Category Archives: Artificial Intelligence

SAN FRANCISCO, Feb. 5, 2020 /PRNewswire/ -- The global artificial intelligence marketsize is expected to reach USD 390.9 billion by 2025, according to a new report by Grand View Research, Inc. The market is anticipated to expand at a CAGR of 46.2% from 2019 to 2025. Artificial Intelligence (AI) is considered to be a revolutionary technological development and its integration across a host of applications is one of the key factors driving this market. Advances in image and voice recognition are driving the growth of the regional market. Improved image recognition technology is critical in enhanced drones, self-driving cars, and robotics.

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Read 100 page research report with ToC on "Artificial Intelligence Market Size, Share & Trends Analysis Report By Solution, By Technology (Deep Learning, Machine Learning), By End Use (Advertising & Media, Law, Healthcare), And Segment Forecasts, 2019 - 2025" at: https://www.grandviewresearch.com/industry-analysis/artificial-intelligence-ai-market

The two major factors fueling market growth are emerging Artificial Intelligence technologies and growth in big data espousal. Rising prominence of Artificial Intelligence is enabling new players to venture into the market by offering niche application-specific solutions. Furthermore, companies are engaging in industry consolidations in a bid to gain competitive advantages. For instance, in January 2017, Microsoft Corporation acquired Maluuba in order to advance in the deep learning and AI landscape. Existing solution providers are innovating their product portfolio to include both hardware and software solutions.

North America held the dominant share in the global AI market in 2018 thanks to the availability of high government funding, presence of leading players, and strong technical base. Asia Pacific, however, is anticipated to overtake North America to emerge as the leading regional market by 2025, registering the highest CAGR. This can be attributed to rapid improvements in information storage capacity, high computing power, and parallel processing, all of which have contributed to the swift uptake of Artificial Intelligence technology in end-use industries such as automotive and healthcare.

AI has the potential to reduce the burden on clinicians and provide an efficient tool to workforces for accomplishing their tasks in a better way. For instance, AI voice-enabled symptom checkers can better access a situation and assist patients to the emergency department when immediate treatment is required. Artificial Intelligence is expected to resolve around 20% of unmet healthcare demands.

Grand View Research has segmented the global Artificial Intelligence market based on solution, technology, end use, and region:

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About Grand View Research

Grand View Research, U.S.-based market research and consulting company, provides syndicated as well as customized research reports and consulting services. Registered in California and headquartered in San Francisco, the company comprises over 425 analysts and consultants, adding more than 1200 market research reports to its vast database each year. These reports offer in-depth analysis on 46 industries across 25 major countries worldwide. With the help of an interactive market intelligence platform, Grand View Research helps Fortune 500 companies and renowned academic institutes understand the global and regional business environment and gauge the opportunities that lie ahead.

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Artificial Intelligence Market Size Worth $390.9 Billion by 2025: Grand View Research, Inc. - Yahoo Finance

For Immediate Release: February 07, 2020

Today, the U.S. Food and Drug Administration authorized marketing of software to assist medical professionals in the acquisition of cardiac ultrasound, or echocardiography, images. The software, called Caption Guidance, is an accessory to compatible diagnostic ultrasound systems and uses artificial intelligence to help the user capture images of a patients heart that are of acceptable diagnostic quality.

The Caption Guidance software is indicated for use in ultrasound examination of the heart, known as two-dimensional transthoracic echocardiography (2D-TTE), for adult patients, specifically in the acquisition of standard views of the heart from different angles. These views are typically used in the diagnosis of various cardiac conditions.

Echocardiograms are one of the most widely-used diagnostic tools in the diagnosis and treatment of heart disease, said Robert Ochs, Ph.D., deputy director of the Office of In Vitro Diagnostics and Radiological Health in the FDAs Center for Devices and Radiological Health. Todays marketing authorization enables medical professionals who may not be experts in ultrasonography, such as a registered nurse in a family care clinic or others, to use this tool. This is especially important because it demonstrates the potential for artificial intelligence and machine learning technologies to increase access to safe and effective cardiac diagnostics that can be life-saving for patients.

According to the Centers for Disease Control and Prevention, heart disease is the leading cause of death in the United States, killing one out of every four people, or approximately 647,000 Americans each year. The term heart disease refers to several types of heart conditions. The most common type is coronary artery disease, which can cause heart attack. Other kinds of heart disease may involve the valves in the heart, or the heart may not pump well and cause heart failure.

Cardiac diagnostic tests are necessary to identify heart conditions. Among them are electrocardiograms (more widely known as an EKG or ECG), Holter monitors and cardiac ultrasound examinations. The software authorized today is the first software authorized to guide users through cardiac ultrasound image acquisition. The Caption Guidance software was developed using machine learning to train the software to differentiate between acceptable and unacceptable image quality. This knowledge formed the basis of an interactive AI user interface that provides prescriptive guidance to users on how to maneuver the ultrasound probe to acquire standard echocardiographic images and video clips of diagnostic quality. The AI interface provides real-time feedback on potential image quality, can auto-capture video clips, and automatically saves the best video clip acquired from a particular view. Importantly, the cardiologist still reviews the images for a final assessment of the images and videos for patient evaluation.

