IBM and Japan join hands in the development of quantum computers – Neowin

Back in September, IBM Q announced a host of new tools catered to making quantum computing more accessible. Amongst the new additions were a bunch of 5-qubit quantum computers, which extended the IBM's fleet of quantum computers.

Today, IBM has taken yet another step in the same direction. The tech giant IBM has partnered with the University of Tokyo forming the Japan IBM Quantum Partnership to advance quantum computing and use it to benefit science, industry, and society. Essentially, the partnership will have three 'tracks of engagement':

...one focused on the development of quantum applications with industry; another on quantum computing system technology development; and the third focused on advancing the state of quantum science and education.

But one of the most marked developments under the agreement is that the IBM Q System One will be installed in an IBM facility in Japan. This feat will make Japan the third country to house such an installation after the United States and Germany, and the only one in the region to do so. Once in Japan, the System One will delve into research on quantum algorithms and the development of practical applications leveraging the power of the quantum realm.

Besides directly collaborating on research topics, IBM and the University of Tokyo will also establish a novel quantum system technology center under the same agreement. This center will be primarily focused on developing and testing hardware for quantum computers and in particular, will focus on cryogenic and microwave test capabilities for the same.

Vis--vis the initiative, the Director of IBM Research, Dario Gil, was hopeful that it will lead to the expansion of quantum computing in Japan and have various added advantages:

"This partnership will spark Japan's quantum research capabilities by bringing together experts from industry, government and academia to build and grow a community that underpins strategically significant research and development activities to foster economic opportunities across Japan."

While the President of the University of Tokyo, Makoto Gonokami, emphasized the relevance of quantum computing and what the initiative entails for Japan:

"Quantum computing is one of the most crucial technologies in the coming decades, which is why we are setting up this broad partnership framework with IBM, who is spearheading its commercial application. We expect this effort to further strengthen Japan's quantum research and development activities and build world-class talent."

As such, in addition to all of the above, the University of Tokyo will also be giving high priority to quantum programming and technical development of its students and researchers to help push the envelope of quantum computing.

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IBM and Japan join hands in the development of quantum computers - Neowin

Quantum Technology Expert to Discuss Quantum Sensors for Defense Applications at Office of Naval Research (ONR) – Business Wire

ARLINGTON, Va.--(BUSINESS WIRE)--Michael J. Biercuk, founder and CEO of Q-CTRL, will describe how quantum sensors may provide exceptional new capabilities to the warfighter at the Office of Naval Research (ONR) on Jan. 13, 2020, as part of the ONRs 2020 Distinguished Lecture Series.

Quantum sensing is considered one of the most promising areas in the global research effort to leverage the exotic properties of quantum physics for real-world benefit. In his lecture titled Quantum Control as a Means to Improve Quantum Sensing in Realistic Environments, Biercuk will describe how new concepts in quantum control engineering applied to these sensors could dramatically enhance standoff detection and precision navigation and timing in military settings.

Biercuk is one of the worlds leading experts in the field of quantum technology. In 2017, he founded Q-CTRL based on research he led at the Quantum Control Lab at the University of Sydney, where he is a professor of Quantum Physics and Quantum Technology.

Funded by some of the worlds leading investors, including Silicon Valley-based Sierra Ventures and Sequoia Capital, Q-CTRL is dedicated to helping teams realize the true potential of quantum hardware, from sensing to quantum computing. In quantum computing, the team is known for its efforts in reducing hardware errors caused by environmental noise. Computational errors are considered a major obstacle in the development of useful quantum computers and sought-after breakthroughs in science and industry.

Now in its 11th year, the ONR Distinguished Lecture Series features groundbreaking innovators who have made a major impact on past research or are working on discoveries for the future. It is designed to stimulate discussion and collaboration among scientists and engineers representing Navy research, the Department of Defense, industry and academia.

Past speakers include Michael Posner, recipient of the National Medal of Science; Mark Hersam, MacArthur Genius Award recipient and leading experimentalist in the field of nanotechnology; and Dr. Robert Ballard, the deep-sea explorer best-known for recovering the wreck of the RMS Titanic.

I am honored to be taking part in this renowned lecture series, Biercuk said. Quantum technology, which harnesses quantum physics as a resource, is likely to be as transformational in the 21st century as harnessing electricity was in the 19th. I look forward to sharing insights into how Q-CTRLs efforts can accelerate the development of this new field of technology for defense applications.

About the Office of Naval Research

The Department of the Navys Office of Naval Research provides the science and technology necessary to maintain the Navy and Marine Corps technological advantage. Through its affiliates, ONR is a leader in science and technology with engagement in 50 states, 55 countries, 634 institutions of higher learning and nonprofit institutions, and more than 960 industry partners.

ABOUT Q-CTRL

Q-CTRL was founded in November 2017 and is a venture-capital-backed company that provides control-engineering software solutions to help customers harness the power of quantum physics in next-generation technologies.

