Weve all heard the warning cries: automation will disrupt entire industries and put millions of people out of jobs. In fact, up to 45 percent of existing jobs can be automated using current technology.

However, this may not necessarily apply to the education sector. After a detailed analysis of more than 2,000-plus work activities for more than 800 occupations, a report by McKinsey & Co states that of all the sectors examined, the technical feasibility of automation is lowest in education.

There is no doubt that technological trends will have a powerful impact on global education, both by improving the overall learning experience and by increasing global access to education. Massive open online courses (MOOCs), chatbot tutors, and AI-powered lesson plans are just a few examples of the digital transformation in global education. But will robots and artificial intelligence ever fully replace teachers?

While various tasks revolving around educationlike administrative tasks or facilities maintenanceare open to automation, teaching itself is not.

Effective education involves more than just transfer of information from a teacher to a student. Good teaching requires complex social interactions and adaptation to the individual students learning needs. An effective teacher is not just responsive to each students strengths and weaknesses, but is also empathetic towards the students state of mind. Its about maximizing human potential.

Furthermore, students dont just rely on effective teachers to teach them the course material, but also as a source of life guidance and career mentorship. Deep and meaningful human interaction is crucial and is something that is very difficult, if not impossible, to automate.

Automating teaching is an example of a task that would require artificial general intelligence (as opposed to narrow or specific intelligence). In other words, this is the kind of task that would require an AI that understands natural human language, can be empathetic towards emotions, plan, strategize and make impactful decisions under unpredictable circumstances.

This would be the kind of machine that can do anything a human can do, and it doesnt existat least, not yet.

Lets not forget how quickly AI is evolving. Just because its difficult to fully automate teaching, it doesnt mean the worlds leading AI experts arent trying.

Meet Jill Watson, the teaching assistant from Georgia Institute of Technology. Watson isnt your average TA. Shes an IBM-powered artificial intelligence that is being implemented in universities around the world. Watson is able to answer students questions with 97 percent certainty.

Technologies like this also have applications in grading and providing feedback. Some AI algorithms are being trained and refined to perform automatic essay scoring. One project has achieved a 0.945 correlation with human graders.

All of this will have a remarkable impact on online education as we know it and dramatically increase online student retention rates.

Any student with a smartphone can access a wealth of information and free courses from universities around the world. MOOCs have allowed valuable courses to become available to millions of students. But at the moment, not all participants can receive customized feedback for their work. Currently, this is limited by manpower, but in the future that may not be the case.

What chatbots like Jill Watson allow is the opportunity for hundreds of thousands, if not millions, of students to have their work reviewed and all their questions answered at a minimal cost.

AI algorithms also have a significant role to play in personalization of education. Every student is unique and has a different set of strengths and weaknesses. Data analysis can be used to improve individual student results, assess each students strengths and weaknesses, and create mass-customized programs. Algorithms can analyze student data and consequently make flexible programs that adapt to the learner based on real-time feedback. According to the McKinsey Global Institute, all of this data in education could unlock between $900 billion and $1.2 trillion in global economic value.

Its important to recognize that technological automation alone wont fix the many issues in our global education system today. Dominated by outdated curricula, standardized tests, and an emphasis on short-term knowledge, many experts are calling for a transformation of how we teach.

It is not enough to simply automate the process. We can have a completely digital learning experience that continues to focus on outdated skills and fails to prepare students for the future. In other words, we must not only be innovative with our automation capabilities, but also with educational content, strategy, and policies.

Are we equipping students with the most important survival skills? Are we inspiring young minds to create a better future? Are we meeting the unique learning needs of each and every student? Theres no point automating and digitizing a system that is already flawed. We need to ensure the system that is being digitized is itself being transformed for the better.

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Why Education Is the Hardest Sector of the Economy to Automate - Singularity Hub

I'm calling it - we're in the Summer of Artificial Intelligence. Ok, it might not sound as glamorous as the Summer of Love or Bryan Adams' Summer of '69, but it's just as seminal - if not more so.

Over the past couple of years we've seen a trend where technologies previously reserved for the elite or big tech giants have been opened up to mass consumption. We saw this last summer, when the launch of Pokmon Go and the game's meteoric rise - amassing 10 million downloads in its first week - brought Augmented Reality (AR) into the mainstream. A year on, consumers across the world use AR without batting an eyelid every time we add a Snapchat filter.

This year, we're seeing Artificial Intelligence go through the same kind of shift. Amazon Alexa's domination shows no sign of stopping, and June saw the successful launch of Amazon Echo Show, adding video to the highly competent voice technology. Now, for the first time, Alexa has been built natively into a smartphone - the HTC U11. Even the most traditional of British institutions are using AI to enrich the consumer experience, with Wimbledon using IBM Watson to create a voice assistant called Fred (after Fred Perry, obviously) to direct fans to the nearest strawberries. Gone are the days when AI sounded like science fiction - we all interact with it countless times every day; knowingly or not.

The democratisation of these kinds of technologies is a wonderful thing. As well as allowing people to run around cities catching Pidgeys and Rattatas to their hearts' content, AR is enabling surgeons with limited resources to get interactive training from other doctors overseas. And the applications of AI stretch miles beyond Alexa telling you the weather forecast - with mobile health apps now giving millions of people in developing countries access to instant diagnosis.

Consumer trust in Artificial Intelligence is growing, and adoption around the world is rocketing - but we must make sure that as trust in this kind of technology grows, accountability comes with it.

Earlier this month, Elon Musk told a roomful of US governors that AI poses an 'existential threat' to civilisation, and went on to merrily suggest ways that AI could wipe out humanity. With all due respect to the Tesla founder, this is a little catastrophic. We have far more to gain from AI than fear.

What is worth discussing, though, is the responsibility of the tech community to ensure that they are creating this technology in an ethical way - with safety, equality and accessibility at front of mind. To this end, Sage has created a set of five guidelines for businesses to follow as we embark on the Fourth Industrial Revolution - it's called The Ethics of Code.

For AI to truly work, this is what we think it should do.

1. It should reflect the diversity of the users it serves.

We all know that we have unconscious biases relating to gender, race, sexuality and more - let's not build them into our software. The first voice recognition software couldn't understand female voices - because it was tested on an all-male team.

2. It should be held to account - and so should its users.

The trust we place in technology needs to be taken seriously - AI must never be allowed to be too clever to be accountable. We don't accept unpleasant or unethical behaviour from people in the workplace - why should we accept it from our technology?

3. It should be rewarded for 'good behaviour'.

Most organisations now have a variant of 'doing the right thing' as one of their values - we need to hold our technology to the same standards. When designing AI, it should be rewarded for performing a task successfully, but also for how it aligned with good values to get there.

4. It should level the playing field.

AI should have minimal barriers to access, and should work to democratise services that were previously off limits to groups of people. Voice recognition software makes multiple solutions accessible to people with sight impairments, as well as those with dyslexia and limited mobility.

5. It will replace jobs, but it must also create them.

Ok, the robots aren't going to steal all our jobs - but they are going to take on some roles that automation is better suited to. But for any jobs that AI is going to replace, its existence will also evolve existing jobs and create new ones. I have a friend who's a conversation designer, writing the personality of a chatbot - jobs like that weren't even thought of five years ago.

**

Although I'm calling this the 'summer of artificial intelligence', this technology is far more than a passing trend. Unlike fidget spinners and ripped jeans, AI will stick around - continuing to evolve and permeate all aspects of our daily lives. And this isn't something to fear. It will bring huge opportunity, and open up a host of services previously reserved for the most privileged - if we create it in the right way.

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Why This Is The Summer Of Artificial Intelligence - HuffPost UK

MAGOS is a complex AI forecasting model, based on a collaborative system of neural networks. It serves as a core for a fund that operates on Ethereum blockchain. By using the latest developments in AI and neutral networks, MAGOS is able to forecast the outcome of an event with a high degree of accuracy. The model was open tested earlier this year, and showed a significant forecasting edge that anyone can verify. This edge is used by the fund to generate profits from multiple platforms, including prediction markets. Share of profits is distributed between the holders of MAG tokens, available through a crowdsale opening on August 16th.

Today, a lot of Blockchain projects are aiming to build a decentralized prediction market platform, where individuals can bet on the outcome of future events. It will offer an opportunity for forecasters to monetize their knowledge and ability. Those who can accurately predict the outcome will turn a profit in the long run, and the best forecasters will be the ones making the most money.

It is only a matter of time before prediction markets become a disruptive economic innovation, offering this monetization opportunity to mass audience. However, for an individual to fully realize this opportunity in todays Era of technology, it is more than necessary to have access to an accurate forecasting model.

The purpose of MAGOS project is to build the ultimate forecasting tool, by using the advancements in AI and machine learning, and connect it to a wide variety of platforms: from prediction markets, to exchanges and sportsbooks.

