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Posts Tagged ‘AI’

Different views of AI fuel distrust between China and America

Posted by hkarner - 18. Januar 2020

Date: 16‑01‑2020

Source: The Economist: Chaguan

The two countries talk past each other about its risks

In the depths of the cold war, American and Soviet arms‑control negotiators pulled off something remarkable: an agreement so grimly logical that their mutual distrust did not matter. The superpowers pledged to stop building new systems to defend their respective homelands against nuclear missiles. Their Anti‑Ballistic Missile Treaty rested on a theory of mutual deterrence: the notion that the surest path to nuclear‑armed co‑existence lay in knowing that war would lead to catastrophe for both sides.

Today the rivalry between America and China is sliding into its own ice age of suspicion. Once again, new and unproved technologies—this time computer systems capable of performing superhuman tasks using machine learning and other forms of artificial intelligence (ai)—threaten to destabilise the global “strategic balance”, by seeming to offer ways to launch a knockout blow against a nuclear‑armed adversary, without triggering an all‑out war.

A report issued in November by America’s National Security Commission on Artificial Intelligence, a body created by Congress and chaired by Eric Schmidt, a former boss of Google, and Robert Work, who was deputy defence secretary from 2014‑17, ponders how ai systems may reshape global balances of power, as dramatically as electricity changed warfare and society in the 19th century. Notably, it focuses on the ability of ai to “find the needle in the haystack”, by spotting patterns and anomalies in vast pools of data. In a medical setting ai can find tumours that radiologists miss. In a military context, it may one day find the stealthiest nuclear‑armed submarines, wherever they lurk. The commission is blunt. Nuclear deterrence could be undermined if ai‑equipped systems succeed in tracking and targeting previously invulnerable military assets. That in turn could increase incentives for states, in a crisis, to launch a devastating pre‑emptive strike. China’s rise as an ai power represents the most complex strategic challenge that America faces, the commission adds, because the two rivals’ tech sectors are so entangled by commercial, academic and investment ties. Den Rest des Beitrags lesen »

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It’s a war between technology and a donkey‘ – how AI is shaking up Hollywood

Posted by hkarner - 17. Januar 2020

Date: 16‑01‑2020

Source: The Guardian Steve Rose

Subject: ‚It’s a war between technology and a donkey‘ – how AI is shaking up Hollywood

The film business used to run on hunches. Now, data analytics is far more effective than humans at predicting hits and eliminating flops. Is this a brave new world – or the death knell of creativity?

Cinelytics claims its AI, used by Warner Bros, can forecast box office results with 85% accuracy.

If Sunspring is anything to go by, artificial intelligence in film‑making has some way to go. This short film, made as an entry to Sci‑Fi London’s 48‑hour film‑making competition in 2016, was written entirely by an AI. The director, Oscar Sharp, fed a few hundred sci‑fi screenplays into a long short‑term memory recurrent neural network (the type of software behind predictive text in a smartphone), then told it to write its own. The result was almost, but not quite, incoherent nonsense, riddled with cryptic nonsequiturs, bizarre turns of phrase and unfathomable stage directions such as “he is standing in the stars and sitting on the floor”. All of which Sharp and his actors filmed with sincere commitment.

“In a future with mass unemployment, young people are forced to sell blood,” says a man in a shiny gold jacket. “You should see the boy and shut up. I was the one who was going to be a hundred years old,” replies a woman fiddling with some electronics. The man vomits up an eyeball. A second man says: “Well, I have to go to the skull.” And so forth. An unwitting viewer might be unsure whether they were watching meaningless nonsense or a lost Tarkovsky script.


This isn’t how artificial intelligence is changing the movies – yet. But AI is changing the industry in other ways, to a greater extent than is being admitted. In early January, Warner Bros broke cover and announced it had signed up to an AI‑driven project management system that would “inform decision‑making around content and talent valuation to support release strategies”. In other words, Warners will be using AI to help it decide what movies to make.

