Sejnowski, T. J. (2018). The Deep Learning Revolution. Cambridge, MA: The MIT Press.
How deep learning―from Google Translate to driverless cars to personal cognitive assistants―is changing our lives and transforming every sector of the economy.
The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy.
Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.
Buzzwords like “deep learning” and “neural networks” are everywhere, but so much of the popular understanding is misguided, says Terrence Sejnowski, a computational neuroscientist at the Salk Institute for Biological Studies.
Sejnowski, a pioneer in the study of learning algorithms, is the author of The Deep Learning Revolution(out next week from MIT Press). He argues that the hype about killer AI or robots making us obsolete ignores exciting possibilities happening in the fields of computer science and neuroscience, and what can happen when artificial intelligence meets human intelligence.
Machine learning is a very large field and goes way back. Originally, people were calling it “pattern recognition,” but the algorithms became much broader and much more sophisticated mathematically. Within machine learning are neural networks inspired by the brain, and then deep learning. Deep learning algorithms have a particular architecture with many layers that flow through the network. So basically, deep learning is one part of machine learning and machine learning is one part of AI.
December 2012 at the NIPS meeting, which is the biggest AI conference. There, [computer scientist] Geoff Hinton and two of his graduate students showed you could take a very large dataset called ImageNet, with 10,000 categories and 10 million images, and reduce the classification error by 20 percent using deep learning.Traditionally on that dataset, error decreases by less than 1 percent in one year. In one year, 20 years of research was bypassed. That really opened the floodgates.
The inspiration for deep learning really comes from neuroscience.
AlphaGo, the program that beat the Go champion included not just a model of the cortex, but also a model of a part of the brain called the basal ganglia, which is important for making a sequence of decisions to meet a goal. There’s an algorithm there called temporal differences, developed back in the ‘80s by Richard Sutton, that, when coupled with deep learning, is capable of very sophisticated plays that no human has ever seen before.
there’s a convergence occurring between AI and human intelligence. As we learn more and more about how the brain works, that’s going to reflect back in AI. But at the same time, they’re actually creating a whole theory of learning that can be applied to understanding the brain and allowing us to analyze the thousands of neurons and how their activities are coming out. So there’s this feedback loop between neuroscience and AI
“Shifts in students’ learning style will prompt a shift to active construction of knowledge through mediated immersion.”-Chris Dede
The theory of constructivist-based learning, according to Dr. Seymour Papert, “is grounded in the idea that people learn by actively constructing new knowledge, rather than having information ‘poured’ into their heads.”
Moreover, constructionism asserts that people learn with particular effectiveness when they are engaged in constructing personally meaningful artifacts (such as computer programs, animations, 3D modeling, creating spatial environments in virtual reality or building robots).”
Technologies like virtual reality, especially for Gen Z students’, provides avenues that allow them to engage in a social, collaborative, and active learning environment.
Virtual reality, especially when combined with powerful storytelling, allows the student to participate in the story, develop empathy to experiences outside their current realm of understanding and allows them to be fully immersed in their own exploration and learning.
U.S. retail giant Walmart has applied to the U.S. Patent & Trademark Office (USPTO) to patent a blockchain system for deliveries, according to an official patent document released August 30.
Walmart has applied for a number of blockchain-related patents in the U.S. in the past year. According to Investopedia, blockchain technology enhancement is mainly being used by the retailed in order to “help Walmart keep pace with its rivals,” such as Amazon.
Recently, Walmart applied for a patent on systems and methods for managing smart appliances via blockchain. The tech would allow users to customize levels of access and control for appliances such as portable computing devices.
In mid-July, the retail giant patented the technology for a blockchain-powered delivery management system that can keep delivered items safe until their purchasers are able to sign for and collect them.
In Media Manipulation and Disinformation Online, Marwick and Lewis (2017) of the Data & Society Research Institute described the agents of media manipulation, their modus operandi, motivators, and how they’ve taken advantage of the vulnerability of online media. The researchers described the manipulators as right-wing extremists (RWE), also known as alt-right, who run the gamut from sexists (including male sexual conquest communities) to white nationalists to anti-immigration activists and even those who rebuke RWE identification but whose actions confer such classification. These manipulators rally behind a shared belief on online forums, blogs, podcasts, and social media through pranks or ruinous trolling anonymity, usurping participatory culture methods (networking, humor, mentorship) for harassment, and competitive cyber brigades that earn status by escalating bullying such as the sharing of a target’s private information.