If you would look at the current state of forecasting though a prism of AI and its latest developments the forecasting methodology would appear extremely dated. And for a good reason It is still largely dependent on simplistic predicative models, outdated forecasting algorithms, and human expertise. Our team of talented data scientists aims to significantly change the landscape of forecasting with MAGOS, and our goal is to allow anyone to share the success of AI in the forecasting domain. The project is far from being just an idea, we have a functioning model that has been operating since 2015, and was extensively tested multiple times. We encourage everyone to look into the results of MAGOS performance, see what the model is capable of, and join us in the upcoming crowdsale on August 16th.

Ante Magnusson, CEO, MAGOS AI

MAGOS is based on a system of neural networks. Each network performs a specific task, but they work together in collaboration. The backbone of MAGOS is its modular architecture. It allows us to develop and implement individual forecasting modules, targeting different kinds of forecasting domains, from business and finance to sports and politics.

Andreas Theiss, Data scientist and CTO, MAGOS AI

The MAGOS crowdsale opens August 16th and MAG tokens are strictly limited in supply. Earliest contributors receive a discount on their MAG tokens. Token holders have access to a share of profits the fund generates, proportional to the number of tokens they hold. In addition, the tokens grant special voting rights, allowing the holders to influence projects development and fund parameters. ERC20 standard MAG token will also be tradeable on exchanges.

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MAGOS Oracle based on Artificial Intelligence - newsBTC

Elon Musk tweeted some warnings about artificial intelligence on Friday night.

"If you're not concerned about AI safety, you should be. Vastly more risk than North Korea," Musk tweeted after his $1 billion startup, OpenAI, made a surprise appearance at a $24 million video game tournament Friday night, beating the world's best players in the video game, "Dota 2."

Musk claimed OpenAI's bot was the first to beat the world's best players in competitive eSports, but quickly warned that increasingly powerful artificial intelligence like OpenAI's bot which learned by playing a "thousand lifetimes" of matches against itself would eventually need to be reined in for our own safety.

"Nobody likes being regulated, but everything (cars, planes, food, drugs, etc) that's a danger to the public is regulated. AI should be too," Musk said in another tweet on Friday night.

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North Korean leader Kim Jong Un applauds during a military parade marking the 105th birth anniversary of the country's founding father, Kim Il Sung, in Pyongyang April 15, 2017. REUTERS/Damir Sagolj

Missiles are driven past the stand with North Korean leader Kim Jong Un and other high ranking officials during a military parade marking the 105th birth anniversary of country's founding father Kim Il Sung, in Pyongyang April 15, 2017. REUTERS/Damir Sagolj TPX IMAGES OF THE DAY

High ranking military officers cheer as North Korean leader Kim Jong Un arrives for a military parade marking the 105th birth anniversary of country's founding father Kim Il Sung, in Pyongyang April 15, 2017. REUTERS/Damir Sagolj

People react as they march past the stand with North Korean leader Kim Jong Un during a military parade marking the 105th birth anniversary of the country's founding father Kim Il Sung, in Pyongyang, April 15, 2017. REUTERS/Damir Sagolj

TOPSHOT - Korean People's Army (KPA) tanks are displayed during a military parade marking the 105th anniversary of the birth of late North Korean leader Kim Il-Sung in Pyongyang on April 15, 2017. North Korean leader Kim Jong-Un on April 15 saluted as ranks of goose-stepping soldiers followed by tanks and other military hardware paraded in Pyongyang for a show of strength with tensions mounting over his nuclear ambitions. / AFP PHOTO / Ed JONES (Photo credit should read ED JONES/AFP/Getty Images)

Korean People's Army (KPA) soldiers march on Kim Il-Sung squure during a military parade marking the 105th anniversary of the birth of late North Korean leader Kim Il-Sung in Pyongyang on April 15, 2017. North Korean leader Kim Jong-Un on April 15 saluted as ranks of goose-stepping soldiers followed by tanks and other military hardware paraded in Pyongyang for a show of strength with tensions mounting over his nuclear ambitions. / AFP PHOTO / Ed JONES (Photo credit should read ED JONES/AFP/Getty Images)

North Korean leader Kim Jong Un waves to people attending a military parade marking the 105th birth anniversary of country's founding father Kim Il Sung, in Pyongyang April 15, 2017. REUTERS/Damir Sagolj

Military vehicles carry missiles with characters reading "Pukkuksong" during a military parade marking the 105th birth anniversary of country's founding father Kim Il Sung, in Pyongyang April 15, 2017. REUTERS/Damir Sagolj

Members of the Korean People's Army (KPA) ride on mobile missile launchers during a military parade marking the 105th anniversary of the birth of late North Korean leader Kim Il-Sung in Pyongyang on April 15, 2017. North Korean leader Kim Jong-Un on April 15 saluted as ranks of goose-stepping soldiers followed by tanks and other military hardware paraded in Pyongyang for a show of strength with tensions mounting over his nuclear ambitions. / AFP PHOTO / Ed JONES (Photo credit should read ED JONES/AFP/Getty Images)

North Korean soldiers march and shout slogans during a military parade marking the 105th birth anniversary of the country's founding father Kim Il Sung in Pyongyang, North Korea, April 15, 2017. REUTERS/Damir Sagolj

An unidentified rocket is displayed during a military parade marking the 105th anniversary of the birth of late North Korean leader Kim Il-Sung in Pyongyang on April 15, 2017. North Korean leader Kim Jong-Un on April 15 saluted as ranks of goose-stepping soldiers followed by tanks and other military hardware paraded in Pyongyang for a show of strength with tensions mounting over his nuclear ambitions. / AFP PHOTO / Ed JONES (Photo credit should read ED JONES/AFP/Getty Images)

People carry flags in front of statues of North Korea founder Kim Il Sung (L) and late leader Kim Jong Il during a military parade marking the 105th birth anniversary Kim Il Sung in Pyongyang, April 15, 2017. REUTERS/Damir Sagolj TPX IMAGES OF THE DAY

North Korean soldiers march and shout slogans during a military parade marking the 105th birth anniversary of country's founding father, Kim Il Sung in Pyongyang, North Korea April 15, 2017. REUTERS/Damir Sagolj TPX IMAGES OF THE DAY

A soldier salutes from atop an armoured vehicle as it drives past the stand with North Korean leader Kim Jong Un during a military parade marking the 105th birth anniversary of country's founding father Kim Il Sung, in Pyongyang April 15, 2017. REUTERS/Damir Sagolj

North Korean soldiers march and shout slogans during a military parade marking the 105th birth anniversary of country's founding father Kim Il Sung in Pyongyang, North Korea, April 15, 2017. REUTERS/Damir Sagolj

North Korean soldiers attend a military parade marking the 105th birth anniversary of country's founding father Kim Il Sung in Pyongyang, North Korea, April 15, 2017. REUTERS/Damir Sagolj

Attendees carry sheets in colours of the national flag of North Korea during a military parade marking the 105th birth anniversary of country's founding father Kim Il Sung, in Pyongyang April 15, 2017. REUTERS/Damir Sagolj

North Korean soldiers, some of them on horses, march during a military parade marking the 105th birth anniversary of country's founding father Kim Il Sung in Pyongyang, North Korea, April 15, 2017. REUTERS/Damir Sagolj

Civilian attendees watch North Korean soldiers marching during a military parade marking the 105th birth anniversary of country's founding father Kim Il Sung in Pyongyang, North Korea, April 15, 2017. REUTERS/Damir Sagolj

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Musk has previously expressed a healthy mistrust of artificial intelligence. The Tesla and SpaceX CEO warned in 2016 that, if artificial intelligence is left unregulated, humans could devolve into the equivalent of "house cats" next to increasingly powerful supercomputers. He made that comparison while hypothesizing about the need for a digital layer of intelligence he called a "neural lace" for the human brain.

"I think one of the solutions that seems maybe the best is to add an AI layer," Musk said. "A third, digital layer that could work well and symbiotically" with the rest of your body," Musk said during Vox Media's 2016 Code Conference in Southern California.

Nanotechnologists have already been working on this concept.

Musk said at the time: "If we can create a high-bandwidth neural interface with your digital self, then you're no longer a house cat."

Jillian D'Onfro contributed to this report.

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SEE ALSO: Elon Musk's $1 billion AI startup made a surprise appearance at a $24 million video game tournament and crushed a pro gamer

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Elon Musk: Artificial intelligence presents 'vastly more risk than North Korea' - AOL

Artificial intelligence took a step forward last night, at an annual tournament for players of the tactical wargame Defense of the Ancients 2. A bot created by the Elon Musk-backed nonprofit OpenAI defeated champion human player Danylo Dendi Ishutin in two back to back demonstration matches.

