Summary of “Why Deep Learning Is Not Enough”

I should know: For the last three decades, since I started graduate school at the Massachusetts Institute of Technology, studying with the inspiring cognitive scientist Steven Pinker, I have been embroiled in on-again, off-again debate about the nature of the human mind, and the best way to build AI. I have taken the sometimes unpopular position that techniques like deep learning aren’t enough to capture the richness of the human mind.
When 140 characters no longer seemed like enough, I tried to take a step back, to explain why deep learning might not be enough, and where we perhaps ought to look for another idea that might combine with deep learning to take AI to the next level.
In a series of tweets he claimed that I hate deep learning, and that because I was not personally an algorithm developer, I had no right to speak critically; for good measure, he said that if I had finally seen the light of deep learning, it was only in the last few days, in the space of our Twitter discussion.
I have been giving deep learning some credit ever since I first wrote about it as such: in The New Yorker in 2012, in my January 2018 Deep Learning: A Critical Appraisal article, in which I explicitly said, “I don’t think we should abandon deep learning,” and on many occasions in between.
To take another example, consider a widely-read 2015 article in Nature on deep learning by LeCun, Bengio, and Geoffrey Hinton, the trio most associated with the invention of deep learning.
There again much of what was said is true, but there was almost nothing acknowledged about the limits of deep learning, so that it would be easy to walk away from the paper imagining that deep learning is a much broader tool than it really is.
The paper’s conclusion furthers that impression by suggesting that deep learning’s historical antithesis-symbol-manipulation/classical AI-should be replaced: “New paradigms are needed to replace the rule-based manipulation of symbolic expressions on large vectors.” The traditional ending of many scientific papers-limits-is essentially missing, inviting the inference that the horizons for deep learning are limitless.
When I rail about deep learning, it’s not because I think it should be “Replaced”, but because I think that it has been oversold, often with vastly greater attention to its strengths than its potential limitations, and exuberance for deep learning is often accompanied by a hostility to symbol-manipulation that I believe is a foundational mistake in the ultimate solution to AI. I think it is far more likely that the two-deep learning and symbol-manipulation-will co-exist, with deep learning handling many aspects of perceptual classification, but symbol-manipulation playing a vital role in reasoning about abstract knowledge.

The orginal article.

Summary of “Teaching kids to code: I’m a developer and I think it doesn’t actually teach important skills.”

On a recent late-night formula run, I passed by a large display of books about teaching children to code.
These books are part of a flood of resources-summer coding camps, after-school code clubs, apps designed to teach kindergarteners the rudiments of JavaScript-aimed at equipping children with future-proof skills.
If learning to code is good, then learning earlier is better.
While these products may teach kids specific coding languages, they actually have very little to do with the work of creating software.
The description in one popular book says starting coding early is “Essential to prepare kids for the future.” This gives the impression that not teaching kids to code is somehow equivalent to not teaching them to read. That is, of course, ridiculous.
Coding books for kids present coding as a set of problems with “Correct” solutions.
Early in my career, I wrote some code to configure and run a group of remote servers.
Well-designed code feels good to work with, and ugly code will make developers involuntarily cringe.

The orginal article.

Summary of “4 In-Demand Skills You Can Learn Online”

High costs of college tuition and the growing abundance of online resources to learn about topics from computer science to blockchains have created an unprecedented opportunity for self-taught professionals and entrepreneurs.
Whether you’re looking to transition into another field or just want to learn some new skills as a hobby, the ability to do so has never been as convenient or powerful as it is now.
Many freelancers and entrepreneurs are self-taught, learning new skills on the fly out of a need to develop a professional talent or by meticulously studying a topic through online classes or reading.
Online resources for enhancing professional skills range from free university courses to standalone educational platforms that connect students and paid professionals.
Here are four areas in which you develop skills and learn more about online.
These resources are not just relegated to proprietary online platforms either.
Learning new languages becomes more challenging as you get older, but the sheer amount of content and material available to learn new languages today is perhaps the best representation of online education’s progression.
Once challenging areas of study to access are now widely available through platforms such as Class Central that aggregate resources from the top online universities in several fields.

The orginal article.

