Facility management might not sound like the sexiest use of AI technology. But office space can be a huge expense for larger businesses the biggest after staff costs which is why Y Combinator-backed startup, VergeSense, says its settled on facility management as the initial target for an AI-powered sensing device its been developing since joining the incubator program in May.

Their sensor as a system platform, as they dub it, consists of sensing devices containing a series of different sensor hardware, including an image sensor, coupled with a cloud platform for pre-training machine learning models that run on the hardware, process data and report occupancy analysis back to VergeSenses cloud.

Were using really inexpensive hardware weve crammed a bunch of different sensors inside. The core of the product is actually built around computer vision, so weve got a really inexpensive image sensor thats embedded inside, VergeSense co-founder Dan Ryan tells TechCrunch. The whole concept around what were doing is were using machine learning in pre-trained AI modules to do all of processing on the device itself.

Were not streaming a bunch of raw video data back to a cloud service weve pre-trained our models to run on the device themselves, he adds.

These AI modules can be trained to meet the particular tracking requirement of a customer before being loaded onto the sensor hardware that is sited in the customers space. This means processing is done locally, on the device, and only detection results are sent to the cloud where VergeSense customers are able to log in to view the analytics pertaining to their building.

Overall the sales pitch to customers is a system that can passively track how an office space is being used, providing visibility into dynamic multi-occupant, even multi-tenant environments, and making suggestions on how to reallocate resources to make best use of a space.

Maybe youve got an office thats segmented between a bunch of open office spaces and youve got a bunch of conference rooms, but your conference rooms are actually way over-utilized, theyre full all the time, we could inform that building owner that those rooms are being over-utilized and that they need to double down on a room, explains Ryan.

Or, in the opposite use-case, we could say youve got a conference room thats designed for 16 people but at max we only get two people using the room We can make that data available to them and they could split that space into two spaces.

It sounds like kind of a boring problem, but especially in the Bay Area, the price of real estate being $60/ft a year, on average, if youve got a 300sq ft conference room space thats an $18,000 a year asset, right. Just in that one room. So theres actually huge savings and efficiencies you can start gleaning by making all that data available to the end-users, he adds.

As well as an image sensor, the hardware contains a PIR (infrared) motion sensor, audio and RF capability (wi-fi and Bluetooth).

Typically an office space would need one sensor per 1,000sq ft, according to Ryan, although he says this can vary depending on factors such as ceiling height.

At this stage the team has a few early phase deployments of their system across some Fortune 500 companies in the Bay Area.

The startups first focus is commercial office buildings. And the first application its offering is people counting, to power occupancy analytics, though Ryan says the tech could also be used to track lots of other things for example, specific equipment like photocopiers, or even to hone in on something as specific as desk occupancy or to track usage of specific devices.

He also envisages utility in other verticals in future such as tracking people and equipment in hospitals or retail environments, for example.

The sensors can either be wired in or battery powered. They can also run on different networks, depending on whether the customer wants them on their corporate network (or indeed on a dedicated IoT network).

Ryan says VergeSense also offers a gateway device that can backhaul over a 2G cellular connection. Were not sending a lot of data. Its a little like text messages, what you can think of in terms of the data were sending back just people counts, he adds.

From a privacy point of view, as well as local processing, he says all the tracking is anonymous, so VergeSense is not tying analytics to individual identities or otherwise harvesting individual identities. Were not getting any personally identifiable information about anybody, he says. Its all anonymous counts i.e. I saw a person or I detected an object here or there.

Though he also suggests businesses deploying sensing technology within a multi-occupant environment where such tech at least runs the risk of being viewed suspiciously are best being upfront and honest with the employees at the facility about what the datas being used for and how its being leveraged.

The core challenge that people are trying to solve with these technologies is managing the space and actually making the employee experience more fulfilling and less frustrating, he argues. Theres not really the big brother aspect to the technologies its more about how do we just make that data make this workspace more efficient overall.