Musk hailed the achievement on Twitter, saying that it was a significant advance over what AI had accomplished in more traditional games .

Defense of the Ancients 2 commonly referred to as DOTA 2 is whats known as a multiplayer online battle arena, or MOBA. Players control one of dozens of different characters with varying abilities, and compete to collect items and control territory. Its currently one of the most popular games from Valve, the publisher that organized last nights event, and one of the most popular competitive e-sports games worldwide.

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AI developers have recently shown that computers can dominate the best human players in Go and chess. But DOTA 2 has far more variables and possible board states than even Go, meaning decision-making is much more complex. The game also takes place in real time rather than discrete turns.

The bot's victory, then, adds up to more than just fun and games. OpenAI describes it as "a step towards building AI systems which accomplish well-defined goals in messy, complicated situations involving real humans." That includes applications like delivery routing, strategic planning, and traffic management.

According to The Verge, last nights demonstration did reduce some of the games complexity. Perhaps most significantly, while Ishutin was defeated in a 1-on-1 match, DOTA 2 is normally played by opposing teams of five players each. OpenAI says it plans to continue developing its software so it can play full-scale matches.

It might seem odd that Elon Musk would sponsor AI development at all, since hes been vocal about the threat he thinks the technology poses to humanity. But OpenAI is aimed at building safe AI and influencing the conditions under which AI is created potentially by helping Musk push for greater regulation of the technology.

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This Elon Musk-Backed Startup Just Used AI to Defeat a Pro Gamer - Fortune

Mark Zuckerberg and Elon Musk have recently been trading insults about each other's knowledge of AI. Before taking sides, you might want to learn the technology for yourself. The Deep Learning and Artificial Intelligence Introductory Bundle helps you build your own intelligent programs through four premium courses. You can start learning now for just $39 via the Popular Science Shop.

Self-driving cars and voice assistants are only scratching the surface of what artificial intelligence can do. Before long, AI will be an essential feature in every device, app and website. This bundle helps you get ahead of the curve and gain valuable skills.

Inspired by the human brain, deep learning allows software to learn from its own mistakes and observations. To develop this kind of artificial intelligence, you need a working knowledge of data science. This bundle covers both topics through hands-on video tutorials, and you learn how to code with Python. Aside from the tech sector, these skills are highly valuable in business, finance, and marketing.

They're normally $480, but you can get these courses now for just $39.

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The deep learning and artificial intelligence introductory bundle - Popular Science

Airbnb has cancelled several reservations made by those planning to attend the rally, telling NBC29, "When throughout background check processes or from input of our community we identify and determine that there are those who would be pursuing behavior on the platform that would be antithetical to the Airbnb Community Commitment, we seek to take appropriate action including, as in this case, removing them from the platform."

Members of anti-fascist and anti-racist groups were also on the scene last night and several fights broke out at the foot of the Thomas Jefferson statue. Police broke up the fights and sent protestors away. Witnesses on twitter and in live YouTube videos claimed that chemicals were dispersed.

Last night's march was sparked by a federal judge ruling that the Unite the Right rally could go on in Emancipation park as planned, according to Fox News. City officials had announced earlier this week that the protest must be moved to a different park further from the downtown area as they expect thousands of protestors to show up. The American Civil Liberties Union (ACLU) of Virginia and Rutherford Institute, filed an injunction early Friday, demanding that the rally continue as planned and won.

Virginia Gov. Terry McAuliffe has ordered members of the National Guard to be on standby at the event today, and declared a state of emergency after things turned violent. He said in a statement, "Men and women from state and local agencies will be in Charlottesville [on Saturday] to keep the public safe, and their job will be made easier if Virginians, no matter how well-meaning, elect to stay away from the areas where this rally will take place."

Sounds familiar: The KKK held a similar, torch-bearing protest in the beginning of July, which was met with 1,000 counter protestors and resulted in 23 arrests.

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Mattis: Pentagon should leverage artificial intelligence - Axios

NEW YORK (Reuters) - U.S. technology company The Bitfury Group has formed a partnership with Insilico Medicine, a Baltimore-based medical artificial intelligence (AI) firm, to create new applications for the healthcare industry using blockchain, Bitfury's chief executive officer said on Friday.

Blockchain is a digital ledger of transactions that gained prominence as the software underpinning the digital currency bitcoin. The technology, being developed in the public and private sectors, has gained attention globally for its ability to permanently record and track assets or transactions across all industries.

The two companies signed a memorandum of understanding last month for collaboration to study and develop blockchain and AI solutions for sharing, managing, tracking and validating healthcare data, said Bitfury founder and CEO Valery Vavilov in an email to Reuters. The collaboration is in an early stage and there were no details available about potential projects or specific uses.

Artificial intelligence in the healthcare sector uses algorithms and software to mimic human ability in analyzing complex medical data. Vast amounts of healthcare data are pushing the development of AI applications.

Vavilov said both companies will use Bitfury's Exonum blockchain platform to store and secure health data in a system compatible with artificial intelligence.

"AI has not reached its full potential for the healthcare industry yet because it requires a large and diverse range of data to learn from in order to ensure accuracy and provide actionable results," said the Bitfury chief executive.

Healthcare AI is expanding by an annual rate of 40 percent, research firm Frost & Sullivan said in a recent study. It said global revenue generated by artificial intelligence systems will soar to $6.7 billion by 2021 from $811 million in 2015.

"A blockchain-based medical records system could safeguard patient data and allow for improved interoperability between doctors and hospitals, while also giving patients more ownership over their own records," Vavilov said.

Reporting by Gertrude Chavez-Dreyfuss; Editing by David Gregorio

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US blockchain company in tie-up on medical artificial intelligence - Reuters

Evolutionary biologist and "passionate rationalist" Richard Dawkins has a new anthology of essays out today, titled Science in the Soul. Over at Scientific American, John Horgan posted an interview with Dawkins in which the two discuss a range of topics, from A.I. to agnosticism. From SciAm:

At the Templeton (Foundation) meeting, you described yourself as an agnostic, because you cannot be certain that God does not exist, correct?

This is a semantic matter. Some people define atheism as a positive conviction that there are no gods and agnosticism as allowing for the possibility, however slight. In this sense I am agnostic, as any scientist would be. But only in the same way I am agnostic about leprechauns and fairies. Other people define agnosticism as the belief that the existence of gods is as probable as their nonexistence. In this sense I am certainly not agnostic. Not only are gods unnecessary for explaining anything, they are overwhelmingly improbable. I rather like the phrase of a friend who calls himself a tooth fairy agnostichis belief in gods is as strong as his belief in the tooth fairy. So is mine. We live our lives on the assumption that there are no gods, fairies, hobgoblins, ghosts, zombies, poltergeists or any supernatural entities. Actually, it is not at all clear what supernatural could even mean, other than something which science does not (yet) understand....

...Do you share the concerns of billionaire entrepreneur Elon Musk, who has said that artificial intelligence might pose an existential risk to humanity?

Elon Musk is a 21st-century genius. You have to listen to what he says. I am philosophically committed to mechanistic naturalism, from which follows the conclusion that anything humans can do, machines can in principle do, too. In many cases we already know they can do it better. Whether they can do it better in all cases remains to be seen, but I wouldnt bet against it. The precautionary principle should lead us to behave as though there is a real dangera danger we should take immediate steps to forestall. Unless, that is, we think robots could to a better job of running the world than we can. And a better job of being happy and increasing the sum of sentient happiness...

Why we secretly love our cords. Tamara Warren: Theres a certain security in the cord. Its the idea of connection, perhaps even dating back to our days in the womb. A battery, no matter how sophisticated, is fleeting. When we have our cords with us, we are in constant pursuit of power, even when []

The classic beatbox not an expensive clone or a collection of cleverly-tweaked samples is back. Rolands TR-08 directly models the original machines analog circuits to recreate its sound as accurately as possible with modern digital technology, and joins revived versions of the TR-909[Amazon] and TB-202[Amazon] in the companys lineup of boutique boxes. The []

Coming after improvements to Firefox and continued unease at Googles life-pervading insight, this image is outperforming the Virality Control Group today (via). It got me thinking about all the promises that were made. Heres the earliest article in Google News to contain Big browser in its headline, published by Time Magazine on Nov. []

This project management bundle will help you get organized and learn how to lead a team to success. You can pay what you want for these five courses when you pick them up from the Boing Boing Store.To help you become an invaluable asset for your company, this bundle includes a curated collection of professional []

Despite the push towards USB-C as the one connector to rule them all, most peripherals in the wild are still largely USB-A. Since theres little reason to upgrade all of your old flash drives, wired keyboards, and game controllers, youll need a decent hub to keep them all talking to your new computer.The MondoHub Master []

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Richard Dawkins on artificial intelligence, agnosticism, and utopia - Boing Boing

Posted August 11, 2017 11:58:38

Artificial intelligence is becoming commonplace, from your smartphone and your Amazon account to the driverless cars that will soon grace public roads in Australia.