Marwick and Lewis reported on how RWE groups have taken advantage of certain media tactics to gain viewers’ attention such as novelty and sensationalism, as well as their interactions with the public via social media, to manipulate it for their agenda. For instance, YouTube provides any individual with a portal and potential revenue to contribute to the media ecosystem. The researchers shared the example of the use of YouTube by conspiracy theorists, which can be used as fodder for extremist networks as conspiracies generally focus on loss of control of important ideals, health, and safety.
One tactic they’re using is to package their hate in a way that appeals to millennials. They use attention hacking to increase their status such as hate speech, which is later recanted as trickster trolling all the while gaining the media’s attention for further propagation
SHARED MODUS OPERANDI
Marwick and Lewis reported the following shared tactics various RWE groups use for online exploits:
Ambiguity of persona or ideology,
Baiting a single or community target’s emotions,
Bots for amplification of propaganda that appears legitimately from a real person,
“…Embeddedness in Internet culture… (p. 28),”
Exploitation of young male rebelliousness,
Hate speech and offensive language (under the guise of First Amendment protections),
Irony to cloak ideology and/or skewer intended targets,
Memes for stickiness of propaganda,
Mentorship in argumentation, marketing strategies, and subversive literature in their communities of interest,
Networked and agile groups,
“…Permanent warfare… (p.12)” call to action,
Pseudo scholarship to deceive readers,
“…Quasi moral arguments… (p. 7)”
Shocking images for filtering network membership,
“Trading stories up the chain… (p. 38)” from low-level news outlets to mainstream, and
Trolling others with asocial behavior.
teenagers in Veles, Macedonia who profited around 16K dollars per month via Google’s AdSense from Facebook post engagements
a long history of mistrust with mainstream media
If you’re a college instructor of communications or teach digital literacy as a librarian, see the corresponding syllabus for this article. It provides discussion questions and assignments for teaching students about media manipulation. To teach your students how to combat fake news online, see my post on Navigating Post-Truth Societies: Strategies, Resources, and Technologies.
the trending but undefined concepts of digital storytelling and immersive learning
definition
Storytelling is a logical form of thought. It is an analytical process including perception, labeling, organizing, categorizing real and imaginary objects and their real and imaginary relations in speech.
Q: What do you think immersive documentation technologies such as 360 images and videos can bring to this process?
V: 360 degree media and virtual reality are cultural-historically developed tools that mediate our relationship to the world in a new way. They expand the possible fields of perception transcending space and time. Perception precedes other psychological functions.
Definition
Immersive storytelling can be understood as an activity through which students use language to visualize relations and meaning in 360 degree digital environments. Naming or describing relations between objects in our field of perception using verbal or visual language awakens intellectual processes fundamental to learning.
Q: Would you say immersive storytelling is a form of creative play?
V: That is a possible interpretation. Play is a psychological process through which we create an imaginary situation or place, reflecting or separating objects and their actual meaning, or creating new meanings. The ability to digitally create and modify situations and environments can be understood as a form of play, opening a realm of spontaneity and freedom, connected with pleasure.
Q: Can robots help us learn? Is AI already the More Knowledgeable Other?
V: The More Knowledgeable Other (MKO) refers to anyone or anything who has a better understanding or a higher ability level than the learner, with respect to a particular task, process, or concept. If a robot with artificial intelligence can function as an MKO and support our problem solving, it can expand our Zone of Proximal Development.
https://www-wired-com.cdn.ampproject.org/c/s/www.wired.com/story/187-things-the-blockchain-is-supposed-to-fix/amp
Blockchains, which use advanced cryptography to store information across networks of computers, could eliminate the need for trusted third parties, like banks, in transactions, legal agreements, and other contracts. The most ardent blockchain-heads believe it has the power to reshape the global financial system, and possibly even the internet as we know it.
Now, as the technology expands from a fringe hacker toy to legitimate business applications, opportunists have flooded the field. Some of the seekers are mercenaries pitching shady or fraudulent tokens, others are businesses looking to cash in on a hot trend, and still others are true believers in the revolutionary and disruptive powers of distributed networks.