The Caption Guidance software currently can be used with a specific FDA-cleared diagnostic ultrasound system produced by Teratech Corporation, with the potential to be used with other ultrasound imaging systems that have technical specifications consistent with the range of ultrasound systems used as part of the development and testing.

In its review of this device application, the FDA evaluated data from two independent studies. In one study, 50 trained sonographers scanned patients, with and without the assistance of the Caption Guidance software. The sonographers were able to capture comparable diagnostic quality images in both settings. The other study involved training eight registered nurses who are not experts in sonography to use the Caption Guidance software and asking them to capture standard echocardiography images, followed by five cardiologists assessing the quality of the images acquired. The results showed that the Caption Guidance software enabled the registered nurses to acquire echocardiography images and videos of diagnostic quality.

The FDA is dedicated to ensuring medical device regulation keeps pace with technological advancements, such as todays marketing authorization. This February, the FDA is hosting a public workshop titled Evolving Role of Artificial Intelligence (AI) in Radiological Imaging and seeks to discuss emerging applications of AI in radiological imaging, including AI devices intended to automate the diagnostic radiology workflow, as well as guided image acquisition. Discussions will also focus on best practices for the validation of AI-automated radiological imaging software and image acquisition devices, which is critical to assess safety and effectiveness.

The FDA reviewed the device through the De Novo premarket review pathway, a regulatory pathway for low- to moderate-risk devices of a new type. Along with this authorization, the FDA is establishing special controls for devices of this type, including requirements related to labeling and performance testing. When met, the special controls, along with general controls, provide reasonable assurance of safety and effectiveness for devices of this type. This action creates a new regulatory classification, which means that subsequent devices of the same type with the same intended use may go through FDAs 510(k) premarket process, whereby devices can obtain marketing authorization by demonstrating substantial equivalence to a predicate device.

The FDA granted marketing authorization of the Caption Guidance software to Caption Health Inc.

The FDA, an agency within the U.S. Department of Health and Human Services, protects the public health by assuring the safety, effectiveness, and security of human and veterinary drugs, vaccines and other biological products for human use, and medical devices. The agency also is responsible for the safety and security of our nations food supply, cosmetics, dietary supplements, products that give off electronic radiation, and for regulating tobacco products.

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FDA Authorizes Marketing of First Cardiac Ultrasound Software That Uses Artificial Intelligence to Guide User - FDA.gov

The "Artificial Intelligence (AI) in the Global Freight Transportation Industry, Forecast to 2025" report has been added to ResearchAndMarkets.com's offering.

This study analyses the key trends and applications of artificial intelligence in the freight transportation industry by mode of transport i.e. road, rail, air, and ocean freight transportation. This research also analyses the disruptive impact of artificial intelligence on freight transportation business operations and discusses its adoption prospects until 2025.

Market Insights

With increased trade flow, the fleet population in freight transportation has become denser, and expectations of customers have evolved beyond recognition, resulting in complex transport operations, requiring operational flexibility from freight operators. Human errors in operations, underutilized assets, low workforce productivity, inefficient operational planning, inability to match supply with demand, and trimmed profit margins are key prevailing concerns with freight operators.

The emergence of digital technologies and the rapid technological advancements in digitization have transformed the business and operational landscape of the global freight transportation industry. It is essential for freight operators to embrace such operational complexity and evolve by adopting technologies to turn complexity into an advantage.

Today, the world is connected more than ever, and the growth of data generation has been exponential with smart devices and process automation. Data-driven insights help freight operators move forward and gain a competitive advantage over their peers. Artificial intelligence enables freight operators to harness data more effectively for actionable insights.

Artificial intelligence-powered systems in conjunction with other digital technologies such as internet of things and big data analytics utilize data to its full potential to anticipate events for freight operators, aiding them to avoid risks and create innovative solutions. Machine learning algorithms based on neural networks powered by artificial intelligence would unlock multiple benefits for companies operating in the freight transportation industry.

AI brings changes to the supply chain with autonomous vehicles, helping fleet operators reduce operating cost with and fuel consumption and plan optimized routes for service. The freight operators that are enhancing their capabilities with artificial intelligence are reaping its benefits by increasing efficiency with predictive intelligence. Artificial intelligence also enriches the relationship between the shipper and carrier with personalized service offerings.

Advanced sensor fusion with artificial intelligence supports the integration of smart infrastructure and operating assets and the freight operators in the development of connected freight ecosystem, aiding autonomous fleet management. The transformation of the logistics industry due to artificial intelligence is imperative in the near future; however, the readiness and openness of freight operators for an AI-based data-driven environment will determine how well this industry copes with challenges.

Key Topics Covered:

1. Executive Summary

2. Research Scope and Methodology

3. AI in Logistics Industry

4. AI in Freight Forwarding

5. AI in Freight Transportation

6. Stature of AI Adoption in Freight Transportation

7. Growth Opportunities and Companies to Action

8. The Last Word

Companies Mentioned

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View source version on businesswire.com: https://www.businesswire.com/news/home/20200207005450/en/

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ResearchAndMarkets.comLaura Wood, Senior Press Managerpress@researchandmarkets.com For E.S.T Office Hours Call 1-917-300-0470For U.S./CAN Toll Free Call 1-800-526-8630For GMT Office Hours Call +353-1-416-8900

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Global Forecast on Artificial Intelligence (AI) in the Freight Transportation Industry (2020 to 2025) - Disruptive Impact of AI on Freight...