And while there are other potential solutions for tracking occupancy and equipment, for example motion sensors or RFID or Bluetooth tags on individual items, Ryan says VergeSenses advantage is the system allows for a purely passive approach to tracking so theres no need to manually tag anything, and the system adapts to changes as the models are trained to interpret the environment.

We havent seen many other folks yet with this sort of combination of really inexpensive hardware powered by machine learning, he says, when asked about the competitive landscape. I expect to see a lot more competition popping up over the next six months to a year. But I still think the space is pretty early.

And if you talk to anybody in this space particular real estate services space utilization people have been looking for solutions for this for years, literally And nobodys really come to the table yet with a solution thats flexible, simple to deploy yet really, really powerful.

We think this combination of machine learning AI on inexpensive hardware is going to be really powerful and unlock much opportunity, he adds. With computer vision youre just going to have so many different things that youre going to be able to train the models to detect and report back.

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VergeSense's AI sensing hardware tackles facility management - TechCrunch

In BriefAstrophysicist Lord Martin Rees believes that AI could surpasshumans within a few hundred years, ushering in eons of dominationby electronic intelligent lifethe same kind of intelligent life hethinks may already exist elsewhere in the universe. Fixed to This World

Lord Martin Rees, Astronomer Royal and University of Cambridge Emeritus Professor of Cosmology and Astrophysics, believes that machines could surpasshumans within a few hundred years, ushering in eons of domination. He also cautions that while we will certainly discover more about the origins of biological life in the coming decades, we should recognize that alien intelligence may be electronic.

Just because theres life elsewhere doesnt mean that there is intelligent life, Lord Rees told The Conversation. My guess is that if we do detect an alien intelligence, it will be nothing like us. It will be some sort of electronic entity.

Rees thinks that there is a serious risk of a major setback of global proportions happening during this century, citing misuse of technology, bioterrorism, population growth, and increasing connectivity as problems that render humans more vulnerable now than we have ever been before. While we may be most at risk because of human activities, the ability of machines to outlast us may be a decisive factor in how life in the universe unfolds.

If we look into the future, then its quite likely that within a few centuries, machines will have taken overand they will then have billions of years ahead of them, he explains. In other words, the period of time occupied by organic intelligence is just a thin sliver between early life and the long era of the machines.

In contrast to the delicate, specific needs of human life, electronic intelligent life is well-suited to space travel and equipped to outlast many global threats that could exterminate humans.

[We] are likely to be fixed to this world. We will be able to look deeper and deeper into space, but traveling to worlds beyond our solar system will be a post-human enterprise, predicts Rees. The journey times are just too great for mortal minds and bodies. If youre immortal, however, these distances become far less daunting. That journey will be made by robots, not us.

Rees isnt alone in his ideas. Several notable thinkers, such as Stephen Hawking, agreethat artificial intelligences (AI) have the potential to wipe out human civilization. Others, such as Subbarao Kambhampati, the president of the Association for the Advancement of Artificial Intelligence, see malicious hacking of AI as the greatest threat we face. However, there are at least as many who disagree with these ideas, with even Hawking noting the potential benefits of AI.

As we train and educate AIs, shaping them in our own image, we imbue them with the ability to form emotional attachmentsthat could deter them from wanting to hurt us. There is evidence thatthe Singularity might not be a single moment in time, but is instead a gradual process that is already happeningmeaning that we are already adapting alongside AI.

But what if Rees is correct and humans are on track to self-annihilate? If we wipe ourselves out and AI is advanced enough to survive without us, then his predictions about biological life being a relative blip on the historical landscape and electronic intelligent life going on to master the universe will have been correctbut not because AI has turned on humans.

Ultimately, the idea of electronic life being uniquely well-suited to survive and thrive throughout the universe isnt that far-fetched. The question is, will we survive alongside it?