The system in question was launched last year by Cinelytic, a Los Angeles‑based startup. Other clients listed on its website include Sony Pictures, Ingenious Media and STX Entertainment (the studio behind Hustlers and Playmobil: The Movie). Meanwhile, 20th Century Fox has partnered with Google to develop its own AI, named Merlin, which predicts audiences based on analysis of patterns and objects in movie trailers. Other new companies have also entered the AI game in the past few years, including Belgium‑based ScriptBook and Israel’s Vault AI.

You can see the appeal, especially for a studio like Warner Bros. As well as putting out hits such as Joker and A Star Is Born, it has had its share of box‑office flops, such as King Arthur: Legend of the Sword, The Kitchen, Shaft and The Goldfinch. These projects must have looked like hits on paper. How to tell the difference? Traditionally, Hollywood almost prides itself on its own unpredictability, accepting as a given William Goldman’s adage “no one knows anything”. It is an industry that carries out extensive analysis, research and audience testing, but that still relies to a large extent on human intuition and gut instinct. It is also an industry where the majority of films made are never released, and less than half of those that are make their money back.

Can the machines do better? Absolutely, says Cinelytic, which claims an accuracy of 85% in its box office forecasting. Cinelytic was founded in 2015 by Tobias Queisser, whose background is in finance and film producing. His co‑founder, Dev Sen, is a rocket scientist who developed risk assessment software for Nasa. Cinelytic claims to have crunched data from more than 95,000 movies and 500,000 actors and professionals, but its chief selling point is that it can make forecasts in real time – expressed as percentage probabilities of certain levels of success. With its user‑friendly interface, clients can play with the variables and assess the impact on box office right away.

Let’s make an action comedy starring Dwayne Johnson, say. It will be huge! But what if Johnson is not available? How would it look if you cast Gerard Butler instead? Not so huge, perhaps, but the budget might also be lower. How would it do if you released it over 1,000 screens, or 3,000? How would it do in Brazil or China? In effect, Cinelytic’s AI treats the movie industry like fantasy football, assigning quantitative scores to individuals, according to factors such as recent or past box‑office performance or social media profile.

Others take a slightly different approach. ScriptBook’s AI primarily analyses scripts, as opposed to actors or directors. “Most people believe that cast is everything, but we’ve learned that the story has the highest predictive value,” says Nadira Azermai, who founded the company in 2015. It doesn’t take a computer‑sized brain to think of a movie that had a stellar cast but still flopped. But a good story will succeed even without stars – and potentially more so with them, she says.

Within six minutes, ScriptBook’s AI reads a script and assigns it more than 400 parameters. “Anything that is information: emotion analysis, the journey for the protagonist and antagonist, whether the film will cater to a wide audience or niche audience, whether it follows a traditional three‑act structure, whether the action happens in the most important places.” As more information becomes available, such as the cast, the prediction becomes more accurate, but if the computer says no to begin with, no additional information will change it to a yes.

ScriptBook’s success rates are comparable to those of Cinelytic: 83% to 86%, Azermai claims, whereas human decision‑making is successful 27% to 31% of the time. In a retroactive study of Sony’s output between 2015 and 2017, for example, it successfully identified 22 out of its 32 releases that lost money. It could have saved the company a fortune. It has achieved similar levels of accuracy with movies before they were released, even predicting the success of unconventional outliers such as Get Out, La La Land and A Quiet Place. Azermai is not yet at liberty to reveal which companies ScriptBook has been working with, but she applauds Warners’ announcement that it is working with Cinelytic. “It is an important message, because the majority of companies are still treating AI as a dirty little secret.”

One of the factors driving the AI revolution is undoubtedly Netflix, which, by its spectacular ascent over the past decade, has awakened the entertainment industry to the awesome power of data. Netflix has valued its “recommendations” algorithms (which suggest to viewers what to watch next) at $1bn (£760m) a year in terms of keeping subscribers engaged. The company is notoriously secretive about its methods, but it is safe to assume it is tracking viewers’ every move: what they watch, how long they watch it, what time of day it is, what they watch next, how many hits a new show receives in its first day, and so on. Because Netflix also streams other people’s content, it is even better informed when it comes to producing its own. The studio’s staggering output (Netflix put out 700 original TV shows and 80 features in 2018) would not be possible without AI assistance. As a result of Netflix’s success, tech companies such as Apple and Amazon are getting into content creation and giving the old‑school studios a run for their money.