We might still be decades away from the superhuman artificial intelligence (AI), like sentient HAL 9000 from 2001: A Space Odyssey, but our fear of robots having a mind of their own and acting at their own (free) will and using it against humankind is nonetheless present. Even some of the greatest minds of our time, such as Elon Musk and Stephen Hawking have been talking about this possibility.

On a more down-to-earth and practical level, artificial intelligence has already sneaked into our lives. Weve grown so accustomed to some of the best AI apps,such as Cortana, Alexa or Siri, that we already think of them as our trusted companions that help us run our everyday tasks easily and smoothly.

However, while a catastrophic sci-fi movie scenario is not a thing we should be worried about (at least not at the moment) there are some risks related to AI implementation which are far more tangible and possible.

Read on to find out more about some real-life benefits and risks of AI implementation.

By now, all of the industries have opened their doors to the various advancements AI brings. Here are some of the most prominent usages were witnessing and will be seeing more of in the years to come, in the digital marketing, healthcare, and finance industry.

If youve recently used a chat to reach customer service, chances are high youve been talking to a chatbot, maybe even without realizing this fact. It may come as a surprise that 40% of customers are fine with both options, as long as they get their issues solved.

Chatbots embody many benefits AI brings to businesses, and are a great example of how it may improve a sensitive and time-consuming matter such as customer service.

Some of the crucial points where you can see the advantages of AI-powered chatbots are:

Besides chatbots, AI can benefit digital marketing in many different ways, as it can be used to automate many different tasks, such as email and paid ads campaigns. It can also help marketers create more precise buyer personas, predict customers behavior and give sales forecasts, help with content creation, etc. These benefits to the e-commerce industry can hardly be measured, as businesses can now always be there for their online customers, assisting them in making their purchasing decisions and helping them navigate their customer journey.

Another noticeable way AI benefits our lives is through its usage in healthcare.

Weve recently witnessed a win of trained AI over human experts, as AI outperformed six radiologists in reading mammograms and recognizing breast cancer. Images can now be analyzed in a few seconds by the computer algorithm, so the use of AI can significantly improve the speed of diagnosis.

Except in radiology, AI is widely used in digital consultations, on platforms such as Buoy or Isabel symptom checkers, offering remote medical assistance, and suggesting how to see a professional based on their location.

The advantages of AI have been recognized early by the finance and banking sectors, and the technology is now implemented in the ways beneficial for both parties.

One of the best examples of how beneficial AI in this industry can be, is Erica, a virtual employee of the National Bank of America. Erica has by now served over 7 million customers and managed over 50 million of their requests, helping them with their transactions and budgeting, tracking their spending habits and giving useful advice.

As for the potential actual risks of AI nowadays, the one that seems to bring the most concerns is job loss, which in some industries seem inevitable.

AI-powered employees have quite a few advantages when compared to their human colleagues. As they have no personal and emotional responses theyre never exhausted, bored or distracted, not to mention that they are more productive and efficient. Furthermore, their capacity to make errors is significantly reduced.

Such qualities of AI are the most likely to cause layoffs where a lot of tasks can be automated, such as the trucking, food service and retail industry, leading to millions of unemployed and an even higher income inequality.

Another rising concern has been an invasion of privacy. This has already taken place in China, where AI-powered technologies are used for the purposes of mass surveillance, impacting the so-called social credit system.

The system tracks users behavior everywhere it has access to their social media profiles, their financial reports, health records etc. Data collected this way, including jaywalking and failing to correctly sort personal waste can now negatively influence the credit score while donating blood or volunteering can increase it. Negative credit can, for example, ban you from buying plane tickets, or enrolling your kids in certain schools.Finally, the possibility of using AI capacities for military purposes shouldnt be neglected, as the idea of having this kind of power concentrated in the hands of any of the world leaders, seems like a genuine threat to the world as we know it.

And while we think about all the benefits and the risks artificial intelligence brings, lets not forget one crucial point AI doesnt set its own goals. The power it has is the power we delegate it to achieve the things we are trying to accomplish, meaning that were responsible for both its benefits and its risks.

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Benefits and Risks of Artificial Intelligence - TechSpective

Graham Allison alerts us to artificial intelligence being the epicenter of todays superpower arms race.

Drawing heavily on Kai-Fu Lees basic thesis, Allison draws the battlelines: the United States vs. China, across the domains of human talent, big data, and government commitment.

Allison further points to the absence of controls, or even dialogue, on what AI means for strategic stability. With implied resignation, his article acknowledges the smashing of Pandoras Box, noting many AI advancements occur in the private sector beyond government scrutiny or control.

However, unlike the chilling and destructive promise of nuclear weapons, the threat posed by AI in popular imagination is amorphous, restricted to economic dislocation or sci-fi depictions of robotic apocalypse.