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Eminent Astrophysicist Issues a Dire Warning on AI and Alien Life - Futurism

The zoom and enhance trope is a TV clich, but advances in AI are slowly making it a reality. Researchers have shown that machine learning can enlarge low-resolution images, restoring sharpness that wasnt there before. Now, this technology is making its way to consumers, with image editor Pixelmator among the first to offer such a feature.

The Photoshop competitor today announced what it calls ML Super Resolution for the $60 Pro version of its software: a function that the company says can scale an image up to three times its original resolution without image defects like pixelation or blurriness.

After our tests, we would say this claim needs a few caveats. But overall, the performance of Pixelmators super resolution feature is impressive.

Pixelation is smoothed away in a range of images, from illustration to photography to text. The results are better than those delivered by traditional upscaling algorithms, and although the process is not instantaneous (it took around eight seconds per image on our 2017 MacBook Pro), its fast enough to be a boon to designers and image editors of all stripes. There are some examples below from Pixelmator, with a zoomed-in low resolution image on the left, and the processed ML Super Resolution image on the right:

You can see more images over on Pixelmators blog, including comparisons with traditional upscaling techniques like the Bilinear, Lanczos, and Nearest Neighbor algorithms. While ML Super Resolution isnt a magic wand, it does deliver consistently impressive results.

Research into super resolution has been ongoing for some time now, with tech companies like Google and Nvidia creating their own algorithms in the past few years. In each case, the software is trained on a dataset containing pairs of low-resolution and high-resolution images. The algorithm compares this data and creates rules for how the pixels change from image to image. Then when its shown a low-resolution picture its never seen before, it predicts what extra pixels are needed and inserts them.

Pixelmators creators told The Verge that their algorithm was made from scratch in order to be lightweight enough to run on users devices. Its just 5MB in size, compared to research algorithms that are often 50 times larger. Its trained on a range of images in order to anticipate users different needs, but the training dataset is surprisingly small just 15,000 samples were needed to create Pixelmators ML Super Resolution tool.

The company isnt the first to offer this technology commercially. There are a number of single-use super resolution tools online, including BigJPG.com and LetsEnhance.io. In our tests, the output from these sites was of a more mixed quality than Pixelmators (though it was generally good), and free users can only process a small number of images. Adobe has also released a super resolution feature, but the results are, again, less dramatic.

Overall, Pixelmator seems to be offering the best commercial super resolution tool weve seen (let us know in the comments if you know of a better one), and every day, zoom and enhance becomes less of a joke.

Correction: An earlier version of this story included comparisons between images that had been non-destructively downsized then upscaled using Pixelmators ML Super Resolution, resulting in unrealistically improved results. These have been removed. We regret the error.

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AI super resolution lets you zoom and enhance in Pixelmator Pro - The Verge

Once upon a time, terrorists used bombs, machetes, and bullets to get their message across. While that's still the case, modern day terror has a new tool at its disposal, one that it has become particularly adept and successful at deploying: social media. This stark reality has come to light in the wake of terror campaigns that ended with participants pledging their support to their chosen causes and posting them on social media platforms.

Other insidious forms of communication and objectionable material have flourished in the internet era as well. Hate speech and violent threats have found homes there. Governments and advertisers worldwide are aware of the phenomenon and are increasingly pressuring social-media companies like Facebook, Inc. (NASDAQ:FB), Alphabet Inc. (NASDAQ:GOOGL) (NASDAQ:GOOG), Twitter, Inc. (NYSE:TWTR), and Microsoft Corporation (NASDAQ:MSFT) to police undesirable content on their sites.

The sheer volume of content and the differences and complexity of local laws and regulations conspired to create a near-insurmountable task for these sites. However, recent advances in artificial intelligence (AI) are being brought to bear, and producing surprisingly effective results.

Facebook is deploying AI to fight terror. Image source: Facebook.