“All of a sudden you have this conservative, traditional industry versus companies who are believers in data,” says Azermai. “There is a war on content, but one party is using the latest technology and the other is riding a donkey.”

The AI revolution will clearly benefit film‑makers, but what is in it for us viewers? One potential drawback is that AI eliminates not only financial risk but creative risk, too. The fear is, if you fed in a vaguely challenging or experimental or atypical project into the machine – say Mulholland Drive or Under the Skin – the algorithm would discourage you from taking the gamble. Why not do a Dwayne Johnson action comedy instead?

Added to which, the data these algorithms are processing are actually human beings, who are inherently erratic, fallible and unpredictable. Your asset might go into rehab, get divorced or decide to go off and make shoes for a year. In 1996 Robert Downey Jr was arrested driving his Porsche naked through Los Angeles throwing imaginary rats out of the window. What algorithm would have recommended casting him as Iron Man?

“Already we’re seeing that we’re getting more and more remakes and sequels because that’s safe, rather than something that’s out of the box,” says Tabitha Goldstaub, a tech entrepreneur and commentator who specialises in artificial intelligence. Her work has raised deeper concerns about AI. Far from being a dispassionate tool, it often reflects the biases and prejudices of its creators, she says. “A lot of people think it’s maths so it can’t be biased, whereas in fact it’s completely the opposite way around: it’s maths, and therefore it’s data, and whatever data you feed a machine will have bias in it. The world is biased, and so these machines exacerbate our own biases.”

She points to the fact that no women have been nominated for best director at this year’s Oscars, and only five women have ever been nominated. The AI might well conclude that if you want to make an Oscar‑winning movie, don’t hire a female director. “You can’t help but think: do you really want to leave these people in charge of creating an algorithm that predicts the next hits? It’s quite scary.”

But there are signs that AI could help reduce bias. The producer Todd Garner cited an example on his Producer’s Guide podcast recently. Garner’s company produced the Marlon Wayans comedies White Chicks and Little Man, and did very well out of them. But when it took a new Wayans project to traditional studios and financiers, nobody bit, he says. “Because there was no way, they thought, that this movie would play internationally … so it’s a purely domestic play [a US‑only release]. Netflix came in and scooped it up immediately, gave us a lot more money to make the movie and the movie was huge for their site. Because Netflix had hosted White Chicks and other Wayans movies on their site, they knew that Marlon Wayans has a worldwide audience. If you don’t have that data, your instinct is, well, African American movies don’t play overseas, period.”

Now that AI is here, there is also the question of how much further it will infiltrate film‑making. Screenwriting, for example. Things have moved on since Sunspring in 2016. Last year, Kevin Macdonald directed a one‑minute advert for Lexus entirely written by an AI – that had been trained on 15 years’ worth of luxury ads.


As well as analytical tools, ScriptBook is developing a screenwriting AI, which it has given the dystopian sci‑fi thriller name of Deepstory. “It really is a co‑creator,” says Azermai, reassuringly. “We envision a next‑generation writers’ room where whenever they don’t know where to head to for the next scene, they would have Deepstory create it. The engine takes into account everything that you’ve written, and it will deliver you the next scene, or the next 10 pages, or write it to the end.” Azermai admits Deepstory still has much to learn. “The consistency in writing stays for another 10 pages and then the AI becomes a bit crazy – sometimes it kills the protagonist for some reason – but it’s improving. Within five years we’ll have scripts written by AI that you would think are better than human writing.”

The movies themselves have trained us to be suspicious of AIs. They make terrible substitute children (Spielberg’s AI), and even worse romantic partners (Spike Jonze’s Her). They often decide humans are expendable and take over (Kubrick’s 2001) or they enslave us in some futuristic dystopia (Terminator, The Matrix). Could it be that by embracing AI, Hollywood is unwittingly building an equivalent of the Terminator movies’ Skynet? Or, in a slightly less apocalyptic scenario, are we looking at a future where movies are personally tailored to individual viewers? Might we be approaching a sort of Turing test for machine‑written fiction? Maybe we have passed it already and we just don’t know it yet. Sounds like a plot for a great, metatextual Hollywood conspiracy thriller. If we got Dwayne Johnson it could be a smash. Let’s crunch some numbers!


