Artificial intelligence bringing education into digital age | Lenovo - SHINE

East China Normal University signed agreements with Microsoft and Lenovo today during the ongoing World Artificial Intelligence Conference to empower education with artificial intelligence by Yang Meiping, Metro Reporter.

The agreements were signed at an education-themed forum during the event, which focused on how AI can empower the digital transformation of education.

The cooperation between the university and Microsoft Research Asia aims to advance research capabilities and conduct leading-edge research in academia and industry, as well as cultivate and attract high-end talent from across the world.

According to Microsoft Research Asia, the two parties have developed an intelligent Chinese writing assistance system previously, with which students can have their writings assessed and analyzed to improve writing skills...

The two parties aim to build the park into a highland for intelligent education to facilitate the development of other core industries, such as AI, biomedicine and integrated circuits.

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Source: SHINE

Can machine learning bring more diversity to STEM? | AI / Machine Learning - Harvard School of Engineering and Applied Sciences

Postdoctoral researcher will use AI to study implicit bias in middle school students, according to Adam Zewe, Communications Manager at Harvard School of Engineering and Applied Sciences. 

Photo: Haewon Jeong

Even though progress has been made over the past decades, gender and racial disparities in STEM (science, technology, math, and engineering) fields continue to persist.

A 2021 Pew Research study found that only 9 percent and 8 percent of STEM jobs are held by Black and Hispanic workers, respectively. And while the study found that women hold 50 percent of all STEM jobs (including health-related jobs), the percentages are far lower for jobs in physical sciences (40 percent), computing (25 percent), and engineering (15 percent).

Could machine learning help researchers better understand the factors that contribute to those disparities? Or are machine-learning tools partly to blame for the gender and racial discrepancies in STEM? Haewon Jeong, a postdoctoral fellow in the lab of Flavio Calmon, Assistant Professor of Electrical Engineering at the Harvard John A. Paulson School of Engineering and Applied Sciences, is embarking on a research study to explore both questions...

While the algorithms may provide valuable insights, the risks the technology poses when applied to testing, grading, and class placement inspired Jeong to study the downsides of machine learning.

“Machine learning can be a double-edge sword,” she said. “If you just use machine learning without care, you can induce more bias.”

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Source: Harvard School of Engineering and Applied Sciences

The Future of Deep Learning | Deep Learning - Analytics Insight

Apoorva Bellapu, A content writer by passion says, When thinking of technology, one cannot go without talking about deep learning. 

Photo: Analytics Insight

Needless to say, deep learning has become one of the most critical aspects of technology. Gone are the days when organizations alone used to show interest in technologies like AI, deep learning, machine learning, etc. Today, even individuals are inclined towards the very aspect of technology, deep learning in particular. One of the many reasons why deep learning draws all the attention is because of its ability to enable improved data-driven decisions and also improve the accuracy of the predictions made.

In a nutshell, companies are in a position to reap out various financial and operational benefits by virtue of deep learning. With many deep learning innovations proliferating with time, it makes every possible sense to have a clear picture as to how does the future of deep learning looks like...

What everything boils down to is the fact that as a result of the growing popularity of deep learning and with the advancement in technology, by the end of this decade, the deep learning industry will simplify its offerings considerably so that they’re comprehensible and useful to the average developer.

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Source: Analytics Insight

Everything You’ve Ever Known is Statistics | Statistics - Medium

Information is never without uncertainty, argues Tim Andersen, Ph.D., Research in general relativity and quantum field theory, published in Cantor's Paradise.

Photo: Alex Chambers on Unsplash

The brain is an amazingly complex machine for processing information. Whatever your philosophy of mind is, you can’t deny that it depends in large part on the brain’s ability to process incoming signal data and convert that data into higher level understanding.

These days brain-inspired techniques have taken over Artificial Intelligence (AI) in a way that they never had decades ago.

Yet, skepticism over neural networks and their ability to mimic human intelligence remains strong, particularly among those with a strong mathematical background, because neural networks are, fundamentally, statistical instruments. They are nothing more nor less than a way of determining statistics from data and then mining those statistical insights for factors. Even decision making, which seems like a non-statistical activity, is statistical in that it represents the correlation between two spaces: that of data and that of decisions.

This article, however, is not about artificial intelligence but about the very nature of information. The overarching thesis is that all empirical knowledge is statistical...

This is why everything you’ve ever known is essentially statistical.

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Source: Medium    

200+ women scientists and schoolgirls closing gender gap in STEM | Mathematics - Mirage News

National STEM camps for girls double their reach across Australia by Australian Science Innovations.

Women in STEM mentor 128 schoolgirls in science and technology.

One hundred and twenty-eight schoolgirls from across Australia, including 90 from regional towns in every state and territory, are completing six months of extension learning and mentoring this week in national camps that have immersed underrepresented girls in science, technology, engineering and maths (STEM).

The high-potential year 9 and 10 students have explored all aspects of STEM through lectures, experiments, workshops, coaching and networking, all delivered for the first time online to combat the impact of COVID-19...

Students have participated in intensive modules of learning across physics, digital technology, chemistry, biology, mathematics, engineering and Earth and environmental science. They have worked with their mentors on projects over a six-month period.

Some of the students’ projects this year have included learning about and applying computer programming, investigating mathematical theories, researching public health issues, analysing Anglo-Australian Telescope data to calculate the mass of dark matter in a galaxy, and learning about data science and its industrial applications. 