Q-CTRL is built on Professor Michael J. Biercuks research leading the Quantum Control Lab at the University of Sydney, where he is a Professor of Quantum Physics and Quantum Technology.

The teams expertise led Q-CTRL to be selected as an inaugural member of the IBM Q startup network in 2018. Q-CTRL is funded by SquarePeg Capital, Sierra Ventures, Sequoia Capital China, Data Collective, Horizons Ventures and Main Sequence Ventures.

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Quantum Technology Expert to Discuss Quantum Sensors for Defense Applications at Office of Naval Research (ONR) - Business Wire

16 Artificial Intelligence Pros and Cons Vittana.org

Artificial intelligence, or AI, is a computer system which learns from the experiences it encounters. It can adjust on its own to new inputs, allowing it to perform tasks in a way that is similar to what a human would do. How we have defined AI over the years has changed, as have the tasks weve had these machines complete.

As a term, artificial intelligence was defined in 1956. With increasing levels of data being processed, improved storage capabilities, and the development of advanced algorithms, AI can now mimic human reasoning. AI personal assistants, like Siri or Alexa, have been around for military purposes since 2003.

With these artificial intelligence pros and cons, it is important to think of this technology as a decision support system. It is not the type of AI from science-fiction stories which attempts to rule the world by dominating the human race.

1. Artificial intelligence completes routine tasks with ease.Many of the tasks that we complete every day are repetitive. That repetition helps us to get into a routine and positive work flow. It also takes up a lot of our time. With AI, the repetitive tasks can be automated, finely tuning the equipment to work for extended time periods to complete the work. That allows human workers to focus on the more creative elements of their job responsibilities.

2. Artificial intelligence can work indefinitely.Human workers are typically good for 8-10 hours of production every day. Artificial intelligence can continue operating for an indefinite time period. As long as there is a power resource available to it, and the equipment is properly cared for, AI machines do not experience the same dips in productivity that human workers experience when they get tired at the end of the day.

3. Artificial intelligence makes fewer errors.AI is important within certain fields and industries where accuracy or precision is the top priority. When there are no margins for error, these machines are able to breakdown complicated math constructs into practical actions faster, and with more accuracy, when compared to human workers.

4. Artificial intelligence helps us to explore.There are many places in our universe where it would be unsafe, if not impossible, for humans to see. AI makes it possible for us to learn more about these places, which furthers our species knowledge database. We can explore the deepest parts of the ocean because of AI. We can journey to inhospitable planets because of AI. We can even find new resources to consume because of this technology.

5. Artificial intelligence can be used by anyone.There are multiple ways that the average person can embrace the benefits of AI every day. With smart homes powered by AI, thermostat and energy regulation helps to cut the monthly utility bill. Augmented reality allows consumers to picture items in their own home without purchasing them first. When it is correctly applied, our perception of reality is enhanced, which creates a positive personal experience.

6. Artificial intelligence makes us become more productive.AI creates a new standard for productivity. It will also make each one of us more productive as well. If you are texting someone or using word processing software to write a report and a misspelled word is automatically corrected, then youve just experienced a time benefit because of AI. An artificial intelligence can sift through petabytes of information, which is something the human brain is just not designed to do.

7. Artificial intelligence could make us healthier.Every industry benefits from the presence and use of AI. We can use AI to establish healthier eating habits or to get more exercise. It can be used to diagnose certain diseases or recommends a treatment plan for something already diagnosed. In the future, AI might even assist physicians who are conducting a surgical procedure.

8. Artificial intelligence extends the human experience.With an AI helping each of us, we have the power to do more, be more, and explore more than ever before. In some ways, this evolutionary process could be our destiny. Some believe that computers and humanity are not separate, but instead a single, cognitive unit that already works together for the betterment of all. Through AI, people who are blind can now see. Those who are deaf can now hear. We become better because we have a greater capacity to do thins.

1. Artificial intelligence comes with a steep price tag.A new artificial intelligence is costly to build. Although the price is coming down, individual developments can still be as high as $300,000 for a basic AI. For small businesses operating on tight margins or low initial capital, it may be difficult to find the cash necessary to take advantage of the benefits which AI can bring. For larger companies, the cost of AI may be much higher, depending upon the scope of the project.

2. Artificial intelligence will reduce employment opportunities.There will be jobs gained because of AI. There will also be jobs lost because of it. Any job which features repetitive tasks as part of its duties is at-risk of being replaced by an artificial intelligence in the future. In 2017, Gartner predicted that 500,000 net jobs would be created because of AI. On the other end of the spectrum, up to 900,000 jobs could be lost because of it. Those figures are for jobs only within the United States.