Often, the response to this reality is one of trepidation and concern, about mass unemployment and the dominance of Big Tech. But that's not always the case.

"Art is one of the last domains in AI where there is an optimistic view on how humans and machines can work together," says Dave King, founder of Move 37, a creative AI company.

He says creativity is not a God-given thing. It's a process, and it takes practice.

"One of the most interesting aspects of creativity is that ability to combine ideas or to draw things together," he says.

"If you have an algorithm that is working for you in the way you want it to it can source and discover lots and lots of different things."

AI is already being used in a range of artistic fields. Algorithms trained on millions of pages of romance novels have been used to write poems, and the recent Robot Art Competition showed a range of paintings with brushwork so sophisticated it could have been done by a human hand.

Jon McCormack is an artist and professor of computer science at Monash University whose work incorporates algorithms.

His series Fifty Sisters (2012) featured images of futuristic-looking plants that were "algorithmically grown" from computer code. In another work, titled Eden, he created an installation featuring "virtual creatures" whose movements were influenced by gallery visitors entering the space.

McCormack says when there is concern about AI, it is understandable.

"We're naturally scared of anything where we take away something from people, particularly something as precious as being creative and art, which we associate with being the most fundamental human [trait] that thing that differentiates us from every other species on the planet," he said.

After all, as AI expert Professor Toby Walsh notes: "We have one of the most creative brains out there."

"One of the oldest jobs on the planet, being a carpenter or an artisan, we will value most [in the future] because we will like to see an object carved or touched by the human hand, not a machine."

Artists have always used tools to create their work: for Van Gogh, it was a paint brush; for Henri Cartier-Bresson, a Leica camera.

With AI, however, the question becomes one of authorship.

"I see myself as being the artist," McCormack says of his compositions. "The computer is still very primitive it doesn't have the same capabilities as a human creative, but it's capable of doing things that complement our intelligence.

King says AI currently can only bring a limited perspective to artistic practice.

"They can only draw on what they've been trained on," he says, referring to the reams of data used to create artificial intelligence. "Whereas the human condition is expansive and broad and brings a lot more depth of perspective to it."

By itself, AI can certainly generate things that look like art, McCormack says. Whether you could consider it art is a harder question.

"So much of what we think about art is humans communicating to each other," he says.

"As soon as you bring a computer into the mix, suddenly you've got a non-human entity trying to fulfil the role that used to be occupied exclusively by people."

Soon, however, it may be possible to go further; to consider the machine not just a tool, but a partner or collaborator, with its own ability to create.

"We always think of Lennon and McCartney as being the great musical creative partnership," McCormack says.

"Will we eventually see a point in time where we have a human and computer partnership that we acknowledge as being more than the sum of its parts?

"If the art was really, really good if it moved us emotionally in the way the best art does then I think we would come to start to accept art that's made by machines."

Topics: arts-and-entertainment, robots-and-artificial-intelligence, science-and-technology, australia

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Artificial intelligence and creativity: If robots can make art, what's left for us? - ABC Online

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Growing up, theres a good chance you heard the mantra go to a good school, get a good job, and make lots of money. On the surface, that seems like sound advice. After all, college graduates, on average,earn almost $1 million morein their lifetimes than those with only a high school education.

Perhaps you were encouraged to get a professional degree to land a high paying job like a doctor, dentist, lawyeror something similar.This also seems like great advice, considering a professional degree holder typically earns more than $2 million more in their lifetimes than the average college graduate.

But that was then, and this now.

Related: The Future of Productivity: AI and Machine Learning

Thanks to rapid advances in robotics, automation and artificial intelligence, jobs are falling to machines left and right. And its not just blue-collar jobs that are being taken over by automation. It's white-collar professions as well. According to an Oxford study, 47 percentof U.S. jobs could fall to automation in the next 20 years.

The safe, high paying jobs of the past are starting to look much less secure going forward. If youre currently in one of the following professions, or going to school to get into these fields, you should think twice before continuing.

If Wall Street is known for anything, its known for crazy high salaries and bonuses. For those who have wanted to get rich quickly post-college, there have been few better industries than finance. Alas, finance is one of the industries with the highest risk of automation.

Bridgewater Associates, the worlds largest hedge fund, announced late last year that it was going to be cutting staff in favor of more automation. Its getting harder to compete with AI driven hedge funds like Sentient and high-frequency traders in general, and an impressive swath of financial management services are now being handled by robo-advisors like Betterment and Wealthfront, both of which are growing rapidly.

In fact, according to Angel List, there are more than 15,000 finance startups right now working to actively disrupt finance, many of them utilizing artificial intelligence and other forms of automation. If youre in this field or planning to enter it, you might want to reconsider.

So, if not finance, then what? If youre good with numbers and detail-oriented, you should consider getting into data science. Data scientist salaries are rising rapidly, and theyre considered the new rock stars of the tech world. Of course, you could always try getting into venture capital to ride the massive transitional wave thats coming, but being a VC isnt all its cracked up to be either. Either way, traditional finance jobs are on the way out.

Related: How AI Machines Coudl Save Wall Street Brokers' Jobs

The work that doctors do is tremendously important, and on average, theyre very well paid for it. That said, there are numerous areas of medicine that are ripe for automation and improved efficiencies. One key example would be medical imaging and the fields of radiology, pathology and dermatology.

Using AI, IBMs Watson is now considered at least on-par with a professional radiologist in terms of ability to analyze an image and diagnose a patient, and it can do the analysis much faster while considering vastly larger amounts of information than any human could ever hope to. This is fantastic news for the people who need a diagnoses, but not so great for medical imaging jobs. If youre already in the field, or working to get into it, you could consider transitioning into some aspect of computer vision, be it research or training. If you cant beat the machines, you can always help to make them better.

There are numerous other technologies, such as telemedicine and mobile medical devices, that will also heavily disrupt this field going forward. And while there will still be a strong need for certain medical skills going forward, youll need to be highly selective in what you choose.

Ahh, lawyers. The world could probably use far fewer lawyers, and the machines are well on their way to making that a reality. While you can still make a pretty penny as a lawyer, depending on your specialty, its worth noting that lawyers spend a lot of time gathering and parsing data, creating or reviewing legal documentsand numerous other mundane tasks. For most lawyers, its far from a glamorous profession.

Much of this grunt work has already been automated, and there are more than 1,500 startups out there trying to streamline the legal world even further. While this wont immediately eliminate all legal jobs, it means that it will take far fewer lawyers -- and especially paralegals --to handle the same level of work.

Because lawyers tend to pay excellent attention to detail, and are highly versed in logic, a good alternative field would be programming. Programming languages are built around logicand require every bit as much attention to detail as any contract. Best of all, there are a ton of courses online that can help you learn, including some from top-tier universities like Stanford, MITand even Harvard.

And of course, programmers are incredibly well paid and in high demand virtually everywhere. Here are a few of the most in-demand programming languages to help you along if you decide to make the switch.

Related: Advancing Automation Means Humans Need to Embrace Lifelong Learning

There have been numerous times throughout history when a large number of old jobs have gone away, only to be replaced by new jobs as new technologies came along. Sometimes the transition from old to new is protracted enough to make a semi-smooth transition possible. That may or may not be the case this time around.

Sam McRoberts is the CEO ofVUDU Marketing, and the author ofScrew the Zoo. He has delved deep into the worlds of philosophy, cognitive psychology and neuroscience to better help his clients achieve their goals. When he isn't...

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Artificial Intelligence Is Likely to Make a Career in Finance, Medicine or Law a Lot Less Lucrative - Entrepreneur

Peter Macdiarmid/Getty Images

Digitizing plant specimens is opening up a whole new world for researchers looking to mine collections from around the world.

Computer algorithms trained on the images of thousands of preserved plants have learned to automatically identify species that have been pressed, dried and mounted on herbarium sheets, researchers report.

The work, published in BMC Evolutionary Biology on 11 August1, is the first attempt to use deep learning an artificial-intelligence technique that teaches neural networks using large, complex data sets to tackle the difficult taxonomic task of identifying species in natural-history collections.

It's unlikely to be the last attempt, says palaeobotanist Peter Wilf of Pennsylvania State University in University Park. This kind of work is the future; this is where were going in natural history.

Natural-history museums around the world are racing to digitize their collections, depositing images of their specimens into open databases that researchers anywhere can rifle through. One data aggregator, the US National Science Foundations iDigBio project, boasts more than 150 million images of plants and animals from collections around the country.