Facebook revealed that new AI algorithms based on image recognition have been deployed to assist with the Herculean chore. One tool has been developed to scan the site for images and live videos containing terrorist propaganda, including beheadings, and to remove them without the intercession of a human moderator.

Another system has been trained to identify accounts that have been set up by terrorists, and prevent them from setting up additional accounts. Another algorithm is being trained in the language of propaganda to help identify posts related to terror. Once the content has been identified and removed, the system catalogs the data, then consistently scans the site and identifies attempts to repost it.

Twitter has been deploying similar tools based on AI for rooting out terrorist content. The company says that these methods flagged 74% of the nearly 377,000 accounts it removed between July and December of 2016.

This follows an alliance by some of the biggest names in tech circles late last year to create a database of the worst content, to prevent it from being reposted on any of the sites. YouTube, Twitter, and Facebook joined Microsoft in the venture to create unique digital identifiers, or "fingerprints," to use for automatically detecting and removing content that had previously been tagged as terrorist propaganda.

Microsoft developed and deployed similar technology to battle child pornography on the internet. The system was used to detect, report, and remove the images contained in a database.

Big tech is bringing AI to the fight on terror. Image source: Getty Images.

Google, the Alphabet subsidiary and owner of YouTube, is a pioneer in AI and recently found another way to use the nascent technology. YouTube faced a massive boycott from some of its biggest advertisers after it was revealed that brand advertising had appeared on YouTube videos containing racist, homophobic, anti-Semitic, and terrorist content. The company applied new AI techniques to the task, and within weeks achieved a 500% improvement in identifying objectionable content. YouTube revealed that more than half the content it removed over the previous six months for containing terrorist-related material had been identified using AI.

The world is a complicated place, and new technology brings new challenges. The advent of social media brought the world closer together, for better or for worse. Artificial intelligence is still a nascent technology, and while it isn't a panacea, it is being used in a variety of ways that make the world a better place.

Suzanne Frey, an executive at Alphabet, is a member of The Motley Fool's board of directors. Teresa Kersten is an employee of LinkedIn and is a member of The Motley Fool's board of directors; LinkedIn is owned by Microsoft. Danny Vena owns shares of Alphabet (A shares) and Facebook. Danny Vena has the following options: long January 2018 $640 calls on Alphabet (C shares) and short January 2018 $650 calls on Alphabet (C shares). The Motley Fool owns shares of and recommends Alphabet (A shares), Alphabet (C shares), Facebook, and Twitter. The Motley Fool has a disclosure policy.

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How Social Media Is Using AI to Fight Terrorism - Motley Fool

The conversation in the technology community about artificial intelligence was first rekindled by manufacturing giant IBM and its AI platform, Watson, CEO Ginni Rometty said on Tuesday.

"We are the ones that woke up the AI world here again," Rometty told "Mad Money" host Jim Cramer in a wide-ranging interview about Washington, Warren Buffett and her business.

Rometty said that the key to her century-old company remaining an institution in this country is how many times it has been able to reinvent itself and follow the latest trends in tech.

Today, those trends are the cloud and artificial intelligence, which IBM employees refer to as "cognitive" programming.

"There's a reason we call it cognitive," Rometty told Cramer. "It's about augmenting what you and I do so we can do what we're supposed to, our best. And then that's the IBM that takes that technology and the know-how about how the world works and puts that together and actually changes business. We are the champion for business."

Rometty also stressed the distinction between AI that consumers see and use and IBM's AI area of expertise, business-oriented AI programs.

"Consumer AI in your home, it's typically speech detects to a search. That's fine. That's great," she said. "But we deal in the enterprise world, so this is training Watson. Watson is trained in industries: What does underwriting do? What does a tax preparer do? What does a doctor do? What does a customer service agent do? What does a repairperson do? And it helps them be better, and, in fact, helps them do their job."

Between IBM's dealings in cognitive programming and the internet of things, Rometty predicted that 1 billion people would interact with Watson by the end of 2017. The result would be a boon to IBM's latest transformation efforts, which Rometty said revolve around one word: data.