3. Artificial intelligence will be tasked with its own decisions.One of the greatest threats we face with AI is its decision-making mechanism. An AI is only as intelligent and insightful as the individuals responsible for its initial programming. That means there could be a certain bias found within is mechanisms when it is time to make an important decision. In 2014, an active shooter situation caused people to call Uber to escape the area. Instead of recognizing the dangerous situation, the algorithm Uber used saw a spike in demand, so it decided to increase prices.

4. Artificial intelligence lacks creativity.We can program robots to perform creative tasks. Where we stall out in the evolution of AI is creating an intelligence which can be originally creative on its own. Our current AI matches the creativity of its creator. Because there is a lack of creativity, there tends to be a lack of empathy as well. That means the decision of an AI is based on what the best possible analytical solution happens to be, which may not always be the correct decision to make.

5. Artificial intelligence can lack improvement.An artificial intelligence may be able to change how it reacts in certain situations, much like a child stops touching a hot stove after being burned by it. What it does not do is alter its perceptions, responses, or reactions when there is a changing environment. There is an inability to distinguish specific bits of information observed beyond the data generated by that direct observation.

6. Artificial intelligence can be inaccurate.Machine translations have become an important tool in our quest to communicate with one another universally. The only problem with these translations is that they must be reviewed by humans because the words, not the intent of the words, is what machines translate. Without a review by a trained human translator, the information received from a machine translation may be inaccurate or insensitive, creating more problems instead of fewer with our overall communication.

7. Artificial intelligence changes the power structure of societies.Because AI offers the potential to change industries and the way we live in numerous ways, societies experience a power shift when it becomes the dominant force. Those who can create or control this technology are the ones who will be able to steer society toward their personal vision of how people should be. It also removes the humanity out of certain decisions, like the idea of having autonomous AI responsible for warfare without humans actually initiating the act of violence.

8. Artificial intelligence treats humanity as a commodity.When we look at the possible outcomes of AI on todays world, the debate is often about how many people benefit compared to how many people will not. The danger here is that people are treated as a commodity. Businesses are already doing this, looking at the commodity of automation through AI as a better investment than the commodity of human workers. If we begin to perceive ourselves as a commodity only, then AI will too, and the outcome of that decision could be unpredictable.

These artificial intelligence pros and cons show us that our world can benefit from its presence in a variety of ways. There are also many potential dangers which come with this technology. Jobs may be created, but jobs will be lost. Lives could be saved, but lives could also be lost. That is why the technologies behind AI must be made available to everyone. If only a few hold the power of AI, then the world could become a very different place in a short period of time.

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16 Artificial Intelligence Pros and Cons Vittana.org

Top 45 Artificial Intelligence ETFs – ETFdb.com

This is a list of all Artificial Intelligence ETFs traded in the USA which are currently tagged by ETF Database. Please note that the list may not contain newly issued ETFs. If youre looking for a more simplified way to browse and compare ETFs, you may want to visit our ETFdb Categories, which categorize every ETF in a single best fit category.

This page includes historical return information for all Artificial Intelligence ETFs listed on U.S. exchanges that are currently tracked by ETF Database.

The table below includes fund flow data for all U.S. listed Artificial Intelligence ETFs. Total fund flow is the capital inflow into an ETF minus the capital outflow from the ETF for a particular time period.

Fund Flows in millions of U.S. Dollars.

The following table includes expense data and other descriptive information for all Artificial Intelligence ETFs listed on U.S. exchanges that are currently tracked by ETF Database. In addition to expense ratio and issuer information, this table displays platforms that offer commission-free trading for certain ETFs.

Clicking on any of the links in the table below will provide additional descriptive and quantitative information on Artificial Intelligence ETFs.

The following table includes ESG Scores and other descriptive information for all Artificial Intelligence ETFs listed on U.S. exchanges that are currently tracked by ETF Database. Easily browse and evaluate ETFs by visiting our Responsible Investing themes section and find ETFs that map to various environmental, social and governance themes.

This page includes historical dividend information for all Artificial Intelligence listed on U.S. exchanges that are currently tracked by ETF Database. Note that certain ETFs may not make dividend payments, and as such some of the information below may not be meaningful.

The table below includes basic holdings data for all U.S. listed Artificial Intelligence ETFs that are currently tagged by ETF Database. The table below includes the number of holdings for each ETF and the percentage of assets that the top ten assets make up, if applicable. For more detailed holdings information for any ETF, click on the link in the right column.

The following table includes certain tax information for all Artificial Intelligence ETFs listed on U.S. exchanges that are currently tracked by ETF Database, including applicable short-term and long-term capital gains rates and the tax form on which gains or losses in each ETF will be reported.

This page contains certain technical information for all Artificial Intelligence ETFs that are listed on U.S. exchanges and tracked by ETF Database. Note that the table below only includes limited technical indicators; click on the View link in the far right column for each ETF to see an expanded display of the products technicals.

This page provides links to various analyses for all Artificial Intelligence ETFs that are listed on U.S. exchanges and tracked by ETF Database. The links in the table below will guide you to various analytical resources for the relevant ETF, including an X-ray of holdings, official fund fact sheet, or objective analyst report.