Absent from Allisons call to action is explaining the so what?why does the future hinge on AI dominance? After all, the few examples (mass surveillance, pilot HUDs, autonomous weapons) Allison does provide reference continued enhancements to the status quoincremental change, not paradigm shift.

As Allison notes, President Xi Jinping awoke to the power of AI after AlphaGo defeated the worlds number one Go human player, Lee Sedol. But why? What did Xi see in this computation that persuaded him to make AI the centerpiece of Chinese national endeavor?

The answer: AIs superhuman capacity to think.

To explain, lets begin with what I am not talking about. I do not mean so-called general AIthe broad-spectrum intelligence with self-directed goals acting independent of, or in spite of, preferences of human creators.

Eminent figures such as Elon Musk and Sam Harris warn of the coming of general AI. In particular, the so-called singularity, wherein AI evolves the ability to rewrite its own code. According to Musk and Harris, this will precipitate an exponential explosion in that AIs capability, realizing 10,000 IQ and beyond in a matter of mere hours. At such time, they argue, AI will become to us what we are to ants, with similar levels of regard.

I concur with Sam and Elon that the advent of artificial general superintelligence is highly probable, but this still requires transformative technological breakthroughs the circumstances for which are hard to predict. Accordingly, whether general AI is realized 30 or 200 years from now remains unknown, as is the nature of the intelligence created; such as if it is conscious or instinctual, innocent or a weapon.

When I discuss the AI arms race I mean the continued refinement of existing technology. Artificial intelligence that, while being a true intelligence in the sense of having the ability to self-learn, it has a single programmed goal constrained within a narrow set of rules and parameters (such as a game).

To demonstrate what President Xi saw in AI winning a strategy game, and why the global balance of power hinges on it, we need to talk briefly about games.

Artificial Intelligence and Games

There are two types of strategy games: games of complete information and games of incomplete information. A game of complete information is one in which every player can see all of the parameters and options of every other player.

Tic-Tac-Toe is a game of complete information. An average adult can solve this game with less than thirty minutes of practice. That is, adopt a strategy that no matter what your opponent does, you can correctly counter it to obtain a draw. If your opponent deviates from that same strategy, you can exploit them and win.

Conversely, a basic game of uncertainty is Rock, Scissors, Paper. Upon learning the rules, all players immediately know the optimal strategy. If your opponent throws Rock, you want to throw Paper. If they throw Paper, you want to throw Scissors, and so on.

Unfortunately, you do not know ahead of time what your opponent is going to do. Being aware of this, what is the correct strategy?

The unexploitable strategy is to throw Rock 33 percent of the time, Scissors 33 percent of the time, and Paper 33 percent of the time, each option being chosen randomly to avoid observable patterns or bias.

This unexploitable strategy means that, no matter what approach your opponent adopts, they won't be able to gain an edge against you.

But lets imagine your opponent throws Rock 100 percent of the time. How does your randomized strategy stack up? 33 percent of the time you'll tie (Rock), 33 percent of the time you'll win (Paper), and 33 percent of the time you'll lose (Scissors)the total expected value of your strategy against theirs is 0.

Is this your optimal strategy? No. If your opponent is throwing Rock 100 percent of the time, you should be exploiting your opponent by throwing Paper.

Naturally, if your opponent is paying attention they, in turn, will adjust to start throwing Scissors. You and your opponent then go through a series of exploits and counter-exploits until you both gradually drift toward an unexploitable equilibrium.

With me so far? Good. Let's talk about computing and games.

As stated, nearly any human can solve Tic-Tac-Toe, and computers solved checkers many years ago. However more complex games such as Chess, Go, and No-limit Texas Holdem poker have not been solved.

Despite all being mind-bogglingly complex, of the three chess is simplest. In 1997, reigning world champion Garry Kasparov was soundly beaten by the supercomputer Deep Blue. Today, anyone reading this has access to a chess computer on their phone that could trounce any human player.

Meanwhile, the eastern game of Go eluded programmers. Go has many orders of magnitude more combinations than chess. Until recently, humans beat computers by being far more efficient in selecting moveswe don't spend our time trying to calculate every possible option twenty-five moves deep. Instead, we intuitively narrow our decisionmaking to a few good choices and assess those.

Moreover, unlike traditional computers, people are able to think in non-linear abstraction. Humans can, for example, imagine a future state during the late stages of the game beyond which a computer could possibly calculate. We are not constrained by a forward-looking linear progression. Humans can wonderfully imagine a future endpoint, and work backwards from there to formulate a plan.

Many previously believed that this combination of factorsnear-infinite combinations and the human ability to think abstractlymeant that go would forever remain beyond the reach of the computer.

Then in 2016 something unprecedented happened. The AI system, AlphaGo, defeated the reigning world champion go player Lee Sedol 4-1.

But that was nothing: two years later, a new AI system, AlphaZero, was pitched against AlphaGo.

Unlike its predecessor which contained significant databases of go theory, all AlphaZero knew was the rules, from which it played itself continuously over forty days.

After this period of self-learning, AlphaZero annihilated AlphaGo, not 4-1, but 100-0.

