plainly wrong these trolls are when they weaponize metadata from public Github repositories. 

Source: VICE

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Tuesday, April 16, 2019

The 42 New Skills You Can Now Learn on LinkedIn Learning | | New Courses - LinkedIn Learning

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

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 42 new courses covering everything from Revit 2020 to cloud infrastructure to building high-performance teams. 

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

Source: LinkedIn Learning (Blog)

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Scientists, Data Scientists And Significance by Mike James | iProgrammer

In a recent special issue of The American Statisticianscientists are urged to stop using the term "statistically significant". So what should we be using? Is this just ignorance triumphing over good practice?

There are many who think that science is in a state of crisis of irreproducible, and even fraudulent, results. It is easy to point the finger at the recipe that statisticians have given us for "proving" that something is so. It is a bit of a surprise to discover that at least 43 statisticians (the number of papers in the special edition) are pointing the finger at themselves! However, it would be a mistake to think that statisticians are one happy family. There are the Frequentists and the Bayesians, to name but two warring factions.

The problem really is that many statisticians are doubtful about what probability actually is. Many of them don't reason about probability any better than the average scientist and the average scientist is often lost and confused by the whole deal.

If you are Frequentist then probability is, in principle, a measurable thing. If you want to know the probability that a coin will fall heads then you can toss it 10 times and get a rough answer, toss it 100 times and get a better answer, 1000 and get even better and so on...

A much bigger problem is the repeated experiment situation. If you are using experiments that have a significance of 5%, then if you repeat the experiment 100 times you will expect to see five significant results purely by chance. I once was asked why in a ten by ten correlation matrix there were always a handful of good significant correlations. When I explained why this was always the case, I was told that the researcher was going to forget what he had just discovered and I was never to repeat it. Yes measuring lots of things and being surprised at a handful of significant results is an important experimental tool. If repeated attempts at finding something significant were replaced by something more reliable, the number of papers in many subjects would drop to a trickle. This is a prime cause of the irreproducibility of results and a repeat generally finds the same number of significant results, just a different set.

Source: iProgrammer

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Top 2018 KCSE students pick medicine and engineering | Education - The Star, Kenya

In Summary
University of Nairobi bags the highest number of A students, to study medicine
• Top 2018 KCSE candidate to study aeronautical engineering at Technical University 

Medicine, engineering and pharmacy among the distinguished courses attracting top scorers, says Lewis Nyaundi, young journalist and education writer with the Star newspaper
Photo: courtesy of Stuart Miles at
Top 2018 KCSE scorers will enrol in some of the country's best universities to study prestigious courses of their choice. 

According to official results from the university placements agency, all the 314 students who scored straight As in the Kenya Certificate of Secondary Education exam have been admitted to courses considered distinguished and reserved for top brains.

They include Bachelor of Medicine and Surgery, law, architecture, engineering and computer science,  pharmacy, nursing and quantity survey. 

The Kenya Universities and Colleges Central Placement Service will open the online system for inter-institution transfer applications between May 1 and 30...

He said more girls should be encouraged to pursue science courses. Out of those enrolled in the STEM courses, 36,189 (63 per cent) are male, while 21,498 (37 per cent) are female.

"...Science, Technology, Engineering and Mathematics courses are fast gaining track and have surpassed arts in enrolment, but the trend is worrying as the number of boys still remains higher despite our learners having a level playing ground," Magoha said.

Source: The Star, Kenya

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Monday, April 15, 2019

Meet mathematician Emmy Noether, mother of the most beautiful theorem in the world | Massive Science

Brittney Borowiec, Environmental Physiology explains, She worked out a kink in general relativity and kickstarted the field of abstract algebra.

Photo: Matteo Farinella
Brilliant, creative, and assertive, Emmy Noether helped to fine-tune the theory of general relativity and kick-started a new field of mathematics with her conceptual, abstract approach and “big picture” ideas. 

Noether’s revolutionary way of thinking changed our approach to mathematics and physics in the early 20th century, despite struggling throughout her life for the opportunities afforded to her male colleagues. She is perhaps the most important mathematician that you’ve never heard of.

Emmy Noether was born in Erlangen, Germany in 1882 into an academically brilliant family. Her father Max was a successful mathematician, and two of her younger brothers eventually earned doctorates in chemistry and mathematics. As a child, Noether focused her studies on languages, music, and domestic duties – subjects deemed appropriate for women at the time. But after passing an examination in 1900 to teach French and English, she took the highly unusual action of studying mathematics at the University of Erlangen.

The university had only recently relaxed its ban on female students, but still only allowed women to audit classes, and only after being granted permission from their professors...

In 1915, Hilbert, Klein, and the rest of the University of Göttingen’s mathematics department were enamored with Einstein’s radical new theory of general relativity. Hilbert and Klein hoped that Noether’s expertise in invariants would help them work out unresolved issues with the new theory, and invited her to apply for a faculty position. Despite her clear talent for mathematics, other faculty members refused to accept the prospect of a women colleague.
Read more... 

Recommended Reading

Photo: Matteo Farinella
Meet Ada Lovelace, the world’s first computer programmer by Lauren Mackenzie Reynolds, PhD candidate at McGill University in Montréal. 
"A “prophet of the computer age,” she saw the potential for computers outside of pure mathematics." 

Source: Massive Science

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