This page provides ETFdb Ratings for all Artificial Intelligence ETFs that are listed on U.S. exchanges and tracked by ETF Database. The ETFdb Ratings are transparent, quant-based evaluations of ETFs relative to other products in the same ETFdb.com Category. As such, it should be noted that this page may include ETFs from multiple ETFdb.com Categories.

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Top 45 Artificial Intelligence ETFs - ETFdb.com

Why Cognitive Technology May Be A Better Term Than Artificial Intelligence – Forbes

One of the challenges for those tracking the artificial intelligence industry is that, surprisingly, theres no accepted, standard definition of what artificial intelligence really is. AI luminaries all have slightly different definitions of what AI is. Rodney Brooks says that artificial intelligence doesnt mean one thing its a collection of practices and pieces that people put together. Of course, thats not particularly settling for companies that need to understand the breadth of what AI technologies are and how to apply them to their specific needs.

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In general, most people would agree that the fundamental goals of AI are to enable machines to have cognition, perception, and decision-making capabilities that previously only humans or other intelligent creatures have. Max Tegmark simply defines AI as intelligence that is not biological. Simple enough but we dont fully understand what biological intelligence itself means, and so trying to build it artificially is a challenge.

At the most abstract level, AI is machine behavior and functions that mimic the intelligence and behavior of humans. Specifically, this usually refers to what we come to think of as learning, problem solving, understanding and interacting with the real-world environment, and conversations and linguistic communication. However the specifics matter, especially when were trying to apply that intelligence to solve very specific problems businesses, organizations, and individuals have.

Saying AI but meaning something else

There are certainly a subset of those pursuing AI technologies with a goal of solving the ultimate problem: creating artificial general intelligence (AGI) that can handle any problem, situation, and thought process that a human can. AGI is certainly the goal for many in the AI research being done in academic and lab settings as it gets to the heart of answering the basic question of whether intelligence is something only biological entities can have. But the majority of those who are talking about AI in the market today are not talking about AGI or solving these fundamental questions of intelligence. Rather, they are looking at applying very specific subsets of AI to narrow problem areas. This is the classic Broad / Narrow (Strong / Weak) AI discussion.

Since no one has successfully built an AGI solution, it follows that all current AI solutions are narrow. While there certainly are a few narrow AI solutions that aim to solve broader questions of intelligence, the vast majority of narrow AI solutions are not trying to achieve anything greater than the specific problem the technology is being applied to. What we mean to say here is that were not doing narrow AI for the sake of solving a general AI problem, but rather narrow AI for the sake of narrow AI. Its not going to get any broader for those particular organizations. In fact, it should be said that many enterprises dont really care much about AGI, and the goal of AI for those organizations is not AGI.

If thats the case, then it seems that the industrys perception of what AI is and where it is heading differs from what many in research or academia think. What interests enterprises most about AI is not that its solving questions of general intelligence, but rather that there are specific things that humans have been doing in the organization that they would now like machines to do. The range of those tasks differs depending on the organization and the sort of problems they are trying to solve. If this is the case, then why bother with an ill-defined term in which the original definition and goals are diverging rapidly from what is actually being put into practice?

What are cognitive technologies?

Perhaps a better term for narrow AI being applied for the sole sake of those narrow applications is cognitive technology. Rather than trying to build an artificial intelligence, enterprises are leveraging cognitive technologies to automate and enable a wide range of problem areas that require some aspect of cognition. Generally, you can group these aspects of cognition into three P categories, borrowed from the autonomous vehicles industry:

From this perspective, its clear that while cognitive technologies are indeed a subset of Artificial Intelligence technologies, with the main difference being that AI can be applied both towards the goals of AGI as well as narrowly-focused AI applications. On the other-hand, using the term cognitive technology instead of AI is an acceptance of the fact that the technology being applied borrows from AI capabilities but doesnt have ambitions of being anything other than technology applied to a narrow, specific task.

Surviving the next AI winter

The mood in the AI industry is noticeably shifting. Marketing hype, venture capital dollars, and government interest is all helping to push demand for AI skills and technology to its limits. We are still very far away from the end vision of AGI. Companies are quickly realizing the limits of AI technology and we risk industry backlash as enterprises push back on what is being overpromised and under delivered, just as we experienced in the first AI Winter. The big concern is that interest will cool too much and AI investment and research will again slow, leading to another AI Winter. However, perhaps the issue never has been with the term Artificial Intelligence. AI has always been a lofty goal upon which to set the sights of academic research and interest, much like building settlements on Mars or interstellar travel. However, just as the Space Race has resulted in technologies with broad adoption today, so too will the AI Quest result in cognitive technologies with broad adoption, even if we never achieve the goals of AGI.