In forty days AlphaZero had superseded 2,500 years of total human accumulated knowledge and even invented a range of strategies that had never been discovered before in history.

Meanwhile, chess computers are now a whole new frontier of competition, with programmers pitting their systems against one another to win digital titles. At the time of writing the world's best chess engine is a program known as Stockfish, able to smash any human Grandmaster easily. In December 2017 Stockfish was pitted against AlphaZero.

Again, AlphaZero only knew the rules. AlphaZero taught itself to play chess over a period of nine hours. The result over 100 games? AlphaZero twenty-eight wins, zero losses, seventy-two draws.

Not only can artificial intelligence crush human players, it also obliterates the best computer programs that humans can design.

Artificial Intelligence and Abstraction

Most chess computers play a purely mathematical strategy in a game yet to be solved. They are raw calculators and look like it too. AlphaZero, at least in style, appears to play every bit like a human. It makes long-term positional plays as if it can visualize the board; spectacular piece sacrifices that no computer could ever possibly pull off, and exploitative exchanges that would make a computer, if it were able, cringe with complexity. In short, AlphaZero is a genuine intelligence. Not self-aware, and constrained by a sandboxed reality, but real.

Despite differences in complexity there is one limitation that chess and go both share they're games of complete information.

Enter No-limit Texas Holdem (hereon, Poker). This is the ultimate game of uncertainty and incomplete information. In poker, you know what your hole cards are, the stack sizes for each player, and the community cards that have so far come out on the board. However, you don't know your opponent's cards, whether they will bet or raise or how much, or what cards are coming out on later streets of betting.

Poker is arguably the most complex game in the world, combining mathematics, strategy, timing, psychology, and luck. Unlike Chess or Go, Pokers possibilities are truly infinite and across multiple players simultaneously. The idea that a computer could beat top Poker professionals seems risible.

Except that it has already happened. In 2017, the AI system Libratus comprehensively beat the best Head's-up (two-player) poker players in the world.

And now, just months ago, another AI system Pluribus achieved the unthinkableit crushed super high stakes poker games against multiple top professionals simultaneously, doing so at a win-rate of five big blinds per hour. For perspective, the difference in skill level between the best English Premier League soccer team and the worst would not be that much.

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Explained: The Artificial Intelligence Race is an Arms Race - The National Interest Online

An artificial intelligence tool has been developed to help predict the structure of the universe and aid research into the mysteries of dark energy and dark matter.

Researchers in Japan used two of the world's fastest astrophysical simulation supercomputers, known as ATERUI and ATERUI II, to create an aptly-named "Dark Emulator" tool, which is able to ingest vast quantities of data and produce analysis of the universe in seconds.

The AI could play a role in studying the nature of dark energy, which seems to make up a large amount of the universe but remains an enigma.

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When observed from a distance, the team noted how the universe appears to consist of clusters of galaxies and massive voids that appear to be empty.

But as noted by NASA, leading models of the universe indicate it is made of entities that cannot be seen. Dark matter is suspected of helping to hold galaxy clusters in place gravitationally, while dark energy is believed to play a role in how the universe is expanding.

According to the researchers responsible for Dark Emulator, the AI tool is able to study possibilities about the "origin of cosmic structures" and how dark matter distribution may have changed over time, using data from some of the top observational surveys conducted about space.

"We built an extraordinarily large database using a supercomputer, which took us three years to finish, but now we can recreate it on a laptop in a matter of seconds," said Associate Prof. Takahiro Nishimichi, of the Yukawa Institute for Theoretical Physics.

"Using this result, I hope we can work our way towards uncovering the greatest mystery of modern physics, which is to uncover what dark energy is. I also think this method we've developed will be useful in other fields such as natural sciences or social sciences."

Nishimichi added: "I feel like there is great potential in data science."

The teams, which included experts from the Kavli Institute for the Physics and Mathematics of the Universe and the National Astronomical Observatory of Japan, said in a media release this week that Dark Emulator had already shown promising results during extensive tests.

In seconds, the tool predicted some of effects and patterns found in previous research projects, including the Hyper Suprime-Cam Survey and Sloan Digital Sky Survey. The emulator "learns" from huge quantities of data and "guesses outcomes for new sets of characteristics."

As with all AI tools, data is key. The scientists said the supercomputers have essentially created "hundreds of virtual universes" to play with, and Dark Emulator predicts the outcome of new characteristics based on data, without having to start new simulations every time.

Running simulations through a supercomputer without the AI would take days, researchers noted. Details of the initial study were published in The Astrophysical Journal last October. The team said they hope to input data from upcoming space surveys throughout the next decade.

While work on this one study remains ongoing, there is little argument within the scientific community that understanding dark energy remains a key objective.

"Determining the nature of dark energy [and] its possible history over cosmic time is perhaps the most important quest of astronomy for the next decade and lies at the intersection of cosmology, astrophysics, and fundamental physics," NASA says in a fact-sheet on its website.

More here:

AI Tool Created to Study the Universe, Unlock the Mysteries of Dark Energy - Newsweek

One click, your mortgage process begins. Another click, that mortgage loan is pre-approved.Five minutes pass and you are ready to buy a home.