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Posted by hkarner - 9. Januar 2020

Date: 08‑01‑2020

Source: The Wall Street Journal

Recruiters using AI and virtual‑reality simulations may hire based on a candidate’s behavior, personality traits and physiological responses—no resumes needed

Most job hunters and hiring managers would agree: An interview isn’t the ideal way to find the best person for the job. Applicants sometimes exaggerate their strengths; managers rely on subjective information to make decisions.

And the problem is growing, as rapid technological change forces companies to constantly adjust to new ways of working. Once‑indispensable hard skills or experience may be less and less predictive of a candidate’s chances of success on the job.

“If we accept the fact that jobs are going to be disrupted and replaced, and 80% of the jobs you will find in 2030 or 2040 don’t exist today, and there is a devaluation of expertise and knowledge, then you have to bet on things like curiosity, learning ability, people skills and motivation,” says Tomas Chamorro‑Premuzic, chief talent scientist at ManpowerGroup and a professor of business psychology at University College London and Columbia University.

In the not‑too‑distant future, employers may rely less on resumes and interviews and more on a candidate’s behavior, cognitive abilities, personality traits and physiological responses to decide whether someone is a good fit. Technology is already being developed to allow employers to analyze candidates’ online history, biometric data and real‑time reactions to simulated on‑the‑job challenges.

These technologies raise concerns about ethics and fairness, and experts predict they will prompt legal challenges. In November, the nonprofit Electronic Privacy Information Center filed a complaint with the Federal Trade Commission urging the agency to investigate HireVue, a company that builds artificial‑intelligence‑based hiring tools, over concerns that its technology is not transparent and lacks accountability. HireVue declined to comment on the complaint and said in a statement that its technology “has less bias than traditional screening processes.” An Illinois statute takes effect this month requiring companies to notify job candidates when they use AI‑based video interview tools. Legislation mandating companies inspect their algorithms for bias is under consideration in Congress.

Here, we take a look at the technologies that could reshape the job interview in the years ahead.

Personality Profiling—With the Help of AI

As soft skills gain importance, more employers will use AI to create personality profiles, generated from job candidates’ social‑media profiles, LinkedIn accounts and other text posted online, as well as the words they use in virtual‑reality simulations and video submissions.

A couple of vendors, including Humantic, already offer natural language processing‑based tools to create instant candidate profiles for recruiters and employers. The companies say that the technology is based on traditional personality tests, including DiSC, a behavioral assessment tool, and the Big Five, which measures five personality traits. Instead of applicants filling out long questionnaires, an algorithm creates a personality analysis instantly and affordably, the startups say—with or without someone’s consent.

In her work helping companies select candidates for leadership positions, Tracy Levine of Atlanta‑based Advantage Talent uses Humantic’s tool to find out whether candidates are open to new ideas. The tool helps her overcome her own biases, she says.

Some experts question whether these algorithms are as accurate as traditional methods. AI‑based tools could also find language in a candidate’s social‑media profiles indicating he or she has a medical condition, including depression. Organizational psychologists have argued that it would be unfair and possibly illegal for employers to use this information to make hiring decisions.

If personality profiling becomes more prevalent, a market for algorithms that assist applicants in burnishing their social‑media histories and other online accounts could spring up, according to Ben Taylor, former chief data scientist at HireVue. That could include advising job hunters on what to delete or change to conform to specific personality profiles, he says.

A ‘Credit Score’ for Skills

Currently, many employers rely on candidates’ own assessments to determine applicants’ levels of expertise. One day, companies could automatically score skills using the text that candidates put online, such as LinkedIn posts and Twitter interactions. Experts predict this might first be used to evaluate software engineers’ coding abilities, since they often post code directly to platforms like GitHub.