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Why Cognitive Technology May Be A Better Term Than Artificial Intelligence - Forbes

Artificial intelligence jobs on the rise, along with everything else AI – ZDNet

AI jobs are on the upswing, as are the capabilities of AI systems. The speed of deployments has also increased exponentially. It's now possible to train an image-processing algorithm in about a minute -- something that took hours just a couple of years ago.

These are among the key metrics of AI tracked in the latest release of theAI Index, an annual data update from Stanford University'sHuman-Centered Artificial Intelligence Institutepublished in partnership with McKinsey Global Institute. The index tracks AI growth across a range of metrics, from papers published to patents granted to employment numbers.

Here are some key measures extracted from the 290-page index:

AI conference attendance: One important metric is conference attendance, for starters. That's way up. Attendance at AI conferences continues to increase significantly. In 2019, the largest, NeurIPS, expects 13,500 attendees, up 41% over 2018 and over 800% relative to 2012. Even conferences such as AAAI and CVPR are seeing annual attendance growth around 30%.

AI jobs: Another key metric is the amount of AI-related jobs opening up. This is also on the upswing, the index shows. Looking at Indeed postings between 2015 and October 2019, the share of AI jobs in the US increased five-fold since 2010, with the fraction of total jobs rising from 0.26% of total jobs posted to 1.32% in October 2019. While this is still a small fraction of total jobs, it's worth mentioning that these are only technology-related positions working directly in AI development, and there are likely an increasingly large share of jobs being enhanced or re-ordered by AI.

Among AI technology positions, the leading category being job postings mentioning "machine learning" (58% of AI jobs), followed by artificial intelligence (24%), deep learning (9%), and natural language processing (8%). Deep learning is the fastest growing job category, growing 12-fold between 2015 and 2018. Artificial Intelligence grew by five-fold, machine learning grew by five-fold, machine learning by four-fold, and natural language processing two-fold.

Compute capacity: Moore's Law has gone into hyperdrive, the AI Index shows, with substantial progress in ramping up the computing capacity required to run AI, the index shows. Prior to 2012, AI results closely tracked Moore's Law, with compute doubling every two years. Post-2012, compute has been doubling every 3.4 months -- a mind-boggling net increase of 300,000x. By contrast, the typical two-year doubling period that characterized Moore's law previously would only yield a 7x increase, the index's authors point out.

Training time: The among of time it takes to train AI algorithms has accelerated dramatically -- it now can happen in almost 1/180th of the time it took just two years ago to train a large image classification system on a cloud infrastructure. Two years ago, it took three hours to train such a system, but by July 2019, that time shrunk to 88 seconds.

Commercial machine translation: One indicator of where AI hits the ground running is machine translation -- for example, English to Chinese. The number of commercially available systems with pre-trained models and public APIs has grown rapidly, the index notes, from eight in 2017 to over 24 in 2019. Increasingly, machine-translation systems provide a full range of customization options: pre-trained generic models, automatic domain adaptation to build models and better engines with their own data, and custom terminology support."

Computer vision: Another benchmark is accuracy of image recognition. The index tracked reporting through ImageNet, a public dataset of more than 14 million images created to address the issue of scarcity of training data in the field of computer vision. In the latest reporting, the accuracy of image recognition by systems has reached about 85%, up from about 62% in 2013.

Natural language processing: AI systems keep getting smarter, to the point they are surpassing low-level human responsiveness through natural language processing. As a result, there are also stronger standards for benchmarking AI implementations. GLUE, the General Language Understanding Evaluation benchmark, was only released in May 2018, intended to measure AI performance for text-processing capabilities. The threshold for submitted systems crossing non-expert human performance was crossed in June, 2019, the index notes. In fact, the performance of AI systems has been so dramatic that industry leaders had to release a higher-level benchmark, SuperGLUE, "so they could test performance after some systems surpassed human performance on GLUE."

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Artificial intelligence jobs on the rise, along with everything else AI - ZDNet

Chanukah and the Battle of Artificial Intelligence – The Ultimate Victory of the Human Being – Chabad.org

Chanukah is generally presented as a commemoration of a landmark victory for religious freedom and human liberty in ancient times. Big mistake. Chanukahs greatest triumph is still to comethe victory of the human soul over artificial intelligence.

Jewish holidays are far more than memories of things that happened in the distant pastthey are live events taking place right now, in the ever-present. As we recite on Chanukahs parallel celebration, Purim, These days will be remembered and done in every generation. The Arizal explains: When they are remembered, they reenact themselves.

And indeed, the battle of the Maccabees is an ongoing battle, oneThe battle of the Maccabees is an ongoing battle embedded deep within the fabric of our society. embedded deep within the fabric of our society, one that requires constant vigilance lest it sweep away the foundations of human liberty. It is the struggle between the limitations of the mind and the infinite expanse that lies beyond the minds restrictive boxes, between perception and truth, between the apparent and the transcendental, between reason and revelation, between the mundane and the divine.