The CEO said that Watson will likely also play a monumental role in reforming the health care system, the first step of which would involve touching the lives of 20,000 cancer patients.

"We will be able to address, diagnose and treat 80 percent of what causes 80 percent of the cancer in the world. If that's not motivating, I don't know what is," Rometty told Cramer.

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IBM 'woke up the AI world,' CEO Ginni Rometty says - CNBC

The News Journal Published 11:23 a.m. ET Feb. 24, 2017 | Updated 7 hours ago

Red Clay School District has upheld a decision by A.I. du Pont High School Principal to remove the boys basketball team from consideration for the upcoming DIAA state tournament. 2/24/17 Damian Giletto/The News Journal

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DMA's commandant, Anthony Pullella, responds to accusations his students provoked an incident between A.I. players and fans during a basketball game last week. 2/24/17 JOHN J. JANKOWSKI JR./SPECIAL TO THE NEWS JOURNAL

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Red Clay Consolidated School District will review a decision by the A.I. du Pont High School principal to ban the boys basketball team from participating in the upcoming DIAA Boys Basketball Tournament. 2/23/17 Damian Giletto/The News Journal

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Red Clay upholds A.I. principal's decision to end season

DMA commandant responds to incident at A.I. basketball game

A.I. du Pont principal, parents meet over basketball suspensions

A.I. duPont High School principal Kevin Palladinetti tries to answer questions from parents and political leaders about an incident after the team's 58-46 loss at Delaware Military Academy last Thursday that lead the team from participating in the upcoming DIAA Boys Basketball Tournament.(Photo: Jennifer Corbett, The News Journal )Buy Photo

Red Clay Consolidated School District has upheld a decision by A.I. du Pont High School Principal KevinPalladinetti to remove the boys basketball team from consideration for the upcoming DIAA state tournament.

"We understand it was a difficult decision by staff at A.I. High School but we support that decision and stand behind it, said Superintendent Merv Daugherty. The district believes the disciplinary consequence fits the seriousness of the incident.

Jen Field, whose son is a senior on the team, told The News Journal that a group of those opposed toPalladinetti's decision will meet Friday night to discuss what, if any, next steps they will take.

Palladinettis decision stemmed from an incident following the Tigers loss at Delaware Military Academy on Feb. 16.

With 40 seconds left, an A.I. player was given a technical foul. At that point, A.I. head coach Tom Tabb said he told the players on the bench to skip the customary postgame handshake line. Instead, the coach told the team he would shake hands with the DMA team, and the players were to remain behind him and follow him off the court as a group.

When the game was over, a player started to walk and then sprinted, which caused a chain reaction where the other players followed, the coaches followed, parents followed, some DMA parents followed, Tabb said Thursday.

RELATED: More on the incident and reaction

FOOTBALL: Middletown product eyes NFL

Officials from both schools said the A.I. players ran toward a stairwell leading to thesecond level of the gymnasium, whereDMA students and fans had been watching the game.

DMA officials said they blocked the players from accessing the mezzanine while another teacher directed DMA students out through an emergency door.

Several parents of A.I. du Pont players have alleged that racial slurs were spoken by DMA players, fans and students during the game. But Palladinetti said Tabb, Assistant Principal Damon Saunders (both of whom are black)and the other A.I. assistant coaches did not report hearing any racial slurs.

DMA Commandant Anthony Pullella was at the game and said he did not hear any racial comments. Michael Ryan, the athletic director, said DMA officials conducted their own investigation, questioning parents, players, coaches and fans. He said no evidence was uncovered about any racial comment being used.

In a statement issued Friday, Red Clay officials said the district will also "continue to work with DMA to investigate allegations of inappropriate actions by their players and fans. The district has requested that DMA administration investigate from their school. Red Clay also requested a formal investigation from DIAA about the conduct of the fans during the AIHS/DMA game. We will share all investigative findings concerning fan conduct when we receive them from DMA and DIAA."