Mentions of blockchains and digital currencies on corporate earnings calls doubled in 2017 over the year prior, according to Fortune. Last week at Consensus, the country’s largest blockchain conference, 100 sponsors, including top corporate consulting firms and law firms, hawked their wares.
Here is a noncomprehensive list of the ways blockchain promoters say they will change the world. They run the spectrum from industry-specific (a blockchain project designed to increase blockchain adoption) to global ambitions (fixing the global supply chain’s apparent $9 trillion cash flow issue).
Things Blockchain Technology Will Fix
Bots with nefarious intent
Skynet
People not taking their medicine
Device storage that could be used for bitcoin mining
despite China’s many technological advances, in this new cyberspace race, the West had the lead.
Xi knew he had to act. Within twelve months he revealed his plan to make China a science and technology superpower. By 2030 the country would lead the world in AI, with a sector worth $150 billion. How? By teaching a generation of young Chinese to be the best computer scientists in the world.
Today, the US tech sector has its pick of the finest minds from across the world, importing top talent from other countries – including from China. Over half of Bay Area workers are highly-skilled immigrants. But with the growth of economies worldwide and a Presidential administration hell-bent on restricting visas, it’s unclear that approach can last.
In the UK the situation is even worse. Here, the government predicts there’ll be a shortfall of three million employees for high-skilled jobs by 2022 – even before you factor in the immigration crunch of Brexit. By contrast, China is plotting a homegrown strategy of local and national talent development programs. It may prove a masterstroke.
In 2013 the city’s teenagers gained global renown when they topped the charts in the PISA tests administered every three years by the OECD to see which country’s kids are the smartest in the world. Aged 15, Shanghai students were on average three full years ahead of their counterparts in the UK or US in maths and one-and-a-half years ahead in science.
Teachers, too, were expected to be learners. Unlike in the UK, where, when I began to teach a decade ago, you might be working on full-stops with eleven-year-olds then taking eighteen-year-olds through the finer points of poetry, teachers in Shanghai specialised not only in a subject area, but also an age-group.
Shanghai’s success owed a lot to Confucian tradition, but it fitted precisely the best contemporary understanding of how expertise is developed. In his book Why Don’t Kids Like School? cognitive Dan Willingham explains that complex mental skills like creativity and critical thinking depend on our first having mastered the simple stuff. Memorisation and repetition of the basics serve to lay down the neural architecture that creates automaticity of thought, ultimately freeing up space in our working memory to think big.
Seung-bin Lee, a seventeen-year-old high school graduate, told me of studying fourteen hours a day, seven days a week, for the three years leading up to the Suneung, the fearsome SAT exam taken by all Korean school leavers on a single Thursday each November, for which all flights are grounded so as not to break students’ concentration during the 45 minutes of the English listening paper.
Korea’s childhoods were being lost to a relentless regime of studying, crushed in a top-down system that saw them as cyphers rather than kids.
A decade ago, we consoled ourselves that although kids in China and Korea worked harder and did better on tests than ours, it didn’t matter. They were compliant, unthinking drones, lacking the creativity, critical thinking or entrepreneurialism needed to succeed in the world. No longer. Though there are still issues with Chinese education – urban centres like Shanghai and Hong Kong are positive outliers – the country knows something that we once did: education is the one investment on which a return is guaranteed. China is on course to becoming the first education superpower.
Troublingly, where education in the UK and US has been defined by creativity and independent thinking – Shanghai teachers told me of visits to our schools to learn about these qualities – our direction of travel is now away from those strengths and towards exams and standardisation, with school-readiness tests in the pipeline and UK schools minister Nick Gibb suggesting kids can beat exam stress by sitting more of them. Centres of excellence remain, but increasingly, it feels, we’re putting our children at risk of losing out to the robots, while China is building on its strong foundations to ask how its young people can be high-tech pioneers. They’re thinking big – we’re thinking of test scores.
soon “digital information processing” would be included as a core subject on China’s national graduation exam – the Gaokao – and pictured classrooms in which students would learn in cross-disciplinary fashion, designing mobile phones for example, in order to develop design, engineering and computing skills. Focusing on teaching kids to code was short-sighted, he explained. “We still regard it as a language between human and computer.” (My note: they are practically implementing the Finland’s attempt to rebuild curricula)
“If your plan is for one year,” went an old Chinese saying, “plant rice. If your plan is for ten years, plant trees. If your plan is for 100 years, educate children.” Two and half thousand years later chancellor Gwan Zhong might update his proverb, swapping rice for bitcoin and trees for artificial intelligence, but I’m sure he’d stand by his final point.