There are roughly 3,000 herbaria in the world, hosting an estimated 350 million specimens only a fraction of which has been digitized. But the swelling data sets, along with advances in computing techniques, enticed computer scientist Erick Mata-Montero of the Costa Rica Institute of Technology in Cartago and botanist Pierre Bonnet of the French Agricultural Research Centre for International Development in Montpellier, to see what they could make of the data.

Bonnet's team had already made progress automating plant identification through the Pl@ntNet project. It has accumulated millions of images of fresh plants typically taken in the field by people using its smartphone app to identify specimens.

Researchers trained similar algorithms on more than 260,000 scans of herbarium sheets, encompassing more than 1,000 species. The computer program eventually identified species with nearly 80% accuracy: the correct answer was within the algorithms top 5 picks 90% of the time. That, says Wilf, probably out-performs a human taxonomist by quite a bit.

Such results often worry botanists, Bonnet says, many of whom already feel that their field is undervalued. People feel this kind of technology could be something that will decrease the value of botanical expertise, he says. But this approach is only possible because it is based on the human expertise. It will never remove the human expertise. People would also still need to verify the results, he adds.

This approach can help herbaria process new samples, simplifying an arduous taks that sometimes requires hours of work. And similar efforts could help with other projects, such as a current crowdsourcing project that asks people to manually tick off which herbarium specimens feature a flower or a fruit. Researchers would certainly welcome an automated way of doing that, says botanist Gil Nelson of Florida State University in Tallahassee and a digitization specialist at iDigBio.

The algorithm could also aid smaller herbaria with their species identifications, Bonnet says. His team found that algorithms trained on large data sets from big herbaria improved the identification of plants from relatively data-poor regions of the world a finding that could be particularly useful for areas that are rich in biodiversity but have smaller plant collections.

And this deep-learning approach will allow researchers to perform additional analyses. Herbaria samples contain a wealth of data: when and where the sample was collected, for example, and characteristics such as whether the plant was flowering or fruiting at collection time and how densely clustered the flowers were. Because some samples are centuries old, that data can paint a portrait of how plants have adapted to shifting climates an area of growing interest in the face of concerns about climate change.

Such efforts, including the identification study, are the next phase of digitization, Nelson says. Weve been trying to transition to methods that we can use to mine those images and to pull out useful data, he says. Thats our focus right now.

The projects aren't limited to herbaria. Nelson points to ongoing efforts to automate the identification of fly larvae, and Wilf is working with collaborators to carry out a similar analysis on plant fossils. Such fossils pose other problems, in part because they come in a variety of forms fossilized fruits and flowers, petrified tree trunks or impressions of leaves in rock. Herbarium sheets, by contrast, are mercifully uniform: flat, dry and typically mounted on a standardized size of paper.

Still, Wilf has no doubt that the field will eventually work out these details. Its just going to get better, he says. Someday well have students who wont be able to remember when we didnt have these sorts of tools.

The rest is here:

Artificial intelligence identifies plant species for science - Nature.com

In BriefGoogle's DeepMind Labs has partnered with BlizzardEntertainment to release an application program interface thatenables artificial intelligence researchers to develop their own AIagents for playing StarCraft II. The hope is that the release willspur innovation in deep reinforcement learning and related areas ofAI research. Glorious Combat Is Upon Us

Last year, Googles DeepMind announced a partnership with Blizzard Entertainment to develop and test artificial intelligence (AI) agents in the popular real-time strategy game StarCraft II. Now, DeepMind has released a series of tools theyre calling StarCraft II Learning Environment (SC2LE)to test their agents against human competitors, as well as enable researchers to develop their own agents for the game.

Testing our agents in games that are not specifically designed for AI research, and where humans play well, is crucial to benchmark agent performance, DeepMinds team wrote in a blog post. The large pool of online StarCraft II players will provide a huge variety of extremely talented opponents from which the AI can learn.

Details of DeepMinds research werepublished in a paperalongside the released toolset, which includes a machine learning API; a dataset of game replays; an open source version ofPySC2, the Python component SC2LE;and more.

Artificially intelligent systems have already beaten humans in a number of games, including chess and some Atari games, and DeepMind has already succeeded at creating an AI that could dominate humans in the ancient Chinese game of Go.

However, StarCraft II presents a different challenge. The game is designed to be won by a single player who must successfully navigatean extremely challenging environment. AI agents have to be capable of managing sub-goals gathering resources, building structures, remembering locations on a partially revealed map, etc. in pursuit of a win, and when combined, these various tasks challenge its memory and ability to plan.

DeepMinds initial StarCraft II tests with AI agents showed that they can manage mini-games that focus on broken-down tasks, but when it came to the full game, the agents werent so successful. Even strong baseline agents [] cannot win a single game against even the easiest built-in AI, according to DeepMinds blog. If they are to be competitive, we will need further breakthroughs in deep [reinforcement learning] and related areas.

The release of the SC2LE toolset is DeepMinds way of asking the AI community for additional help in this endeavor. Our hope is that the release of these new tools will build on the work that the AI community has already done in StarCraft, encouraging more DeepRL research and making it easier for researchers to focus on the frontiers of our field, according to the blog post.

Of course, training AI agents to excel atStarCraft II isnt done just for glorys sake. The idea is that an AI will be more capable of managing real-world tasks if it can successfully navigate a gaming environmentthat requires it to perform layers of computation while engaging a human agent. In that respect, todays expert StarCraft II agent could be tomorrows AIcashierorcustomer service rep.

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DeepMind is Teaching AIs How to Manage Real-World Tasks Through Gaming - Futurism

Not much about Makoto Koikes adult life suggests that he would be a farmer. Trained as an engineer, he spent most of his career in a busy urban section of Aichi Prefecture, Japan, near the headquarters of the Toyota Motor Corporation, writing software to control cars. Koikes longtime hobby is tinkering with electronic kits and machines; he is not naturally an outdoorsy type. Yet, in 2014, at the age of thirty-three, he left his job and city life to move to his parents cucumber farm, in the greener prefecture of Shizuoka. I thought I was getting old, Koike told me. I wanted to be close to my home and my family.

The Koikes have been growing cucumbers in Kosai, a town wedged between the Pacific Ocean and the brackish Lake Hamana, for nearly fifty years. Their crop, which fills three small greenhouses, grows year-round. Koikes father, Harumi, plants the seeds; Koike oversees their cultivation; and his mother, Masako, sorts the harvest. This last job is particularly important in Japan, which is famously discerning about its produce. Nice strawberries can fetch several dollars apiece in some markets, and a sublime cubic watermelon can go for hundreds. Vegetables hold a less privileged place than fruits, but supermarkets rarely stock produce that is at all irregular in shape or size. The Koikes send their better cucumbers, the ones that are straight and uniform in thickness, to wholesalers. The not-so-perfect ones go to local stands, where they are sold at half price. (They taste the same, Koike said.) Masako judges the vegetables one by one, separating them into bins. Though she devotes only half a second to each cucumber, the task takes up most of her work time; on some days, she goes through around four thousand of them.

The laborious process of categorizing the cucumbers had remained essentially the same for decades, until last spring, when Koike began developing a new approach. It was inspired, in part, by articles he read about AlphaGo , the first computer program ever to beat a human master of the game of Go. Developed by Google DeepMind , the program relied on deep learning, a method for making computations by arranging basic processing units into complex, layered networks, rather like the way that billions of neurons work together to produce the incomparable (for now) intelligence of the human brain. In the past several years, deep learning has proved exceptionally useful for finding patterns in big piles of data; it has been incorporated into Facebooks facial-recognition algorithms, Amazon Alexas language processing , and autonomous cars navigation systems. In AlphaGos case, the program was fed thirty million images of positions from real games, which it used to help determine which kinds of moves work best. Koike hoped that a similar strategy might help him sort his familys cucumbers.

Makoto Koike with his parents, Harumi and Masako, at the familys cucumber farm, in Shizuoka Prefecture, Japan. The Koikes have been growing cucumbers for nearly fifty years.

Advanced A.I. techniques, including deep learning, have traditionally been the province of specialized researchers and moneyed software companies. Recently, though, some of the tech worlds biggest playersincluding Google, Facebook, Microsoft, Amazon, Yahoo, Baidu, Yandex, and various universitieshave released free, open-source versions of their tools, making A.I. accessible to small-time programmers who arent well-versed in the field, such as Koike. For his project, he used TensorFlow, which Google released to the public in 2015. He began by building a custom photo stand, which allowed him to photograph each cucumber from three angles. Then, to analyze the images, he adapted a popular piece of TensorFlow software used for recognizing handwritten numerals. Before he could turn the A.I. loose, though, Koike had to train it. He captured seven thousand photos of cucumbers that his mother had already sorted, then used the data to teach his software to recognize which vegetables belonged in which categories. Finally, he built an automated conveyor-belt system to move each cucumber from the photo stand to the bin designated by the program.