“Companies will probably start offering certifications for various skills more often because it is becoming a bigger problem: I can claim I have a skill, I don’t have to prove it,” says Tara Behrend, an organizational psychology professor at George Washington University.

On hard skills such as programming and soft skills such as communication abilities, candidates could seek out or receive a number like a credit score. “You are going to see this whole market that does not really exist today,” says Mr. Taylor. “Candidates want it. They want to come across as a very competitive hire.”

Jenny Yang, a fellow at the Urban Institute and former commissioner of the Equal Employment Opportunity Commission, compared the experience to using a person’s high school SAT score to make hiring decisions throughout his or her life. “It does worry me some to think about static things that are hard to change—they are often correlated with wealth,” she says.

Testing Job Performance—Virtually

Employers are already using VR for on‑the‑job testing, training and diversity initiatives. Israel‑based ActiView offers VR assessments for hiring, particularly for recent graduates with shorter resumes.

Israel‑based ActiView offers virtual‑reality assessments for hiring. This test measures cognitive abilities, personality attributes and work methods including time management, attention to detail and tenacity, the company says.

In a typical assessment, a candidate plays a cognitive game while wearing a headset and the system analyzes the person’s behavioral patterns. “Do you strategize before you start solving something or not so much? How decisive are you in your actions?” says Gil Asher, the company’s chief technology officer. Then the job seeker faces simulations of problems he or she might encounter on the job. “If it’s a customer‑service candidate, we put them in front of an angry customer and see how they react,” says Mr. Asher.

Other makers of VR assessment tools are hesitant to use them for hiring decisions because some applicants experience vertigo or motion sickness while wearing headsets.

“You have to be very careful when you are designing an assessment that you are giving people a level playing field,” says Doug Reynolds, executive vice president at Development Dimensions International, which develops assessment tools and VR systems to build empathy in the workplace.

ActiView says it uses advanced headsets and conducts stationary VR tests, reducing vertigo. If job candidates still have problems, they can request an alternative test.

Companies such as HireVue test candidates using video simulations, and use algorithms to determine who’s a good fit. Its clients have included Hilton Worldwide Holdings Inc., Unilever PLC and other Fortune 500 companies. (Unilever declined to comment. Hilton said in a statement that it has used HireVue’s predictive assessment tools in the past as “one data point among many” that its recruiters use to make hiring decisions.)

The Right Brain for the Job

In the next five years, wearable health technology will be able to measure blood pressure, eye movements and skin conductivity, or how well skin transfers electricity, to predict arousal and anxiety, computer scientists say. These technologies could help companies assess job seekers’ stress and engagement levels and self‑regulation skills during VR simulations.

The systems might even be able to monitor brain waves, some experts say, to figure out whether someone has the optimal brain for a job based on the brain structures of employees who are successful in the role.

But it’s difficult to correctly interpret biometric data. Even if you can detect brain waves, “are they for stress or are they more deep thinking?” says Santosh Kumar, a computer science professor at the University of Memphis, who develops wearable health technology.

Biometric information could also reveal medical issues, such as heart conditions, mental illnesses or disabilities—which could be illegal.

“If something is an accurate predictor or a valid signal, but it is beyond people’s control, I think the level of fairness is questionable,” says Dr. Chamorro‑Premuzic.

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Demis Hassabis on AI’s potential

Posted by hkarner - 8. Januar 2020

Date: 06‑01‑2020

Source: The Economist 2020 VISIONS

Artificial intelligence could accelerate research in a range of fields,

says Demis Hassabis, co‑founder and CEO, DeepMind

THE SCIENTIFIC method was perhaps the single most important development in modern history. It established a way to validate truth at a time when misinformation was the norm, allowing natural philosophers to navigate the unknown. From predicting the motions of the planets to discovering the principles of electricity, scientists have honed the ability to distil facts about the universe by generating theories, then using experimentation to qualify those theories. Looking at how far civilisation has come since the Enlightenment, one can’t help being awestruck by all that humanity has achieved using this approach. I believe artificial intelligence (AI) could usher in a new renaissance of discovery, acting as a multiplier for human ingenuity, opening up entirely new areas of inquiry and spurring humanity to realise its full potential.