The digital application process for single-family mortgages has flourished with new technology, new companies entering the space and new capabilities that, even just 10 years ago, we wouldnt have thought possible.

Borrowers can sign closing papers on a new home remotely so that they dont have to miss hours of work. Travelers can close on their home from the other side of the world. The credit invisible, or those with no credit score, can learn more about their financial situation and what they can do to prepare to buy a home after a quick and painless application process.

But if you fast forward just a few weeks, to when a borrower is getting settled into their new home, the experience changes dramatically. Their mortgage loan is sold and their servicer steps in to introduce themselves. The smooth digital process is suddenly transformed into a rough, paper-heavy and confusing process.

Originally posted here:

Coming soon: The promise of artificial intelligence in servicing - HousingWire

When you hear the word cyborg, scenes from the 1980s films RoboCop or The Terminator might spring to mind. But the futuristic characters made famous in those films may no longer be mere science fiction. We are at the advent of an era where digital technology and artificial intelligence are moving more deeply into our human biological sphere. Humans are already able to control a robotic arm with their minds. Cyborgshumans whose skills and abilities exceed those of others because of electrical or mechanical elements built into the bodyare already among us.

But innovators are pushing the human-machine boundary even further. While prosthetic limbs are tied in with a persons nervous system, future blends of biology and technology may be seen in computers that are wired into our brains.

Our ability to technologically enhance our physical capabilitiesthe hardware of our human systems, you could saywill likely reshape our social world. Will these changes bring new forms of dominance and exploitation? Will unaltered humans be subjected to a permanent underclass or left behind altogether? And what will it mean to be humanor will some of us be more than human?

Initial answers may be closer than we think.

Physicist Max Tegmark, MIT professor and president of the Future of Life Institute, considers the recent advances in artificial intelligence and technology through an evolutionary lens to imagine us as more than human. He categorizes all life into three levels. In his view, the vast majority of lifefrom bacteria to mice, iguanas to lobstersfalls into what he calls Life 1.0. These creatures survive and replicate, but they cannot redesign themselves within their lifetime. They evolve and learn over many generations.

Moving up, somewhere between Life 1.0 and 2.0, Tegmark classifies animals such as some primates, cetaceans, and corvids that have the ability to intermesh biology and culture. These animals are able to learn complex new skills, like how to use tools. Humans take this to an extreme, and Tegmark categorizes humans as Life 2.0. Through extensive language, social intelligence, and culture, Life 2.0 individuals can jump into new environments independently of genetic constraints. (If you missed it, we wrote about how body modification, as one example, makes us more socially human in part I, Your Body as a Map, of this pair of posts.)

Just think about how our ability to learn a new language within our lifetime is a bit like adding a software package to a computer. We can add an infinite number of self upgrades during our lifetime and pass our knowledge on to future generations. We also can manipulate other life forms to our own ends on a grand scalefrom cattle farming to harnessing bacteria in the preparation of fermented foods like cheese.

But with the leaps were seeing in artificial intelligence, neuroscience, and biotechnology, our concept of animal and human could compete with the most imaginative Hollywood film. Life 3.0 doesnt yet exist on Earth, but Tegmark argues that in the future, we will see a technological life-form that can design both its hardware (which neither 1.0 or 2.0 can do) and its software (which currently only 2.0 can do).

Even in the near future, humans may be somewhere in between life-forms 2.0 and 3.0. In 2016, Elon Musk, CEO of Tesla and SpaceX, co-founded Neuralink, a company that aims to develop a braincomputer interface. Musk says his goal is to help human beings merge with software and be in sync with advances in artificial intelligence.

Whether people will volunteer to have a robot insert wires into their brain that are attached to a tiny chip implant remains to be seen. But humans across cultures have embraced a variety of technologies in surprising ways.

Today over 5 billion people have access to mobile phones. By 2025, around 71 percent of the worlds population is expected to be connected. The thought that virtually every aspect of a persons day might be influenced by a smartphone or something like it once seemed like science fiction. But as the number of digital natives grows, our relationship with technology does too.

Some of us readily anthropomorphize our gadgets and give our apps and devices names such as Siri or Alexa. We talk to them, allow them to control our surroundings, finances, shopping, and schedules. Yet many hesitate when it comes to embedding technology in our bodies if we are otherwise physically healthy.

Take, for example, microchips inserted under the skin, which can be used to pay for your shopping as well as a bus ride home. This is little different from a credit card in your back pocket, save for the convenience of not having to remember to take it with you.

Our resistance may be influenced by the yuck factor of new or different technologies or cultural shifts. But over time, what we think of as disgusting or offensive may become normalized. Lab-grown meat, for example, has gone from being a scientific and economic fantasy to something that might well be in stores by 2022. Similarly, eating insects, for those unused to the idea in the West, has become more accepted as a sustainable source of protein.

Even if more of us grow to accept the idea of implants, is Life 3.0 a genuine possibility? For now, mindcontrolled prosthetics are the closest innovation that hints at a Neuralink-type future. Such prosthetics are still in relatively early stages of development and not universally available. Nonetheless, as far as Musk is concerned, many of us are already cyborgs, with an indepth digital version of ourselves in the form of social media, email, and much more. His team, or others, may well inch us toward a version of Life 3.0.