Today, as AI development rapidly accelerates, we may be participants in yet a deeper formalization of society, the struggle between man and machine.

Let me explain what I mean by the formalization of society. Formalization is something the manager within us embraces, and something the incendiary, creative spark within that manager defies. Its why many bright kids dont do well in school, why our most brilliant, original minds are often pushed aside for promotions while the survivors who follow the book climb high, why ingenuity is lost in big corporations, and why so many of us are debilitated by migraines. Its also a force that bars anything transcendental or divine from public dialogue.

Formalization is the strangulation of life by reduction to standard formulas. ScientistsFormalization is the strangulation of life by reduction to standard formulas. reduce all change to calculus, sociologists reduce human behavior to statistics, AI technologists reduce intelligence to algorithms. Thats all very usefulbut it is no longer reality. Reality is not reducible, because the only true model of reality is reality itself. And what else is reality but the divine, mysterious and wondrous space in which humans live?

Formalization denies that truth. To reduce is useful, to formalize is to kill.

Formalization happens in a mechanized society because automation demands that we state explicitly the rules by which we work and then set them in silicon. It reduces thought to executable algorithms; behaviors to procedures, ideas to formulas. Thats fantastic because it potentially liberates us warm, living human beings from repetitive tasks that can be performed by cold, lifeless mechanisms so we may spend more time on those activities that no algorithm or formula could perform.

Potentially. The default, however, without deliberate intervention, is the edifice complex.

The edifice complex is what takes place when we create a device, institution or any other formal structurean edificeto more efficiently execute some mandate. That edifice then develops a mandate of its ownthe mandate to preserve itself by the most expedient means. And then, just as in the complex it sounds like, The Edifice Inc., with its new mandate, turns around and suffocates to deathThe Edifice Inc., with its new mandate, turns around and suffocates to death the original mandate for which it was created. the original mandate for which it was created.

Think of public education. Think of many of our religious institutions and much of our government policy. But also think of the general direction that industrialization and mechanization has led us since the Industrial Revolution took off 200 years ago.

Its an ironic formula. Ever since Adam named the animals and harnessed fire, humans have built tools and machines to empower themselves, to increase their dominion over their environment. And, yes, in many ways we have managed to increase the quality of our lives. But in many other ways, we have enslaved ourselves to our own servantsto the formalities of those machines, factories, assembly lines, cost projections, policies, etc. We have coerced ourselves into ignoring the natural rhythms of human life, the natural bonds and covenants of human community, the spectrum of variation across human character and our natural tolerance to that wide deviance, all to conform to those tight formalities our own machinery demands in the name of efficacy.

In his personal notes in the summer of 1944, having barely escaped from occupied France, the Rebbe, Rabbi Menachem M. Schneerson of righteous memory, described a world torn by a war between two ideologiesbetween those for whom the individual was nothing more than a cog in the machinery of the state, and those who understood that there can be no benefit to the state by trampling the rights of any individual. The second ideologythat held by the western Alliesis, the Rebbe noted, a Torah one: If the enemy says, give us one of you, or we will kill you all! declared the sages of the Talmud, Not one soul shall be deliberately surrendered to its death.

Basically, the life of the individual is equal to the whole. Go make an algorithm from that. The math doesntThe life of the individual is equal to the whole. Go make an algorithm from that. The math doesnt work. work. Try to generalize it. You cant. It will generate what logicians call a deductive explosion. Yet it summarizes a truth essential to the sustainability of human life on this planetas that world war demonstrated with nightmarish poignance.

That war continued into the Cold War. It presses on today with the rising economic dominance of the Communist Party of China.

In the world of consumer technology, total dominance of The Big Machine was averted when a small group of individuals pressed forward against the tide by advancing the human-centered digital technology we now take for granted. But yet another round is coming, and it rides on the seductive belief that AI can do its best job by adding yet another layer of formalization to all societys tasks.

Dont believe that for a minute. The telos of technology is to enhance human life, not to restrict it; to provide human beings with tools and devices, not to render them as such.

Technologys ultimate purpose will come in a time of which Maimonides writes, when the occupation of the entire world will be only to know the divine. AI can certainly assist us in attaining that era and living itas long as we remain its masters and do not surrender our dignity as human beings. And that is the next great battle of humanity.

To win this battle, we need once again only a small army, but an army armed with more than vision. They must be people with faith. Faith in the divine spark within the human being. For that is what underpins the security of the modern world.

Pundits will tell you that our modern world is secular. Dont believe them. They will tell you that religion is not taught in American public schools. Its a lie. Western society is sustained on the basis of a foundational, religious belief: that all human beings are equal. Thats a statement withAll human beings are equal. Thats a statement of faith. no empirical or rational support. Because it is neither. It is a statement of faith. Subliminally, it means: The value of a single human life cannot be measured.

In other words, every human life is divine.