Koike completed his machine last year, and it worksto some degree. It sorts cucumbers with an accuracy of seventy per cent, which is low enough that they must subsequently be checked by hand. Whats more, the vegetables still need to be placed on the photo stand one by one. Koikes mother, in other words, is in no immediate danger of being replaced, and thus far, she and her husband are none too impressed. They are quite severe, Koike said. Oh, its not useful yet, they tell him. Tech enthusiasts, meanwhile, have had decidedly more positive reactions, and Koike has been invited to events such as the Maker Faire, in Tokyo, and the CeBIT expo, in Hanover, Germany. There are machines that work better and faster than Koikes, but they are industrial-sized and -priced affairs. Before the democratization of deep learning, it would have been difficult for someone like him to design such an effective device himself.

Koike sees his system as an encouraging proof of concept, and he is currently at work on a new version, which he hopes will be capable of analyzing more than one cucumber at a time. He also plans to build a gentler conveyor system, to preserve the fragile prickles on the vegetables skin, which are considered a sign of freshness. He expects that, within a few years, his A.I. sorter will be nearly as accurate as his mother, freeing her up to do something else. Either way, he told me, he is back in Kosai for the long haul. Thats the plan, he said. Ill probably die as a farmer. By the time that happens, the work may look very different.

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DIY Artificial Intelligence Comes to a Japanese Family Farm - The New Yorker

Friendly or or a Dalek plot? Random Internationals Zoological, part of Wayne McGregors +/- Human Photograph: Ravi Deepres/Alicia Clarke

In Ren Magrittes surrealist painting La Voix des Airs (1931), three inscrutable spheres hover in an empty blue sky above green fields. Ive always wondered what these enigmatic objects really are. Do they come from outer space? Are they about to open and unleash a robot army? What strange message do they bring from their impersonal dimension?

At last I know, because I have met them. I have even danced with them. In the darkened heights of the Roundhouse in north London, a flying flock of white spheres that uncannily resemble Magrittes dream objects float intelligently and curiously, checking out the humans below, hovering downward to see us better. They are the most convincing embodiment of artificial intelligence I have ever seen. For these responsive, even sensitive machines truly create a sense of encounter with a digital life form that mirrors, or mocks, human free will.

They are the most convincing embodiment of artificial intelligence I have ever seen

Nobody is hidden behind a screen piloting this robotic airborne dance troupe. Each sphere has its own decision-making electronic brain. They fly in elegant unison yet also break ranks as they check their positions against the images recorded by infra-red cameras surrounding the circular space where they float and their human visitors walk. It is fitting to experience this eerily beautiful vision of the future in the steampunk setting of a Victorian railway building whose architectural grandeur evokes the first industrial revolution. It can feel like a Doctor Who episode come to life. What are those flying spheres, Doctor are they friendly or is this a Dalek plot?

Random International, the creators of this post-human visitation, have form in boggling minds. People queued for as long as four hours to get into their interactive installation the Rain Room at the Barbican in 2012. This deserves to be as popular and is arguably a lot more thought-provoking. Working with choreographer Wayne McGregor, whose dancers will perform with the ascendant orbs at weekends, these technologically adept art wizards extend the technology of drones to genuinely and movingly ponder the nature of life itself.

Looked at coldly, these devices are just inflated plastic balls whose movements are guided by rotors, like a toy drone. Yet the crucial fact that they guide themselves, mimicking conscious choice in their unplanned and to all intents and purposes spontaneous actions, is apparent without knowing anything about their design. You can tell by the way they move that they are free entities. Their behaviour is by turns entrancing and mildly menacing. They rise one after another from their resting positions in an upper gallery and calmly hover out into the open domed arena where their human guests are waiting. They are never at rest. As they glide in formation one or another is always changing its position, approaching the people below with what seems like curiosity. Then they all follow. It is when the entire swarm gathers directly above you that it suddenly becomes a threatening, sinister presence.

Surely science could learn a lot from this advanced work of art. McGregors understanding of dance is clearly as crucial as Random Internationals engineering ingenuity in creating what amounts to a fascinating illusion of life. Experiments in robotics often produce disturbing doll-faced machines and stilted conversationalist computers. Yet the true secret of copying life, this installation shows, lies in movement. Dance, the oldest human art, turns out to be a key to comprehending life itself, and reproducing it. The orbs dance with you. They locate and follow members of the audience, not with mechanical inevitability but a complex, gracious harmony. Making and breaking patterns, coming together and loosely floating apart, they dance with each other, too.

This artwork that opens visions of a future in which life evolves beyond biology itself.

Its alive! Its alive!, as Frankenstein would say. Ever since Mary Shelley wrote that novel in 1818, the fantasy of creating life, whether by re-animating dead flesh like her overweening scientist or, now, by building robots, has tended to fixate on the human form. We assume robots will walk and talk like us. This installation demonstrates how very different a future of digital intelligence may look. Far from resembling the human, these entities are completely alien. They have no faces, voices or limbs. They do have openings underneath through which their machinery can be glimpsed. Marcel Duchamp as well as Magritte would recognise their post-human grace. In his masterpiece The Bride Stripped Bare by Her Bachelors, Even, left unfinished in 1923, a large panel of glass carries images of a floating mechanical bride and chocolate-grinding male admirers. Duchamp imagined a future where the organic and inorganic are one. He would be entranced by this artwork that opens visions of a future in which life evolves beyond biology itself. When our robot great-grandchildren drift in great electronic herds to the stars, this is what it may look like. That wont be such a bad legacy for us to leave.

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+/- Human review Is this the future of artificial intelligence? Bring it on - The Guardian

I am non-technical by education, but my passion revolves only around technology, and specifically to Artificial Intelligence. Yeah, it sounds more like relating yourself to Steven Spielberg Sci-Fi, wherein everything could be controlled with just a tap or the retina identification, although most of these aspects discussed in the movie are quite possible now, just due to the invasion of Artificial Intelligence in our lives.

What Is AI- Artificial Intelligence

As a layman, it is hard to understand the real mechanism of AI since it would be a glut of high technical language, which may bounce back, so in a plain language, AI stands for that idea, where certain machines are developed in a way that they can think like humans. Just to illustrate further Siri in your iPhone to those self-driving cars, all are the products of Artificial Intelligence. Lets take a look at some of the facts related to AI Taking Care of Daily Chores

We all have to perform certain tasks in our daily routine, which are too obvious but needs to be accomplished daily in personal and professional lives. Such mundane tasks can easily be performed through AI and it increases the chances of enhanced productivity rate of humans.

No Ground For Errors

When I talk about errors then, I simply get a very particular aspect in my mind that is Human Error, which at times, devastates the end result brutally. But AI integrated devices never make mistakes and is programmed in such way that leaves no scope for errors, regardless of the data size.

Saving Humans To Take risks

Curiosity is a part of human nature and to satiate it further, we risk our lives, for instance, the space exploration has always been on the top list of man curiosity chart, but the number of risks involved in it makes it dangerous enough. But this exploration is very much possible with the AI support, which can travel across the landscape of space, exploring it and determining the best paths to take. This indeed is a great step to discover the potential benefits for human civilization.

Virtual Reality For Education

The AI is beneficial for several business domains, and the education industry would take the maximum benefits out of it through the integration of VR assisted learning. This type of learning would open the doors for the students and they can learn and explore the topics more deeply.

AI Is A Blessing For Health Care Industry

AI in healthcare and the medical field is creating a sensation by organizing the better treatment plans for patients and help the medical experts to make the best-suited decision for the patients.

These are some of the benefits Artificial Intelligence is offering to the society, and these numbers of benefits are going to rise exponentially with the demand and future inventions in the near future, although many people argue that AI would consume the jobs of people, but this is not correct, since AI has its own limitations, which can never replace the humans.

On the other hand, if you are looking for a mobile app for your business, you must reach Techugo- a top mobile app development company, wherein we work on different ideology of honesty woven in our work process, and unlike our competitors, we believe in crafting the success journey for our clients and impeccable app experience for their end-users. At Techugo, we take pride in developing the mobile apps for the leading brands to startups and our mobile app development team has the expertise to create a unique variety of mobile app solution for your business needs, which would help you to showcase your idea, goal, and dream in the most informative and engaging way.

Our team of top mobile app designers is here to help assist you with every step of your mobile app development strategy. We love to create the successful mobile apps for your business, which can help you to climb the success ladder further, we consult, brainstorm, manage the project, design, develop, test, launch, and market apps in the best possible way. You can get in touch with our team to discuss further your concept to bring into reality. The discussion would help you to gain a better insight of your app requirement.

AnkitSingh

Techugo Pvt. Ltd.

In his role of Business Head, Ankit offers a helping hand to those, who are looking to build apps. He dedicates his passion in committing the vision of clients and goal of the project simultaneously and he loves to share his writing skills through blog and article writing.