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Source: Mirage News 

“WHY” mathematics is the future | India Blogs - The Times of India

Manan Khurma, founder and CEO of Cuemath summarizes, Look around you carefully, there is math everywhere. 

Even when we use search engines like google or avail of a discount online, consult recommendations before buying a product, watch a favorite movie on an OTT platform, or even understand how a virus becomes a pandemic, it’s all math. So, if you get your math right, you will find an answer to many “Whys” or questions that bombard our minds.

Math is a crucial life skill

There is a lot more to math than finding the hypotenuse of a right-angle triangle or solving an equation. Math is much more than our school curriculum where we apply memorized formulas to problems and focus on getting the solution. Math is about understanding automation and computational thinking. Never has math been more important like a skill than today and the way the future looks, math Coding and Data sciences will be the go-to skills in the future..

Most eLearning courses comprise pre-recorded videos or a broadcast to a class with a large number of students. The students are not able to clarify their doubts and the teacher too cannot check how well a student has understood the topic being taught. Collaborative learning and meaningful interaction are lost in this environment. So, naturally, the joy of learning, exploring, and creating is lost in such a mechanical setting.

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Source: The Times of India   

Math 2.0 Day – July 8, 2021 | Special interests - National Today

Math 2.0 Day celebrated every July 8, is a holiday that commemorates the importance of the combination of math and technology.

The day was formed to celebrate the accomplishments made through the combination of the field of math and technology, and how it can benefit the world in the coming years. This means without math, it would have been impossible for us to be provided with the different travel and entertainment mediums we have today. Nor would we have the technology we use to accomplish several everyday work tasks. So if you love how easy technological innovations have made your life, celebrating Math 2.0 Day is a must!...

History of Math 2.0 Day

Math 2.0 day was created in 2009 by the Math Interest Group. The group was created to promote and enable the use of math online. This is essential since math is critical for the advancement of technology, science, and education. The Math Interest Group also collaborates on research and development projects that focus on mathematics education required in the fields of finance, engineering, medicine, and even social sciences. Here’s how math has helped in the development of technological innovations.

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Source: National Today

This Math Explains Why Cauliflowers Look Too Oddly Perfect | Nature - ScienceAlert

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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Have you ever stared at a cauliflower before preparing it and got lost in its stunningly beautiful pattern? Probably not, if you are in your right mind, but I reassure you it's worth a try, observes Etienne Farcot, Assistant professor of Mathematics, University of Nottingham.

Photo: Steven Lasry/Unsplash

What you'll find is that what at first sight looks like an amorphous blob has a striking regularity.

If you take a good look, you will see that the many florets look alike and are composed of miniature versions of themselves. In math, we call this property self-similarity, which is a defining feature of abstract geometrical objects called fractals. But why do cauliflowers have this property?

Our new study, published in Science, has come up with an answer...

If you manage to count the spirals, they will typically be numbers somewhere along the Fibonacci sequence, where the next number in the sequence is found by adding up the two numbers before it. This gives 0, 1, 1, 2, 3, 5, 8, 13, etc.

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Source: ScienceAlert

Can Traditional Philosophy Help Us Understand Mind vs. Brain? | Articles - Walter Bradley Center for Natural and Artificial Intelligence

Michael Egnor, Professor of Neurosurgery and Pediatrics at State University of New York, Stony Brook asks us to look back to the traditional idea that the soul is the “form” of the body.

Photo: Aristotle

Yesterday, we published the fourth portion of the debate between materialist philosopher David Papineau and neurosurgeon Michael Egnor, where the key issue was “Is the mind simply what the brain does?” Today, we look at the portion which starts roughly at 36 min where Papineau and Egnor start to talk about traditional philosophical ways of thinking about the soul and the body (partial transcript):

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Source: Walter Bradley Center for Natural and Artificial Intelligence  

Riemann Hypothesis: 161-yr-old Math mystery Hyderabad physicist is waiting to prove he solved | Science - ThePrint

In the movie A Beautiful Mind — a biopic on renowned American mathematician John Nash — the protagonist says “he is making progress” on solving Maths’ greatest mystery: The Riemann Hypothesis by Rishika Sadam, Author at ThePrint.

Hyderabad-based theoretical physicist Dr Kumar Eswaran | Rishika Sadam | ThePrint

Like the American stalwart, many great mathematical minds have tried over a century to crack this ‘big unknown’, more so in recent years after a USD one million prize was announced for the final solution.

Now, 161 years after the hypothesis was forwarded, Hyderabad-based theoretical physicist Dr Kumar Eswaran says he has key proof to the unsolved problem that has baffled mathematicians and physicists the world over.

The hypothesis makes predictions on how to find prime numbers along a numerical spectrum. But so far, it remains a conjecture...

The Riemann Hypothesis: Holy grail or double-edged sword?

The hypothesis is a conjecture made by renowned German mathematician Georg Friedrich Bernhard Riemann in a paper in 1859. It is related to the distribution of prime numbers, which are integers divisible just by themselves and by 1.

Riemann’s hypothesis takes forward the work of another noted mathematician (also Riemann’s teacher) Carl Friedrich Gauss. Gauss worked on estimating the primes between zero and any given number.

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Source: ThePrint