No, we dont say those words; there is no class in school discussing our divine image. Yet it is a tacit, unspoken belief. Western society is a church without walls, a religion whose dogmas are never spoken, yet guarded jealously, mostly by those who understand them the least. Pull out that belief from between the bricks and the entire edifice collapses to the ground.

It is also a ubiquitous theme in Jewish practice. As Ive written elsewhere, leading a Jewish way of life in the modern era is an outright rebellion against the materialist reductionism of a formalized society.

We liberate ourselves from interaction with our machines once a week, on Shabbat, and rise to an entirely human world of thought, prayer, meditation, learning, songs, and good company. We insist on making every instance of food consumption into a spiritual, even mystical event, by eating kosherWe liberate ourselves from interaction with our machines once a week. and saying blessings before and after. We celebrate and empower the individual through our insistence that every Jew must study and enter the discussion of the hows and whys of Jewish practice. And on Chanukah, we insist that every Jew must create light and increase that light each day; that none of us can rely on any grand institution to do so in our proxy.

Because each of us is an entire world, as our sages state in the Mishnah, Every person must say, On my account, the world was created.

This is what the battle of Chanukah is telling us. The flame of the menorah, that is the human soul The human soul is a candle of Gd. The war-machine of Antiochus upon elephants with heavy armorthat is the rule of formalization and expedience coming to suffocate the flame. The Maccabee rebels are a small group of visionaries, those who believe there is more to heaven and earth than all science and technology can contain, more to the human soul than any algorithm can grind out, more to life than efficacy.

How starkly poignant it is indeed that practicing, religious Jews were by far the most recalcitrant group in the Hellenist world of the Greeks and Romans.

Artificial intelligence can be a powerful tool for good, but only when wielded by those who embrace a reality beyond reason. And it is that transcendence that Torah preserves within us. Perhaps all of Torah and its mitzvahs were given for this, the final battle of humankind.

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Chanukah and the Battle of Artificial Intelligence - The Ultimate Victory of the Human Being - Chabad.org

Military Applications of Artificial Intelligence – Ethics Project Now Funded – Peace Research Institute Oslo (PRIO)

How canthe moral integrity and agency of military personnel be preserved and enhanced when artificial intelligence is implemented in practices of war?

Congratulations to Greg Reichberg on funding from the SAMKUL callof the Research Council of Norway for a four-yearproject with th title: Warring with Machines:Military Applications of Artificial Intelligence and the Relevance of Virtue Ethics. The PRIO team also consists of Henrik Syse and Mareile Kaufmann, and in addition a full-time PhD position.

Artificial intelligence plays an ever-expanding role in the context of war. This project aims to determine how the moral integrity and agency of military personnel may be preserved and enhanced when artificial intelligence is implemented in practices of war.

The project will pursue this goal from the perspective of virtue ethics, philosophy of action and mind, and applied military ethics, in close dialogue with institutional stakeholders as well as technologists and representatives from cognitive neuroscience. Its three main research questions are as follows:

The project is built up around a unique institutional collaboration between leading national and international research institutions within the fields of military ethics, the philosophy of mind, and artificial intelligence research, as well as key military training institutions and technology manufacturers.

In addition to the PRIO team, the project will have the following externalmembers:

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Military Applications of Artificial Intelligence - Ethics Project Now Funded - Peace Research Institute Oslo (PRIO)

Ume University: Master all areas of Artificial Intelligence – Study International News

Artificial intelligence (AI) is transforming work and life as we know it, already boosting workplace efficiency and leading to noticeable improvements to the quality of for instance healthcare, lowering costs while giving clinicians time to work with their patients more closely, and with more insight. This was made clear in arecent MIT Technology Review Insights surveyproduced in partnership with GE Healthcare, where more than 82 percent of healthcare business leaders said their AI deployments were showing positive results across operational and administrative activities,.

When analysing the impact AI would have on the global education sector, founders of theInstitute for Ethical AI in Education (IEAIED) said there wasno need to fear the technology. Rather than replace the human element in education, AI would augment teaching and learning, they said.

There are highly beneficial applications of machine learning inside the area of education. Artificial Intelligence may enable personalised learning, especially important for students with specialized needs and challenges. Awell-designed AI can be used to identify learners particular needs so that everyone especially the most vulnerable can receive targeted support.

With global education and healthcare being just two of many sectors that AI has advanced so far, and withhundreds more AI technology developmentson the horizon, such as autonomous vehicles, manufacturing and financial services to add to the list, the need for expertise in the field appears limitless!

Firmly supporting this need and accepting this challenge is theFaculty of Science and TechnologyatUme University, Sweden.

Currently open forautumn 2020 intake, their newMasters in Artificial Intelligenceis a postgraduate programme that enables you to develop broad and core competence in AI and equips you with the digital tools necessary for future career success.

Youll also experience a combination of lectures, seminars, group work, and tutorials in conjunction with different types of assignments and laboratory work to advance your AI education in a multidisciplinary manner.