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Facts Related To Artificial Intelligence - Customer Think

Brandon Wirtz was supposed to be a fifth-generation teacher. Indeed, the founder and CEO of artificial intelligence engine developer Recognant is a teacher -- of robots, not people -- and not the factory floor variety of bots, either. Instead, Wirtz sees AI changing a very human process: human resources.

To reach the place where artificial intelligence and HR meet, Wirtz spends his days educating his various AIs about everything from how to order pizza to what an appropriate pickup line might be. His bots -- "Loki," "Lobby" and "Molly" -- are at different stages of independence and aptitude. Loki, who identifies as female, is perhaps Wirtz's favorite bot -- and the most likely to drive him crazy with questions.

The games Wirtz plays with Loki -- "I Spy" is a particular favorite -- might seem frivolous, but they serve as the basis for the bot's education in how humans think and communicate. And though it may seem unimportant that Loki understands Santa Claus, zombies and Instagram, all of that matters when it comes to artificial intelligence and human resources if she -- or a bot like her -- is going to work in HR dealing with prospective employees. "I know this seems creepy, but it isn't," Wirtz laughed.

In his world view, Wirtz believes HR is largely broken and AI is going to fix it. "One of the biggest problems in HR is that you have an interviewer, and they know nothing about the particular job they're hiring for," he explained. "Lots of times, an HR person is faking knowledge about the job, so they don't know enough to know what keywords to be listening for."

An AI is not very good at making jokes, but it can tell when a human has made a joke, and that can help [the bot] decide whether someone has the right personality for the job.

Even if a bot has never heard of, say, Photoshop, it can quickly search the internet and arm itself with enough information to know if an applicant using Corel Draw may lack the necessary experience, Wirtz said. "The AI doesn't have to understand the conversation but can pass the transcription on to the hiring manager and indicate this was not an acceptable answer," he added. "AI is a way to get deeper interactions with interviewees, and it doesn't matter what they talk about because the AI is an expert or at least a jack-of-all-trades."

A robot might have a more in-depth interview with a job applicant, while showing no bias toward the candidate, Wirtz reasoned. "Sometimes it comes down to 'This candidate reminds me of someone I didn't like in high school,' or 'This person and I have bonded over the same hobby,'" he suggested. "Computers don't have these biases." However, they can be programmed to search for applicant biases, such as racially derogative messages posted on social media. And with the right training, a bot can even help sort out the very subtle human characteristics like emotional intelligence, sense of humor and even ambition, Wirtz said. "An AI is not very good at making jokes, but it can tell when a human has made a joke, and that can help [the bot] decide whether someone has the right personality for the job."

If you're dubious about artificial intelligence and human resources, you're far from alone, but Wirtz has an answer for skeptics. "A well-trained AI will listen, and humans really don't," he asserted. "Say you are looking to hire a test engineer. That's a job without a lot of upward mobility. So you want to hire someone who's going to be happy to stay a test engineer. An AI will analyze how many times the person used the future tense and that's key information that a human would more than likely have missed."

Yet that kind of human analysis is only possible when bots are patiently taught by someone who understands the building blocks of AI. Although Wirtz started coding at the age of 7, he took a hiatus from that for several years to be a YMCA camp counselor before returning to software development. He worked on mind simulation products, which provided key training in psychology and understanding how the human brain works. He then moved on to AI-based content creators.

"I was trying to 'game' Google and create content for fun and profit that wasn't great but didn't suck, either," he acknowledged. "So I learned about content creation, fact extraction and knowledge building." Those were the tools that formed the basis for Loki and her AI colleagues at Recognant and what Wirtz hopes will foster a new approach to artificial intelligence and human resources.

Thanks to AI, applying blindly for a job will become a thing of the past, Wirtz predicted. Instead, a chatbot will appear right after the application is submitted online and strike up a conversation with the applicant. That prescreening exchange will provide the hiring manager with immediate information about the applicant; the applicant may receive feedback from the hiring manager as well.

"From spelling errors to subject knowledge to attitude, an AI can ask and record this exchange," Wirtz said. "If this works, we can get rid of the biases, the emphasis on education instead of experience and a lot more unknowns. And it really is starting to happen today."

Does AI really have a role in business?

Do you need HR management software?

A primer on AI in HR

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When artificial intelligence and human resources intersect - TechTarget

Posted August 10, 2017 07:02:33

In the argument between Mark Zuckerberg and Elon Musk, it's hard to know which side to join. Both of them are right. Or, if you like, both of them are wrong.

Musk is wrong to worry about artificial intelligence (AI) being a threat to humanity, so I agree with Zuckerberg. And Zuckerberg is wrong to dismiss all concerns about AI, so I agree with Musk. But neither of them are worrying about the right things.

AI is transforming almost every aspect of our lives, from the workspace to the political arena. You can't open a newspaper today without reading a story about some impressive advance in AI.

Are machines taking over people's jobs? Are algorithms having an impact on political debate? Will robots transform warfare? Are we sleepwalking into some dystopian future?

First, let's put to rest Elon Musk's worry. The machines aren't about to take over the world anytime soon. Those of us working on building intelligent machines appreciate how much of a challenge remains. We're not going to wake up anytime soon and discover the machines are in charge.

Most of my colleagues working in AI estimate it is at least 50 years before we can build machines as smart as humans. And when we do, it's not inevitable they'll be able to make themselves even smarter still.

So, there is plenty of time to ensure the machines are working in our best interests. And there's a healthy community of researchers working on the topic of "AI safety" to ensure that outcome.

But that doesn't mean we can simply put our feet up and wait for the bright future. There's a lot to worry about. Some AI is smart, some is stupid. We're starting to give responsibility to algorithms that aren't actually very intelligent.

Joshua Brown discovered this to his cost in May last year. He was immortalised as the first person killed by their autonomous car. His Tesla was driving down the highway in "autopilot mode" when it hit a truck turning across the road. Mr Brown had too much faith in the technology.

Another worry is the impact AI is having on political discourse. When millions of Donald Trump's Twitter followers are robots, you have to worry if human voices are being drowned out by computers. If the news you see on Facebook is decided by algorithms, who decides on the biases in these algorithms?

A third worry is the impact AI will have on the workforce. There's no fundamental law of economics that requires new technologies to create more jobs than they destroy, which has been the case so far. There are more people working today than ever, and unemployment is at historically low levels.

But this time could be different. In the Industrial Revolution, machines took over much manual labour but left us with many cognitive tasks. In the AI revolution, machines will take over many of these cognitive tasks. What is left for us?

The Industrial Revolution offers us a good historical precedent for dealing with change like this. Before the industrial revolution, many people worked out in the fields. After the Industrial Revolution, machines took over many of these jobs. And new jobs were created in offices and factories.

But we needed to make some significant changes to society to deal with this transition.

We invented universal education so people were educated for these new jobs. We invented labour laws and unions so the owners of the production didn't exploit their workers. We invented a welfare state and pensions so all of us shared the increased wealth. We made some deep, structural changes to society so everyone shared the benefits of increasing productivity.

These changes didn't happen overnight. Indeed, there were 50 years or so of pain before many workers saw their quality of life lift above what is was before the Industrial Revolution.

This then is the challenge we face today except the AI revolution will likely happen even faster than the Industrial Revolution. For this reason, we need more regulation.

Many tech companies like Facebook and Google are driven by opaque algorithms and are increasingly impacting on our lives in undesirable ways.

Facebook is now the largest news organisation on the planet, yet it doesn't have the same responsibilities as the traditional press.

Google is starting to know too much about our lives, and will need to be broken into parts to prevent it becoming a monopoly. Actually, by creating the holding company Alphabet, Larry Page and Sergey Brin have made the regulators' job much easier.

And it's hard to know where to begin with Uber, one of the most badly behaved of them all.

If Google or other companies won't pay taxes, then more countries besides Australia and the UK need to make a Google tax to force them to do so.

Silicon Valley can't wash its hands of the responsibility that comes with immense reach.

For too long, we (and our governments) have been seduced by the promises spun by technologists.

AI is one of the few hopes for tackling many of the problems that challenge us today like climate change and the ongoing global financial crisis.

But with immense power comes responsibility.

Toby Walsh is the Scientia Professor of AI at the University of New South Wales and the author of It's Alive!: Artificial Intelligence from the Logic Piano to Killer Robots.

Topics: robots-and-artificial-intelligence, science-and-technology, australia

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The artificial intelligence revolution is coming and right now, Silicon Valley holds the power - ABC Online

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Many people wonder why Europe is so keen to protect peoples privacy. The reason dates back from WWII, when French and German governments used centralized citizen files to target, and subsequently deport, Jews and other ethnic minorities. Following this, the Universal Declaration of Human Rights included an entire article about the right to privacy, which gave birth to many laws in European countries. The demand for uniform privacy regulations across the continent leads us to the European General Data Protection Regulation (GDPR), which will take effect in May 2018.