The district is taking the claims of inappropriate behavior from game attendees very seriously, Daugherty said. We do not condone the behavior in any way and will continue to work closely with DMA to uncover any acts of impropriety.

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School district upholds decision; AI's season over - The News Journal

Apples AI expert, Tom Gruber, delivered a TED talk back in April extolling the benefits that AI may provide for us in the years to come. The video of the onstage presentation has now been released and gives us a better glimpse into the future Gruber imagines. His presentation focuses on what he calls humanistic AI, the belief that when machines get smarter, so will we.

Gruber explains that the purpose of AI is to empower humans with machine intelligence and that the two can work together effectively. In his talk, he goes through various examples of how AI can be used to improve upon normal human functions and interactions.Starting with Siri, Gruber explains that the virtual assistant was designed as humanistic AI.The assistant may not be world-changing for some users, but for others it quite literally is.

To augment people with a conversational interface that made it possible for them to use mobile computing regardless of who they were and their abilities.

for my friend Daniel, the impact of the AI in these systems is a lifechanger. You see Daniel is a really social guy and hes blind and quadriplegic which makes it hard to use those devices that we all take for granted.

Daniel uses Siri to manage his own social life, his email, text, and phone, without depending on his caregivers. Heres a man whose relationship with AI helps him have relationships with genuine human beings.

Through the rest of his onstage conversation, Gruber continues with more examples of the benefits of human and machine intelligence collaborations. Showing improvements in cancer detection, engineering, and even human memory. Gruber believes that AI will benefit all of us in some manner.

He is clear to point out that the usage of AI to improve human memory must be kept private and secure. In myview, a personal memory is a private memory, he shares. We get to choose what is and is not recalled and retained. Its absolutely essential that this be kept very secure.

Watch Tom Grubers entireon stage TED presentation below.

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Apple AI expert, Tom Gruber explains Siri's 'humanistic AI' at TED - 9to5Mac

When MIT and IBM launched a joint research lab in 2017, the New York-headquartered company pledged $240 million over a decade to chip away at the fundamental obstacles keeping artificial intelligence from transforming industries like healthcare and cybersecurity.

Now, the Cambridge, MA-based MIT-IBM Watson AI Lab is growing in personnel, funding, partners, and square feet, says David Cox, a former Harvard professor who leads the program for IBM (NYSE: IBM).

This week, the lab welcomed its first batch of outside partners. They include South Korea conglomerate Samsung, medical device company Boston Scientific (NYSE: BSX), construction tech firm Nexplore, and financial data provider Refinitiv. Cox said there is a healthy pipeline of other companies that may tap into the labs expertise.

The investment that each partner brings to the lab could lead the joint research venture to end up with double the $240 million it expected from the outset. The funds will help researchers work on making artificial intelligence more autonomous and easier to apply to real-world problems.

We could imagine as much as doubling that investment over time as the program grows, Cox said, declining to share financial figures for how much the partners are chipping into the endeavor. We can substantially increase the scale of the investment we make in MIT.

Cox explained, though, that the final list of partners wont be too extensive.

We dont foresee it being an extremely large program, he said. There are other membership models where you pay a very small amount of money, and everybody is part of it. We really want to have a relatively small number in deep, deep engagements.

In terms of research staff, the numbers are also higher than initially planned. The labs charter envisioned the equivalent of 100 full-timers. The reality now is the lab has 70 projects underway, and MIT and IBM both provide at least one staffer per project, Cox said. (Back in March 2019, Cox told Xconomy the lab had 49 research projects up and running.)

To accommodate the bigger team, the lab is moving a few blocks south to the heart of Kendall Square. The new home for the lab will be 314 Main Street, a 440,000-square-foot MIT building under construction that is expected to also be the home of the MIT Museum, the MIT Press Bookstore, and Boeings Aurora Flight Sciences research unit. Cox said work on the building will be completed next year.