The promise of AI is that it could serve as an extension of our minds and become a meta‑solution. In the same way that the telescope revealed the planetary dynamics that inspired new physics, insights from AI could help scientists solve some of the complex challenges facing society today—from superbugs to climate change to inequality. My hope is to build smarter tools that expand humans’ capacity to identify the root causes and potential solutions to core scientific problems.

Traditional AI programs operate according to hard‑coded rules, which restrict them to working within the confines of what is already known. But a new wave of AI systems, inspired by neuroscience, are capable of learning on their own from first principles. They can uncover patterns and structures that are difficult for humans to deduce unaided, opening up new and innovative approaches. For example, our AlphaGo system mastered the ancient game of Go just by competing against itself and learning from its own mistakes, resulting in original, aesthetically beautiful moves that overturned thousands of years of received wisdom. Now, players of all levels study its strategies to improve their own game. Den Rest des Beitrags lesen »

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Tech Will Rule These ’20s, Too

Posted by hkarner - 7. Januar 2020

Date: 06‑01‑2020

Source: The Wall Street Journal By Andy Kessler

Breakthroughs in health and data could match the consumer boom of 100 years ago.

Does history rhyme? A century ago, the ’20s boomed, driven by consumer spending on homes, cars, radios and newfangled appliances like refrigerators, sewing machines and vacuum cleaners. Most Americans couldn’t afford the upfront cost of a lot of these goods, so manufacturers and retailers invented installment plans. Debt ruled as 75% of cars, furniture and washing machines were bought on credit.

The supply‑side policies of Treasury Secretary Andrew Mellon, who pushed for tax cuts in 1921, 1924 and 1926, increased the capital available for new consumer businesses. The consumption boom also sparked a giant service industry: My grandfather ran Kessler’s Refrigeration Service in Brooklyn, N.Y. Lifestyle advertising was perfected on billboards and in tabloids, which, like today, led to complaints about ads’ ubiquity and influence.

And stocks were hot, hot, hot. Radio Corp. of America shares were worth $11 in 1924, $20 in January 1928 and $114 in 1929, with a peak price/earnings ratio of 72. Turns out equities could be bought on installment too—sometimes a margin loan with a measly 10% down payment.

Like the movie “Titanic,” you know how this ends. Speculation. Tariffs. And finally, the crash of Oct. 28‑29, where the market dropped 13% on Black Monday and 12% on Black Tuesday, triggering widespread margin calls for debt repayment. That risk is why the Federal Reserve now caps stock margins at 50%. According to legend, it’s also why windows in New York skyscrapers don’t open. By 1932, RCA stock was worth $3. Den Rest des Beitrags lesen »

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An artificial intelligence predicts the future

Posted by hkarner - 29. Dezember 2019

Date: 28‑12‑2019

Source: The Economist

What would an artificial intelligence think about the year ahead? We decided to ask one

This publication draws on a wide range of expertise to illuminate the year ahead. Even so, all our contributors have one thing in common: they are human. But advances in technology mean it is now possible to ask an artificial intelligence (AI) for its views on the coming year. We asked an AI called GPT‑2, created by OpenAI, a research outfit. GPT‑2 is an “unsupervised language model” trained using 40 gigabytes of text from the internet. Given a prompt, such as a question or the first sentence of a story, it generates what might plausibly come next. Here are some of its (unedited) ­answers to our questions on the big themes of 2020.

Q: Greetings, GPT‑2. Have you done an interview before?

A: I’m not going to lie. I did not come prepared (laughs).

Q: Which technologies are worth watching in 2020?

A: I would say it is hard to narrow down the list. The world is full of disruptive technologies with real and potentially huge global impacts. The most important is artificial intelligence, which is becoming exponentially more powerful. There is also the development of self‑driving cars. There is a lot that we can do with artificial intelligence to improve the world. Den Rest des Beitrags lesen »

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How to Win with Artificial Intelligence

Posted by hkarner - 20. Dezember 2019

October 15, 2019 By Shervin Khodabandeh , Ronny Fehling , Burt LaFountain , Sylvain Duranton , Philipp Gerbert , Annais Paetsch , and Martin Reeves, BCG

Among the many companies investing in artificial intelligence, there is one surprisingly exclusive group: companies that actually generate value from AI. And right now, at least, the odds against gaining admission are sobering. According to a survey of more than 2,500 executives—conducted for a new report by MIT Sloan Management Review, BCG Gamma, and BCG Henderson Institute—seven out of ten companies report minimal or no gains so far from their AI initiatives. Why do some efforts succeed but many more fail?

