Archive for the ‘Artificial Intelligence’ Category

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

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

How is Artificial Intelligence (AI) Changing the Future of Architecture? – AiThority

Artificial Intelligence (AI) has always been a topic of discussion- is it good enough for us? Getting more and more into this high technology world will give us a better future or not? According to recent research, almost everyone has a different requirement for automation. And most of the work of humans is done by the latest high intelligence computers. You all must be familiar with the fact of how Artificial Intelligence is changing industries, like Medicine, Automobiles, and Manufacturing. Well, what about Architecture?

The main issue is about the fact that these high tech robots will actually replace the creator? Although these high tech computers are not good enough at some ideas and you have to rely on Human Intelligence for that. However, these can be used to save a lot of time by doing some time-consuming tasks, and we can utilize that time in creating some other designs.

Artificial Intelligence is a high technology mechanical system that can perform any task but needs a few human efforts like visual interpretation or design-making etc. AI works and gives the best results possible by analyzing tons of data, and thats how it can excel in architecture.

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While creating new designs, architects usually go through past designs and the data prepared throughout the making of the building. Instead of investing a lot of time and energy to create something new, it is alleged that a computer will be able to analyze the data in a short time period and will give recommendations accordingly. With this, an architect will be able to do testing and research simultaneously and sometimes even without pen and paper. It seems like it will lead to the organizations or the clients to revert to computers for masterplans and construction.

However, the value of architects and human efforts of analyzing a problem and finding the perfect solutions will always remain unchallenged.

Read More: How Automating Procurement is Like Self-Driving Cars

Parametric architecture is a hidden weapon that allows an architect to change specific parameters to create various types of output designs and create such structures that would not have been imagined earlier. It is like an architects programming language.

It allows an architect to consider a building and reframe it to fit into some other requirements. A process like this allows Artificial Intelligence to reduce the effort of an architect so that the architect can freely think about different ideas and create something new.

Constructing a building is not a one-day task as it needs a lot of pre-planning. However, this pre-planning is not enough sometimes, and you need a little bit of more effort to get an architects opinion to life. Artificial Intelligence will make an architects work significantly easier by analyzing the whole data and creating models that can save a lot of time and energy of the architect.

All in all, AI can be called an estimation tool for various aspects while constructing a building. However, when it comes to the construction part, AI can help so that human efforts become negligible.

The countless hours of research at the starting of any new project is where AI steps in and makes it easy for the architect by analyzing the aggregate data in millisecond and recommending some models so that the architect can think about the conceptual design without even using the pen or paper.

Just like while building a home for a family, if you have the whole information about the requirements of the family, you can simply pull all zoning data using AI and generate design variations in a short time period.

This era of modernization demands everything to be smartly designed. Just like smart cities, todays high technology society demands smart homes. However, now architects do not have to bother about how to use AI to create the designs of home only, but they should worry about making the users experience worth paying.

Change is something that should never change. The way your city looks today will be very different in the coming time. The most challenging task for an architect is city planning that needs a lot of precision planning. However, the primary task is to analyze all the possible aspects, and understand how a city will flow, how the population is going to be in the coming years.

All these factors are indicating one thing only, i.e., the future architects will give fewer efforts in the business of drawing and more into satisfying all the requirements of the user with the help of Artificial Intelligence.

Read More: How AI and Automation Are Joining Forces to Transform ITSM

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How is Artificial Intelligence (AI) Changing the Future of Architecture? - AiThority

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

Robotics and Artificial Intelligence in solar energy – ELE Times

A one of a kind opportunity exists to apply AI to a particular part of the clean energy value chain: materials. Materials fill in as the structure blocks of clean energy, for example, the solar cells that make up the photovoltaic panels found on rooftops. Enhancing the materials used to manufacture parts of clean energy is significant on the grounds that current materials are frequently lethal, non-earth rich, and require carbon-concentrated processing.

Without getting excessively technical, basically, the entire reason of AI is a machine emulating the human brain. The machine can learn and adjust to various situations, and as time passes, the machine gets smarter and responds diversely to accomplish better outcomes.

Utilizing AI along these lines can give producers an edge. Manufacturers will in general put resources into upgrading downstream production capacities, which has prompted a few AI applications in sensor innovations and process optimisation. Utilizing AI for upstream design purposes, nonetheless, is an undiscovered business opportunity that could decrease the time it takes to find new materials, opening up capital for deployment and commercialisation strategies.

Robots have already made a difference. They are currently generally used to blend many somewhat various recipes for a material, store them on single wafers or different platforms, and afterward process and test them all the while. In any case, basically trudging through recipe after the recipe is a moderate course to a breakthrough. High throughput is an approach to do heaps of experiments, however, not a great deal of development.

Governments are making the first move on AI-empowered clean energy materials disclosure, flagging this is a region of key national and worldwide interest. Public risk capital drives down expenses for industry, empowering the more extensive adoption of AI in cutting edge producing. Making clean energy materials less expensive, cleaner, and increasingly solid isnt useful for the earth, yet in addition useful for business.

This situation shows an opportunity for the clean energy manufacturing sector. Applying AI to the advancement of new materials can decrease embedded emissions, toxicity and costs while saving researchers valuable time in the lab. Experiments done by trial-and-error are frequently rehashed a lot of times before a breakthrough happens. Rather, AI could automate complex logical tasks and empower analysts to concentrate on tasks that require more creativity and ingenuity.

To speed the procedure, numerous teams have included computer modeling to foresee the equation of likely pearls. Were seeing a torrential slide of exciting materials originating from the forecast, says Kristin Persson of Lawrence Berkeley National Laboratory (LBNL) in California, who runs a large-scale prediction enterprise known as the Materials Project. However, those frameworks still commonly depend on graduate students or experienced researchers to assess the consequences of trials and decide how to continue. However, Individuals still need to do things like rest and eat.

Governments are making the first move on AI-empowered clean energy materials disclosure, flagging this is a region of key national and worldwide interest. Public risk capital drives down expenses for industry, empowering the more extensive adoption of AI in cutting edge producing. Making clean energy materials less expensive, cleaner, and increasingly solid isnt useful for the earth, yet in addition useful for business.

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Robotics and Artificial Intelligence in solar energy - ELE Times