First: A word about presentation format. For the past dozen years, we have been "power-point-less" at the UIS Center for Online Learning, Research and Service. Rather than using a static, aging format, we prefer to create Web pages for our presentations to assure that they are easily accessible, updatable, and always available. I will not be following every link, and I will not be playing any of the videos in our presentation on the 6th. The intent is that this will serve as a reference meta-site for you on the topic.
Please follow along on your own device (or visit at a later date) to delve more deeply into the links and videos that interest you.
Make no mistake, we have crossed the threshold into the fourth industrial revolution that will most markedly advance this decade through maturing artificial intelligence, ultimately driven by quantum computing. The changes will come at an ever-increasing rate as the technologies and societal demands accelerate. Digital computers advanced over the past half century at approximately the rate described by Moore’s Law, with processing power doubling every two years. Now we are entering the era of Neven’s Law, which predicts the speed of progress of quantum computing at a doubly exponential rate. This means change at a dizzyingly rapid rate that will leave many of us unable to comprehend the why and barely able to digest the daily advances that will describe reality. New platforms, products and processes will proliferate in this new decade.
Now, some definitions:
Artificial Intelligence - the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. https://www.lexico.com/en/definition/artificial%20intelligence
Machine Learning - Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it... learn for themselves. [https://expertsystem.com/machine-learning-definition/ https://www.predictiveanalyticsworld.com/machinelearningtimes/watch-3-videos-from-courseras-new-machine-learning-for-everyone/11555/
Deep Learning - In practical terms, deep learning is just a subset of machine learning. In fact, deep learning technically is machine learning and functions in a similar way (hence why the terms are sometimes loosely interchanged). However, its capabilities are different. While basic machine learning models do become progressively better at whatever their function is, but they still need some guidance. If an AI algorithm returns an inaccurate prediction, then an engineer has to step in and make adjustments. With a deep learning model, an algorithm can determine on its own if a prediction is accurate or not through its own neural network. https://www.zendesk.com/blog/machine-learning-and-deep-learning/
Algorithm - In computing, an algorithm is a precise list of operations that could be done by a Turing machine. For the purpose of computing, algorithms are written in pseudocode, flow charts, or programming languages. . https://simple.m.wikipedia.org/wiki/Algorithm [Ray - example Python]
Supervised and Unsupervised Learning - In a supervised learning model, the algorithm learns on a labeled dataset, providing an answer key that the algorithm can use to evaluate its accuracy on training data. An unsupervised model, in contrast, provides unlabeled data that the algorithm tries to make sense of by extracting features and patterns on its own. https://blogs.nvidia.com/blog/2018/08/02/supervised-unsupervised-learning/
Reinforcement Learning - In this kind of machine learning, AI agents are attempting to find the optimal way to accomplish a particular goal, or improve performance on a specific task. As the agent takes action that goes toward the goal, it receives a reward. The overall aim: predict the best next step to take to earn the biggest final reward. https://blogs.nvidia.com/blog/2018/08/02/supervised-unsupervised-learning/
Self-Coding - Now, using neural networks driven by AI, a host of companies including a group led by Intel, MIT and Georgia Tech are developing self-coding AI programs. These will be designed to enable authors to merely describe the porgrams they desire and the software will generate the code. https://www.technologyreview.com/2020/07/29/1005768/neural-network-similarities-between-programs-help-computers-code-themselves-ai-intel/
Artificial Intelligence in Higher Education: Applications, Promise and Perils, and Ethical Questions - EDUCAUSE Review
What are the benefits and challenges of using artificial intelligence to promote student success, improve retention, streamline enrollment, and better manage resources in higher education? AI is affecting all aspects of higher education: administration, teaching, assessment, student performance and more.
Google Announces Neural-Network Chatbox Meena
Google has released a neural-network powered chatbot called Meena that it claims is better than any other chatbot out there. Data slurp: Meena was trained on a whopping 341GB of public social-media chatter—8.5 times as much data as OpenAI’s GPT-2. Google says Meena can talk about pretty much anything, and can even make up (bad) jokes. Google says it won’t be releasing a public demo until it has vetted the model for safety and bias, which is probably a good thing. When Microsoft released its chatbot Tay on Twitter in 2016 it started spewing racist, misogynistic invective within hours.
AI musicians have emerged - Aiva https://youtu.be/HAfLCTRuh7U and https://youtu.be/gA03iyI3yEA, with voiced singing https://youtu.be/4MKAf6YX_7M , and more - they have a following! Impact is coming for music education.
https://www.digitaltrends.com/cool-tech/auxuman-ai-album/
Saraj Raval explains how it is done:
AI that summarizes research for faculty and students.