Summary of “25 Lessons Business School Won’t Ever Teach You”

There are a lot of great lessons you can learn in business school.
Some of the most important lessons you’ll ever learn about how to be successful in business comes from getting out there and doing it.
If you’re hoping that MBA will be your golden ticket to kickstarting a successful career in business, consider these all-important 25 lessons that you’ll have to learn outside the classroom.
This is a topic rarely covered in business school.
Business school will teach you the steps you should follow when forming a business: how to do research, come up with a plan, make a budget, choose a business structure and so on.
Weighing opportunity versus potential failure is often personal – you must take into account so many factors beyond the business formulas you learn in school.
Business school may teach you that disruption begins with defining a solution to a problem and then finding a way to add value to customers’ experience.
Learning to navigate the harsh business world will teach you more than you can ever learn in a classroom.

The orginal article.

Summary of “10 Proven Ways to Learn Faster”

Learning new things is a huge part of life – we should always be striving to learn and grow.
So how can you make the most of your time by speeding up the learning process? Thanks to neuroscience, we now have a better understanding of how we learn and the most effective ways our brains process and hold on to information.
If you want to get a jump start on expanding your knowledge, here are 10 proven ways you can start learning faster today.
The better your notes are, the faster you’ll learn.
Before you learn a new topic, make sure you learn different strategies for note taking, such as the Cornell Method, which helps you organize class notes into easily digestible summaries.
When you use multiple ways to learn something, you’ll use more regions of the brain to store information about that subject.
The more resources you use, the faster you’ll learn.
The more you can relate new concepts to ideas that you already understand, the faster the you’ll learn the new information.

The orginal article.

Summary of “Do Language Apps Like Duolingo Work?”

Duolingo is essentially a product of crowdsourcing; volunteers build much of the teaching content, and the in-app behavior of its 27.5 million active monthly users is continuously analyzed to determine which exercises, sentences, and techniques lead to better adherence and faster learning.
This emphasis on user retention helps explain why Duolingo is by far the most popular language app in the U.S. In other countries, von Ahn notes, learning a language is often crucial to communicating with partners and their families, and for work; learning English, in particular, can be a ticket out of poverty.
“In the U.S., about half of our users aren’t even really motivated to learn a language; they just want to pass the time on something besides Candy Crush,” he said.
Joey J. Lee, the director of the Games Research Lab at Columbia University, who did a study of 50 language apps in 2016, told me that he suspects the addictiveness of tools like Duolingo has more to do with business models than with language learning.
Where most apps really fall short, he said, is in language “Pragmatics.” “That’s the learning that’s based on real-world settings-you’re in a restaurant, in an interview, waiting for a bus,” he explained.
“What most helps someone learn a language is when they’re immersed in a situation and they’re struggling to speak,” he told me.
Most of Babbel’s lessons, he says, are focused on giving users the ability to get by in social settings-which tends to fire up interest in learning more.
“Once we get the ball rolling, we bring in more classic, cognitive learning techniques,” he said, such as more vocabulary and grammar.

The orginal article.

Summary of “How I Rewired My Brain to Become Fluent in Math”

If there were a textbook example of the potential for adult neural plasticity, I’d be Exhibit A. Learning math and then science as an adult gave me passage into the empowering world of engineering.
My doctoral training in systems engineering-tying together the big picture of different STEM disciplines-and then my later research and writing focusing on how humans think have helped me make sense of recent advances in neuroscience and cognitive psychology related to learning.
In the years since I received my doctorate, thousands of students have swept through my classrooms-students who have been reared in elementary school and high school to believe that understanding math through active discussion is the talisman of learning.
In the United States, the emphasis on understanding sometimes seems to have replaced rather than complemented older teaching methods that scientists are-and have been-telling us work with the brain’s natural process to learn complex subjects like math and science.
There is an interesting connection between learning math and science, and learning a sport.
I learned these things about math and the process of learning not in the K-12 classroom but in the course of my life, as a kid who grew up reading Madeleine L’Engle and Dostoyevsky, who went on to study language at one of the world’s leading language institutes, and then to make the dramatic shift to become a professor of engineering.
In my case, from my experience becoming fluent in Russian as an adult, I suspected-or maybe I just hoped-that there might be aspects to language learning that I might apply to learning in math and science.
As I look today at the shortage of science and math majors in this country, and our current trend in how we teach people to learn, and as I reflect on my own pathway, knowing what I know now about the brain, it occurs to me that we can do better.