Other early signs of how technologically integrated lives might function and impact our individual lives and societies are visible in places such as Scandinavia, where checks and cash are on their way out. In Denmark, for example, the majority of citizens make payments using their mobile phones. The absence of cash has had a direct effect on homeless people. Without smartphones of their own, homeless individuals were unable to receive payments for the newspapers they sold to earn money.

The solution was to provide homeless people with smartphones (and thus mobile payment methods). No longer a luxury, mobile phones became a basic tool vital for anyone engaging in modern society in Denmark.

As soon as we move into the idea of integrated technology as a social essential, we recognize a thorny possibility: a world where a new path to social or class dominance emergesperhaps a division between those who can and those who cannot afford to interface with technology. It begins to sound like the plot of the 20th-century dystopian novel Brave New World.

In that new world, would the Life 2.0 human without enhancements be relegated to a servile underclass? Perhaps this reflects a false dichotomy. After all, millions of people living in relatively remote regions around the planet have been able to fast-track to mobile technology, effectively skipping over earlier versions of the telephone and other communication technologies.

Nonetheless, developers of integrated technologies involving invasive surgery would be wise to consider the social ramifications of their work. Today we can accurately reconstruct the wealth distribution of an entire nation based on individual phone records. Can we predict the negative social impacts of a future Life 3.0? If contemporary clues are any answer, yes, we can. But whether we choose to ameliorate those impacts or not still lies within our control.

Matthew Gwynfryn Thomas is a data scientist and anthropologist working in the nonprofit sector in London, U.K. His current work combines machine learning and social science to address the needs of people in crisis. He has also written popular science articles for a variety of outlets, includingBioNews, SciDev.Net, and the Wellcome Trust Blog. Follow him on Twitter@matthewgthomas

Djuke Veldhuis is an anthropologist and science writer based at Monash University in Australia, where she is a course director in the B.Sc. advancedglobal challenges degree program. Her Ph.D. research examined the effects of rapid socioeconomic change on the health and well-being of people in Papua New Guinea. She has written for a series of popular science outlets, including SciDev.Net,Asia Research News, andNew Scientist. Follow her on Twitter@DjukeVeldhuis

A version of this article was originally published at the Conversation and has been republished here with permission.

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'More than human': How neural implants, robotics and artificial intelligence are redefining who we are - Genetic Literacy Project

PUNE, India, Feb. 4, 2020 /PRNewswire/ -- The digital reforms in the legal industry have transformed the traditional courtrooms and law practices, thus strengthening the prevalence of Artificial Intelligence (AI) in legal technology or legaltech. The increasing burden of legal activities, carried out around the globe, over a limited number of law practioners has pushed the digitization of legal practices such as Document Management System, e-Discovery, Practice and Case Management, e-Billing, Contract Management and many others. Major law firms are adopting legaltech solutions featuring AI capabilities to tackle the growing competition and reduce the turn-around time of legal cases. For instance, CMS Legal, a global law firm, has deployed AI-based software for quick and efficient analysis of contracts and other legal documents. Data analytics in law industry can be a complex and time consuming task owing to the huge amount of paperwork. Artificial Intelligence has been recognized for its analytical capabilities and legaltech has harnessed that capability in recent years. Companies such as Luminance Technologies Ltd. are offering AI based platform for locating patterns from the loaded document and identifying deviations from standard clauses. These factors have thus catalyzed the growth of global legaltech artificial intelligence market.

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The digitalization trend has also impacted the judicial system of numerous governments. Countries worldwide are transforming their conventional judicial practices along with their courtrooms. For instance, countries such as China and Australia have implemented digital courts to reduce the net cost of legal services to government. China introduced Judicial Big Data Service Network platform in 2017 to improve the judicial system of country using big data and artificial intelligence. This initiative has led to introduction of three online courts with plans to expand further. These courts are limited to civil and administrative claims form e-commerce and other online activities. These courts employ virtual judges based on artificial intelligence and the entire hearing takes place online. Moreover, the state of New South Wales, Australia introduced online courts in 2016 to conduct preliminary hearings. These factors have pushed the law firms and clients to adopt digital methods owing to the ease of use and reduced turn-around time. Artificial intelligence has improved the efficiency of legaltech thus increasing its adoption in government agencies as well as private law firms and is thus, fueling the growth of global legaltech artificial intelligence market.

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Global LegalTech Artificial Intelligence Market is Expected to Grow at a CAGR of More Than 37.7% Over the Forecast Period Owing to Digitalization...

Commentary

Photo by Michael Langan

ByOren Etzioni & Carissa Schoenick

Editors Note: This Commentary is part of a special report exploring game-changing trends and innovations that have the potential to shake up the schoolhouse.Read the full report: 10 Big Ideas in Education.

Artificial intelligence is a rapidly emerging technology that has the potential to change our everyday lives with a scope and speed that humankind has never experienced before. Some well-known technology leaders such as Tesla architect Elon Musk consider AI a potential threat to humanity and have pushed for its regulation "before it's too late"an alarmist statement that confuses AI science with science fiction. What is the reality behind these concerns, and how can educators best prepare for a future with artificial intelligence as an inevitable part of our lives?