AI passes 12th grade science test; not just regurgitating facts, this test requires cognitive reasoning:
https://www.vox.com/future-perfect/2019/9/13/20863269/ai-aristo-science-test-allen-institute
EssayBot will write your student essays - perhaps not an "A" - but credible.
https://www.vox.com/the-goods/2019/4/15/18311367/essaybot-ai-homework-passing
https://futurism.com/grad-student-neural-network-write-papers
You are reading AI-written reports every day (many are written from AI-gathered research as well) - in Bloomberg (1/3 of all reports), Washington Post, Forbes, Guardian, Associated Press and many more.
https://www.nytimes.com/2019/02/05/business/media/artificial-intelligence-journalism-robots.html
https://techhq.com/2019/09/writing-and-research-tools-the-future-of-the-newsroom/
Quantum Computing will enable advance AI in ways we have yet to full understand, however, we know it will allow incredibly massive datasets to be analyzed in the blink of an eye. It will bring breakthroughs in fields such as meteorology, medicine, and education where we can assemble massive-scale data that can be combed for causality, prediction, and previously unrecognized connections.
Quantum Computing Is Poised to Change Everything
Ray Schroeder, Inside Higher Ed
It is truly rare that an advancement comes along that changes every aspect of society; quantum computing is poised to do just that in the 2020s. Do you recall Moore’s law? That’s the axiom developed by Gordon Moore some two dozen years ago that the processing power of computers would double every 18 months to two years. Now, quantum computing has ushered in Hartmut Neven’s law. His law predicting growth in quantum computing power is one that is doubly exponential. That is two to an exponent of two to a second increasing exponent. Charted on a graph, that growth rate appears to become nearly vertical.
Quantum Information and AI - Alex Moltzau, Towards Data Science
“In physics and computer science, quantum information is the information of the state of a quantum system. It is the basic entity of study in quantum information theory, and can be manipulated using quantum information processing techniques.” “Quantum neural networks (QNNs) are neural network models which are based on the principles of quantum mechanics. There are two different approaches to QNN research, one exploiting quantum information processing to improve existing neural network models (sometimes also vice versa), and the other one searching for potential quantum effects in the brain.”
https://towardsdatascience.com/quantum-computing-and-ai-789fc9c28c5b
Quantum Computing in Higher Ed
Quantum computing is not an incremental step in the advancement of computing. It is - pardon the phrase - a quantum leap!
According to the Financial Times report, the paper said that Google’s quantum processor was able to perform a calculation in three minutes and 20 seconds that would take today’s most advanced supercomputer, known as Summit, around 10,000 years.
Quantum Computing Roundup - HPC
Advances are taking place in the blink of an eye. Universities are assisting in the development and refinement of ever-larger quantum computers. Applications in education - as will almost every field - are astounding. Unimaginably large datasets and nearly unfathomably complex algorithms combined with superposition and entanglement features to make these computers the key component in changing civilization and life as we know it.
Einstein called it "Spooky": Quantum Entanglement
It affords connected actions at speeds exceeding the speed of light by means we do not yet fully understand. It opens the door to a whole new level of privacy and connectivity. Quantum entanglement is thought to be one of the trickiest concepts in science, but the core issues are simple. And once understood, entanglement opens up a richer understanding of concepts such as the “many worlds” of quantum theory.
https://www.quantamagazine.org/entanglement-made-simple-20160428/
Quantum entanglement over 30 miles of fiber has brought super secure internet closer - Douglas Heaven, Technology Review
Albert Einstein wanted nothing to do with it: he mocked the strange concept of quantum entanglement as “spooky action at a distance.” But a hundred years on, Einstein’s bugbear could help create a more secure internet, thanks to the most reliable technique yet for entangling nodes along miles of fiber-optic cable. With entanglement, an object can be put into a quantum superposition of multiple states—like Schrödinger’s cat, both alive and dead at once—and that superposition can be shared with another object. In theory, these objects will maintain that connection even when separated, so that measuring one reveals the state of the other, no matter how far away.
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Contact Ray
rschr1@uis.edu ~ rayschroeder@gmail.com - ray@upcea.edu
Associate Vice Chancellor for Online, Professor Emeritus
University of Illinois Springfield
Senior Fellow, University Professional and Continuing Education Assn.
217-206-7531