The orginal article.

Summary of “Why My Young Daughter Is So Much Better at Learning Chess Than I Am”

Magnus Carlsen, the world’s current top-ranked player, was the youngest player to reach number one, at age 19.
Charness notes that “Younger players are getting skilled faster than they used to,” thanks, in part, to better tools and better feedback: Sophisticated computer engines, databases, the ability to play players of any level at any time of the day.
“If you’re talking about two novices,” Charness said, when I asked him about my daughter, me, and chess, “Your daughter would probably pick things up about twice as fast as you could.” My daughter is, in effect, learning chess like a first language, whereas I am learning it like a second language.
Was it just age, or was my daughter just an inherently better player?
Even if I was only learning chess for the first time, I had a lifetime of play behind me.
As Daniel King, a London-based retired professional chess player who now analyzes and commentates chess matches, tells me, “Children just kind of go for it-that kind of confidence can be very disconcerting for the opponent.” Lacking larger representational “Schema,” the psychologist Dianne Horgan has noted, children players rely more on simple heuristics and “Satisficing,” choosing the first good-looking move.
She played, in those games, as if I were just some lower-level chess engine making haplessly random moves.
For whatever the games had taught me about brains young and old, about the different ways we learn and deploy our cognitive resources, they also taught me that the only thing harder than losing to your daughter in chess is winning against her.

The orginal article.

Summary of “The First Lesson of Marriage 101: There Are No Soul Mates”

Nowadays, when colleges and universities offer courses on the topic of marriage, rather than explicitly offering practical marriage advice, they often survey the institution of marriage from a historical point of view or look at larger sociological trends.
Today’s marriage education classes are most often aimed at high-school students, usually as part of a home economics or health class, where teens are taught how family structure affects child well-being, learn basic relationship and communication skills, or are required to carry around a sack filled with flour for a week so they can learn what is entailed in being responsible for a baby 24 hours a day.
Other courses are taught at specifically religious colleges, or are meant for engaged couples, like Pre-Cana, a marriage prep course required of all couples desiring to marry in a Catholic church.
Northwestern’s Marriage 101 is unique among liberal arts universities in offering a course that is comprehensively and directly focused on the experiential, on self-exploration: on walking students through the actual practice of learning to love well.
While popular culture often depicts love as a matter of luck and meeting the right person, after which everything effortlessly falls into place, learning how to love another person well, Solomon explains, is anything but intuitive.
“The foundation of our course is based on correcting a misconception: that to make a marriage work, you have to find the right person. The fact is, you have to be the right person,” Solomon declares.
To help students recognize what has shaped their views on love, she and her colleagues have students extensively interview their own parents about their own relationship.
Maddy Bloch, who took the course two years ago along with her boyfriend at the time, learned a lot when she interviewed her own parents about their own marriage, despite the fact that they are divorced.

The orginal article.

Summary of “13 Edtech Tools Every Teacher and Student Should Know About”

From interactive whiteboards to educational applications, here are 13 edtech tools that every teacher and student to aid and enhance teaching and learning.
Teaching and Learning AppsThere are many educational apps that were created to enhance teaching and learning, tools for knowledge sharing, instruction, collaboration, practice, productivity, and assessment.
6 EdmodoEdmodo has “The largest global teacher network.” It’s a place akin to a digital classroom, where teachers, students, and even parents get to be involved in education.
In Edmodo, users can find thousands of teacher resources - from articles to videos vetted by other teachers - and share their own with rest of the world.
FlipGrid connects teachers and learners and changes how they teach, learn, and interact.
8 FormativeFormative is a great tool for individualized and real-time feedbacking between teacher and student.
Teachers can jump in and provide real-time help when a student is having a hard time answering a question or doing an activity.
Teachers, especially those teaching history and social studies, will find many valuable lesson plans, activities, topics, tips, and hacks to enrich their teaching practice and student learning.

The orginal article.