Here’s how to evaluate the potential for mobile solutions
Before they set foot in their first class, incoming college students face a maze of requirements and resources that will be critical to their success. So-called “student supports” abound. Yet forty percent of first-year studentsdon’t return the following year, and a growing number report information overload as they navigate campus life amid newfound independence.
The nine in 10 undergraduates who own smartphones are probably familiar with the xkcd about it. College-aged Americans check their devices more than 150 times per day. So it should be no surprise that a growing body of research suggests that mobile solutions can play a critical role in enhancing the student experience.
1. Is the mobile app native?
We’ve all had the frustrating experience of using a smartphone to navigate a page that was designed for a computer. But when designing native mobile apps, developers start with the small screen, which leads to simpler, cleaner platforms that get rid of the clutter of the desktop browsing experience.
As smartphones overtake laptops and desktops as the most popular way for young people to get online, native design is critical for universities to embrace.
2. Is there a simple content management system?
It’s also critical to explore whether mobile apps integrate with an institution’s existing LMS, CMS, and academic platforms. The most effective apps will allow you to draw upon and translate existing content and resources directly into the mobile experience. My note: this is why it is worth experimenting with alternatives to LMS, such as Facebook Groups: they allow ready-to-use SIMPLE mobile interface.
3. Does it allow you to take targeted action?
At-risk or disengaged students often require more targeted communication and engagement which, if used effectively, can prevent them falling into those categories in the first place.
Unlike web-based tools, mobile apps should not only communicate information, but also generate insights and reports, highlighting key information into how students use the platform.
4. Does it offer communication and social networking opportunities?
Teenagers who grew up with chatbots and Snapchat expect instant communication to be part of any online interaction. Instead of making students toggle between the student affairs office and conversations with advisors, mobile platforms that offer in-app messaging can streamline the experience and keep users engaged.
until recently, broadcasting and publishing were difficult and expensive affairs, their infrastructures riddled with bottlenecks and concentrated in a few hands.
When protests broke out in Ferguson, Missouri, in August 2014, a single livestreamer named Mustafa Hussein reportedly garnered an audience comparable in size to CNN’s for a short while. If a Bosnian Croat war criminal drinks poison in a courtroom, all of Twitter knows about it in minutes.
In today’s networked environment, when anyone can broadcast live or post their thoughts to a social network, it would seem that censorship ought to be impossible. This should be the golden age of free speech.
And sure, it is a golden age of free speech—if you can believe your lying eyes. Is that footage you’re watching real? Was it really filmed where and when it says it was? Is it being shared by alt-right trolls or a swarm of Russian bots? My note: see the ability to create fake audio and video footage: https://blog.stcloudstate.edu/ims/2017/07/15/fake-news-and-video/
HERE’S HOW THIS golden age of speech actually works: In the 21st century, the capacity to spread ideas and reach an audience is no longer limited by access to expensive, centralized broadcasting infrastructure. It’s limited instead by one’s ability to garner and distribute attention. And right now, the flow of the world’s attention is structured, to a vast and overwhelming degree, by just a few digital platforms: Facebook, Google (which owns YouTube), and, to a lesser extent, Twitter.
at their core, their business is mundane: They’re ad brokers
They use massive surveillance of our behavior, online and off, to generate increasingly accurate, automated predictions of what advertisements we are most susceptible to and what content will keep us clicking, tapping, and scrolling down a bottomless feed.
in reality, posts are targeted and delivered privately, screen by screen by screen. Today’s phantom public sphere has been fragmented and submerged into billions of individual capillaries. Yes, mass discourse has become far easier for everyone to participate in—but it has simultaneously become a set of private conversations happening behind your back. Behind everyone’s backs.
It’s important to realize that, in using these dark posts, the Trump campaign wasn’t deviantly weaponizing an innocent tool. It was simply using Facebook exactly as it was designed to be used. The campaign did it cheaply, with Facebook staffers assisting right there in the office, as the tech company does for most large advertisers and political campaigns.