Related: FBI: Your Kids' Internet Connected Toys Might Be Spying on Them

In a nutshell, the GDPR forces companies offering a product or service to a European citizen to follow Privacy by Design principles. It doesnt matter where in the world they are headquartered; if they want to do business in Europe, they will need to comply. The penalty for failing to do so is up to 4 percentof global turnover, which could amount to billions of dollars for large companies. This is why over 93 percentof US companies made this their top legal priority in 2017.

Although the GDPR applies to any use of personal data (defined as data that can identify someone directly or indirectly), it poses major challenges to artificial intelligence in particular, as machine learning algorithms often rely on user data to learn to do things.

In the GDPR there are four principles that makes it virtually impossible to do AI as commonly practiced:

Companies will now have to ask for consent in simple terms, rather than buried in legalese terms and conditions. This creates many challenges, in particular for cloud-based voice assistants. Voice is considered to be personal data, therefore devices that listen ambiently should in theory ask everyone in the room for consent before sending their voice to the cloud. Imagine the nightmare of having 10 people over for dinner, and having your Google Home device asking each of them for consent! One way to solve this is to process the user voice directly on the device instead of sending it to the cloud, therefore avoiding the need for explicit consent.

Related: These Companies Are 'Falling Short' on User Privacy

This means that anyone can ask for their personal data to be completely deleted. While this may be easy for a user account in a database, what happens when the data was used to train a machine learning algorithm? One might argue that the user data is still present in the form of outlier nodes in the neural network, and thus that they havent been forgotten.The easiest way to solve this would be to retrain the models without the user data, which is a quite costly process. A better approach would be to find algorithms that can unlearn specific inputs without retraining over the entire dataset.

Related: 3 Reasones Why Privacy Matters to Your Business, Your Brand and Your Future

I love this one because it means European residents will be able to access all the data a company has about them, and transfer it to another provider. The regulation states that the data subject can ask for her personal data to be transferred directly to a new provider, without hindrance, and in a machine readable format. Just like you can switch mobile providers while keeping your phone number, you will be able to switch social networks or search engines without any loss of data. This breaks the personal data lock-in that many services are using to keep us captive. It also opens the door to a massive data exodus when companies mess up: They would lose their data and hence their ability to train their AIs, while new providers would gain more data and thus improve their own AIs. In effect, it would speed up the demise of bad companies by creating an exponentially increasing gap when people switch over.

Related: Beyond the Privacy Fine Print: Making Privacy More Transparent

This one is particularly tricky, as it states that European residents have a right to explanation when an automated decision was made about them. The logic behind it is to avoid discrimination and implicit bias by enabling people to go to court if they feel unfairly treated. But, this would also effectively prohibit the use of deep learning, since it is currently a black box. Many researchers are working on explaining how neural networks make decisions, as this will be a requirement before we can hope for AI to enter areas such as medicine or law.

While the above regulations certainly introduce some new problems for those working in AI, the GDPR also creates a lot of opportunity -- by giving people control over their data, while breaking digital monopolies that prevent innovation beyond incumbent companies.

More than just ethically beneficial for Europe, the GDPR is also a way to reclaim digital territory, and make companies all around the world start respecting a fundamental human right that they have been ignoring for 70 years: privacy.

Rand Hindi is the founder and CEO of Snips, one of the first AI voice platforms for connected devices that offers privacy by design. Hindi was named a TR35 by MIT Technology Review, a Forbes "30 under 30" and is member of the Fren...

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Will Artificial Intelligence Be Illegal in Europe Next Year? - Entrepreneur

Unlike the Industrial Revolution and the computer revolution, the A.I. revolution is not taking certain jobs (artisans, personal assistants who use paper and typewriters) and replacing them with other jobs (assembly-line workers, personal assistants conversant with computers). Instead, it is poised to bring about a wide-scale decimation of jobs mostly lower-paying jobs, but some higher-paying ones, too.

This transformation will result in enormous profits for the companies that develop A.I., as well as for the companies that adopt it. Imagine how much money a company like Uber would make if it used only robot drivers. Imagine the profits if Apple could manufacture its products without human labor. Imagine the gains to a loan company that could issue 30 million loans a year with virtually no human involvement. (As it happens, my venture capital firm has invested in just such a loan company.)

We are thus facing two developments that do not sit easily together: enormous wealth concentrated in relatively few hands and enormous numbers of people out of work. What is to be done?

Part of the answer will involve educating or retraining people in tasks A.I. tools arent good at. Artificial intelligence is poorly suited for jobs involving creativity, planning and cross-domain thinking for example, the work of a trial lawyer. But these skills are typically required by high-paying jobs that may be hard to retrain displaced workers to do. More promising are lower-paying jobs involving the people skills that A.I. lacks: social workers, bartenders, concierges professions requiring nuanced human interaction. But here, too, there is a problem: How many bartenders does a society really need?

The solution to the problem of mass unemployment, I suspect, will involve service jobs of love. These are jobs that A.I. cannot do, that society needs and that give people a sense of purpose. Examples include accompanying an older person to visit a doctor, mentoring at an orphanage and serving as a sponsor at Alcoholics Anonymous or, potentially soon, Virtual Reality Anonymous (for those addicted to their parallel lives in computer-generated simulations). The volunteer service jobs of today, in other words, may turn into the real jobs of the future.

Other volunteer jobs may be higher-paying and professional, such as compassionate medical service providers who serve as the human interface for A.I. programs that diagnose cancer. In all cases, people will be able to choose to work fewer hours than they do now.

Who will pay for these jobs? Here is where the enormous wealth concentrated in relatively few hands comes in. It strikes me as unavoidable that large chunks of the money created by A.I. will have to be transferred to those whose jobs have been displaced. This seems feasible only through Keynesian policies of increased government spending, presumably raised through taxation on wealthy companies.

As for what form that social welfare would take, I would argue for a conditional universal basic income: welfare offered to those who have a financial need, on the condition they either show an effort to receive training that would make them employable or commit to a certain number of hours of service of love voluntarism.

To fund this, tax rates will have to be high. The government will not only have to subsidize most peoples lives and work; it will also have to compensate for the loss of individual tax revenue previously collected from employed individuals.

This leads to the final and perhaps most consequential challenge of A.I. The Keynesian approach I have sketched out may be feasible in the United States and China, which will have enough successful A.I. businesses to fund welfare initiatives via taxes. But what about other countries?

They face two insurmountable problems. First, most of the money being made from artificial intelligence will go to the United States and China. A.I. is an industry in which strength begets strength: The more data you have, the better your product; the better your product, the more data you can collect; the more data you can collect, the more talent you can attract; the more talent you can attract, the better your product. Its a virtuous circle, and the United States and China have already amassed the talent, market share and data to set it in motion.

For example, the Chinese speech-recognition company iFlytek and several Chinese face-recognition companies such as Megvii and SenseTime have become industry leaders, as measured by market capitalization. The United States is spearheading the development of autonomous vehicles, led by companies like Google, Tesla and Uber. As for the consumer internet market, seven American or Chinese companies Google, Facebook, Microsoft, Amazon, Baidu, Alibaba and Tencent are making extensive use of A.I. and expanding operations to other countries, essentially owning those A.I. markets. It seems American businesses will dominate in developed markets and some developing markets, while Chinese companies will win in most developing markets.

The other challenge for many countries that are not China or the United States is that their populations are increasing, especially in the developing world. While a large, growing population can be an economic asset (as in China and India in recent decades), in the age of A.I. it will be an economic liability because it will comprise mostly displaced workers, not productive ones.

So if most countries will not be able to tax ultra-profitable A.I. companies to subsidize their workers, what options will they have? I foresee only one: Unless they wish to plunge their people into poverty, they will be forced to negotiate with whichever country supplies most of their A.I. software China or the United States to essentially become that countrys economic dependent, taking in welfare subsidies in exchange for letting the parent nations A.I. companies continue to profit from the dependent countrys users. Such economic arrangements would reshape todays geopolitical alliances.

One way or another, we are going to have to start thinking about how to minimize the looming A.I.-fueled gap between the haves and the have-nots, both within and between nations. Or to put the matter more optimistically: A.I. is presenting us with an opportunity to rethink economic inequality on a global scale. These challenges are too far-ranging in their effects for any nation to isolate itself from the rest of the world.

Kai-Fu Lee is the chairman and chief executive of Sinovation Ventures, a venture capital firm, and the president of its Artificial Intelligence Institute.

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A version of this op-ed appears in print on June 25, 2017, on Page SR4 of the New York edition with the headline: The Real Threat of Artificial Intelligence.

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The Real Threat of Artificial Intelligence - The New York Times