It is of critical importance to study in a more multidisciplinary manner, where humanities and social sciences are combined with science and technology. AI can no longer be seen as a purely technical or computer science discipline. It is per definition interdisciplinary, says Ume Department of Computing Science Professor, Virginia Dignum.

One of the first professors recruited to Sweden as part of the Wallenberg AI, Autonomous Systems and Software Program (WASP) initiative and actively involved in several international initiatives on policy and strategy guidelines for AI research and applications, such as theEuropean Commission High Level Expert Group on Artificial Intelligence (AI HLEG), Dignum is one of the AI experts at Ume who are driving research and graduate success forward.

My position at Ume University makes it possible for me to look at societal, ethical and cultural consequences of AI. I will for instance be studying methods and tools to ensure that AI systems are formed not to violate human values and ethical principles, says Dignum, who also leads the research group Social and Ethical Artificial Intelligence at the Faculty.

Another integral member at the Faculty is Senior Lecturer Helena Lindgren.

Understanding the urgency of AI integration, Lindgren believes that the university needs to be driven to produce research that develops, educates and enhances the capabilities of AI in society, both in terms of system development and implementation.

One of the objectives at Ume is to raise societys AI competence, such as through continuing education and professional development of currently employed persons. Its very important for Sweden as a nation, as well as its companies and organisations, to be able to take the next step in digital development, says Lindgren.

Lindgren and Dignum reflect the high caliber of the 30-strong researchers at Ume University that are engaged in the development of AI in different areas.

To study here is to be under their expert guidance as you undertake courses that relate to human-AI interaction and complete student projects conducted in collaboration with an organisation addressing societal challenges.

In these projects, students are expected to collaborate in interdisciplinary teams and with representatives from industry and public organisations, adding a practical twist to the 2020 course.

In this English-taught Masters, you are also expected to take full responsibility for organising your tasks so that deadlines are met and collaborative work within student projects are manageable within office hours.

Despite being a new course, AI is not a new focus for Ume.

In the 1970s, Ume Professor Lars-Erik Janlert focused on Knowledge Representation, and in the early 1980s he formed the Swedish AI Society together with other Swedish researchers.

Since then, Ume has expanded its outreach into a variety of research and education activities across different departments and faculties and is now one of seven universities that are part of the governmental initiative AI Competence for Sweden.

Ume University

Continuously building its research efforts through its strong interdisciplinary traditions and close collaborations with society, AI@UmU initiatives have also established an expanding network of researchers, teachers, students and professionals who want to learn, discuss and collaborate around AI-related issues via seminars, panel discussions and courses.

Always welcome to discuss the latest tech revelations and AI advancements with their professors and visiting professionals, Ume students are motivated to unearth AI research angles of their own.

From day one of the new Masters programme, theyll deepen their insight into this exciting field and take their knowledge of AIs theoretical foundations, intelligent robotics, machine learning and data science further.

So, if youre ready to master all areas of AI and want to start your postgraduate study venture in Sweden, click here to find out about the application and eligibility process.

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Ume University: Master all areas of Artificial Intelligence - Study International News

Innovations in Artificial Intelligence, Cloud, Blockchain, and Analytics, 2019: Advances in AI, Blockchain, and Business Intelligence -…

DUBLIN--(BUSINESS WIRE)--The "Innovations in Artificial Intelligence, Cloud, Blockchain, and Analytics" report has been added to ResearchAndMarkets.com's offering.

This edition of IT, Computing and Communications (ITCC) TechVision Opportunity Engine (TOE) provides a snapshot of the emerging ICT led innovations in artificial intelligence, machine learning, cloud, and analytics. This issue focuses on the application of information and communication technologies in alleviating the challenges faced across industry sectors in areas such as banking, oil & gas, healthcare, life sciences, and industrial sectors.

ITCC TOE's mission is to investigate emerging wireless communication and computing technology areas including 3G, 4G, Wi-Fi, Bluetooth, Big Data, cloud computing, augmented reality, virtual reality, artificial intelligence, virtualization and the Internet of Things and their new applications; unearth new products and service offerings; highlight trends in the wireless networking, data management and computing spaces; provide updates on technology funding; evaluate intellectual property; follow technology transfer and solution deployment/integration; track development of standards and software; and report on legislative and policy issues and many more.

Innovations in ICT have deeply permeated various applications and markets. These innovations have profound impact on a range of business functions for computing, communications, business intelligence, data processing, information security, workflow automation, quality of service (QoS) measurements, simulations, customer relationship management, knowledge management functions and many more.

Key Topics Covered:

Companies Mentioned

For more information about this report visit https://www.researchandmarkets.com/r/x8spy9

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Innovations in Artificial Intelligence, Cloud, Blockchain, and Analytics, 2019: Advances in AI, Blockchain, and Business Intelligence -...