General, widespread legislative regulation of AI is not going to be the right way to prepare our society for these changes. The AI field is already humming with a wide variety of new research at an international scale, such that blindly constraining AI research in its early days in the United States would only serve to put us behind the global curve in developing the most important technology of the future. It is also worth noting that there are many applications of AI currently under development that have huge potential benefits for humanity in the fields of medicine, security, finance, and personal services; we would risk a high human and economic cost by slowing or stopping research in those areas if we hastily impose premature, overbearing, and poorly understood constraints.

Oren Etzioni & Carissa Schoenick are CEO and senior program manager at the Allen Institute for Artificial Intelligence, respectively.

Based in Seattle, Etzioni is a professor of computer science at the University of Washington; Schoenick was previously a program manager for Amazon Web Services and for the computational knowledge project WolframAlpha.

The most impactful way to shape the future of AI is not going to be through the regulation of research, but rather through understanding and correctly controlling the tangible impacts of AI on our lives. For example, it is our belief that AI should not be weaponized, and that humans should always have the ultimate "off switch." Beyond these obvious limitations, there are three rules we propose for AI that can be meaningfully applied now to mitigate possible future harm.

An AI system:

1) Must always respect the same laws that apply to its creators and operators;

2) Must always disclose that it is not human whenever it interacts with another entity;

3) Should never retain or share confidential information without explicit approval from the source.

These rules are a strong practical starting point, but to successfully navigate the new world AI will bring about in the coming decades, we're going to need to ensure that our children are learning the skills required both to make sense of this new human-machine dynamic and to control it in the right ways. All students today should be taught basic computer literacy and the fundamentals behind how an AI works, as they will need to be comfortable with learning and incorporating rapidly emerging new technologies into their lives and occupations as they are developed.

We will need our future scientists and engineers to be keenly aware that an AI system can only be as good as the data it is given to work with, and that to avoid dangerous bias or incorrect actions, we need to cultivate the right inputs to these systems that fairly cover all possible perspectives and variables. We will need policymakers who can successfully apply the rules suggested above as well as define the new ones we will need as AI continues to proliferate into the various aspects of our lives.

New and different opportunities and values will likely emerge for humans in the economy that AI creates. As AI makes more resources more widely available, we will find less meaning in material wealth and more value in the activities that are uniquely human. This means that occupations with creative and expressive qualities, such as chefs, tailors, organic farmers, musicians, and artists of all types will become more important in an age in which a real human connection is increasingly precious. Roles that directly affect human development and well-being, such as teaching, nursing, and caregiving, will be especially crucial and should be uplifted as excellent options for people whose vocations are otherwise replaced by AI systems. No AI can hope to match a human for true compassion and empathy, qualities that we should be taking extra care to cultivate in our children to prepare them to inherit a world where these characteristics will be more important than ever.

Background

By Benjamin Herold

What will the rise of artificial intelligence mean for K-12 education?

First, AI and related technologies are reshaping the economy. Some jobs are being eliminated, many others are being changed, and entirely new fields of work are opening up. Those changes are likely to have big implications for the job market in 2030, when today's 6th graders are set to hit their prime working years. But the nation's top economists and technologists are sharply divided about whether AI will be a job killer or creator, presenting a big challenge for the educators and policymakers who must prepare today's students to thrive in a very uncertain tomorrow.

Second, artificial intelligence is changing what it means to be an engaged citizen. K-12 education has never been just about preparing young people for jobs; it's also about making sure they're able to weigh arguments and evidence, synthesize information, and take part in the civic lives of their communities and country. But as algorithms, artificial intelligence, and automated decisionmaking systems are being woven into nearly every aspect of our lives, from loan applications to dating to criminal sentencing, new questions and policy debates and ethical quandaries are emerging. Schools are now faced with having to figure out how to teach students to think critically about the role these technologies are playing in our society and how to use them in smart, ethical ways. Plus, in the age of AI, students will likely have to develop a new communication skill: the ability to talk effectively to intelligent machines. Some economists say that skill could be the difference between success and failure in the workplace of the future.

And third, artificial intelligence could play a powerful role in the push to provide more personalized instruction for all studentsand in the process change the teaching profession itself. Intelligent tutoring systems are making inroads in the classroom. New educational software and technology platforms use algorithms to recommend content and lessons for individual students, sometimes pushing teachers away from the front of the classroom and into the role of "coach" or "facilitator." And schools are being flooded with data about their students, information that educators and administrators alike are increasingly expected to use to make real-time decisions and adjustments in the course of their day-to-day work.

Some educators see the rising role of AI as a threat to their existence and a danger to student-data privacy. Others take a more positive view, seeing it as having the potential to free them from mundane tasks like lecturing and grading, creating rich opportunities for continuous improvement, and opening the doors for more meaningful trial-and-error learning by students.

Whatever the perspective, there is one thing most everyone seems to agree on: Now is the time for the K-12 field to start wrestling with the promises and perils of AI.

Vol. 37, Issue 16, Pages 28-29

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Artificial Intelligence: What Educators Need to Know ...