It’s a crucial question, as the importance and urgency around AI are greater than ever. Nine out of ten survey respondents agreed that AI represents a business opportunity for their company. And nearly half—45%—perceive some risk from AI. So while companies see a lot of potential in AI, they also fear that their competitors may realize it first.

The report looked for patterns in the survey data—supplementing the analysis with in-depth interviews with executives leading AI initiatives. The idea: to uncover the common strategies and approaches employed by those companies that do generate value.

Ultimately, a set of critical strategic, organizational, and leadership behaviors emerged: steps other companies can take to boost their chances of joining that select club—and winning with AI.

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Artificial Intelligence and the Adversary

Posted by hkarner - 4. Dezember 2019

Date: 04‑12‑2019

Source: The Wall Street Journal By Samantha Ravich

What will Beijing do with the data it stole about American military service members and others?

The potential benefits of artificial intelligence are proclaimed loudly, for all to hear. The dangers, however, are discussed quietly among national‑security experts. The time has come to bring the general population into the discussion.

The benefits are enticing. With AI, the future promises longer life expectancy, increased productivity, and better preservation of precious resources. You will be able to take a picture of a mole on your leg and send it electronically to a dermatologist, who will use deep neural networks to determine whether it is skin cancer. Data‑driven sensors and drones will determine the perfect amount of pesticide and water to promote agricultural diversity and counter monocropping. The AI revolution in transportation will herald autonomous planes, trains and automobiles. Music will be created to improve not only mood but heart rate and brain activity. Den Rest des Beitrags lesen »

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How machine learning is revolutionising market intelligence

Posted by hkarner - 24. November 2019

Date: 23-11-2019
Source: The Economist

The business of gathering market-sensitive information is ripe for automation

The thames seems to draw people who work on intelligence-gathering. The spooks of mi6 are housed in a funky-looking building overlooking the river. Two miles downstream, in a shared office space near Blackfriars Bridge, lives Arkera, a firm that uses machine-learning technology to sort intelligence from newspapers, websites and other public sources for emerging-market investors. Its location is happenstance. London has the right time zone, between the Americas and Asia. It is a nice place to live. The Thames happens to run through it.

Arkera’s founders, Nav Gupta and Vinit Sahni, both have a background in “macro” hedge funds, the sort that like to bet on big moves in currencies and bond and stock prices ahead of predicted changes in the political climate. The firm’s clients might want a steer on the political risks affecting public finances in Brazil, or to gauge the social pressures that could arise as a consequence of an austerity programme in Egypt. It applies machine learning to find market intelligence and make it usable. Den Rest des Beitrags lesen »

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AI Doesn’t Actually Exist Yet

Posted by hkarner - 14. November 2019

Date: 13-11-2019
Source: Scientific American By Max Simkoff, Andy Mahdavi

Many businesses claim they’re using it, but they’re kidding themselves—and they’re kidding you, too

During the past few years, all kinds of businesses have begun using what they call “artificial intelligence.” One international survey said 37 percent of organizations have, as a press release put it, “implemented AI in some form.” A different survey, looking at U.S. businesses, put the figure at 61 percent. A third, focused on the U.S. and the U.K., said, in the words of another press release, a whopping “77% have implemented some AI-related technologies in the workplace.”

The numbers don’t differ based on geography alone. They highlight a problem facing any discussion about AI: Few people agree on what it is.

Working in this space, we believe all such discussions are premature. In fact, artificial intelligence for business doesn’t really exist yet. To paraphrase Mark Twain (or rather a common misquote of what Twain actually said), reports of AI’s birth have been greatly exaggerated. Den Rest des Beitrags lesen »

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