Cox said one of the best mile markers for the labs progress is publications, and so far researchers have got 110 papers in journals.

The lab is likely to keep its focus on healthcare and cybersecurity, both local concentrations for IBMs Watson business, Cox said. Teams will also continue their research into how artificial intelligence systems function at their core.

An appealing angle on fundamental AI research for the MIT-IBM teams has been something called neural-symbolic AI, which combined the popular deep learning technologies with symbolic reasoning techniques needed to learn abstract concepts and solve problems, Cox said. Combining the two could help develop more flexible AI systems that call for less hand-holding from humans to clean data, tweak algorithms, and carefully set up a framework for the AI system to explore.

The vision for neural-symbolic AI systems would be one that could think a lot more like humans think, need small sets of data to understand abstract concepts and be more transparent in the decision-making process.

Whats interesting about that is its a progression where less and less is predefined, Cox says, and the system is more and more genuinely autonomous.

Brian Dowling is a Senior Editor at Xconomy, based in Boston. You can reach him at bdowling [at] xconomy.com.

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New Deals May Double $240M Funding For MIT-IBM AI Lab, Director Says - Xconomy

Ford has invested $1 billion in a joint venture with Argo AI, a Pittsburgh-based company with ties to Carnegie Mellon. The goal is to completely outfit Ford vehicles with self-driving technology. Interestingly this isnt a case of a large company simply hiring talent but the creation of an entirely separate company with an independent equity structure.

Ford is the majority stakeholder but will operate with substantial independence. Employees will receive equity in the company. The investment will be made over five years.

AI makers know you basically need an automaker to make an auto, said a person familiar with the deal commenting on Fords decision to connect with the company.

Argo AI will develop and deploy the latest advancements in artificial intelligence, machine learning and computer vision to help build safe and efficient self-driving vehicles that enable these transformations and more, wrote CEO Bryan Salesky. The challenges are significant, but we are a team that believes in tackling hard, meaningful problems to improve the world. Our ambitions can only be realized if we are willing to partner with others and keep an open mind about how to solve problems. Salesky worked at the Carnegie Mellon University National Robotics Engineering Center and, in 2011, led self-driving hardware at Google.

Other team leaders include Dr. Brett Browning and Dr. Peter Rander. Both left CMU for Uber and recently made the switch to Argo. The company is targeting full autonomy by 2021. The pair are part of the slow exodus of researchers from Uber two years after that company hired robotics faculty away from CMU.

Fords billion dollar investment in a company two months old is, arguably, quite bold. Sources say that the team in place has extensive experience in building autonomous vehicles for Caterpillar and others and it seems this is the best and fastest way for Ford to access self-driving talent.

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Ford invests $1 billion in Pittsburgh-based Argo AI to build self-driving cars by 2021 - TechCrunch

Did you know TNW Conference has a track fully dedicated to exploring new design trends this year? Check out the full Sprint program here.

Our intelligence is what makes us human, and AI is an extension of that quality. Yann LeCun

Thehuman species has performed incredible feats of ingenuity. We have created beautiful sculptures from a single block of marble, written enchanting sonnets that have stood for centuries and landed a craft on the face of a distant rock orbiting our planet. It is sobering then to think, that what separates us from our close, albeit far less superior cousins the chimpanzee, is a45% difference in our genomes.

I propose to you, however, that natures insatiable thirst for balance has ultimately led us to create a potential rival to our dominance as a species on this planetArtificial Intelligence. The pertinent question then becomes, what aspects of our infamous ingenuity will AI augment, and perhaps ultimately surpass?

What is AI & Machine Learning?

Essentially what some really smart people out there are trying to achieve, is a computer system that emulates human intelligence. This is the ability to make decisions that maximize the chance of the system achieving its goals. Even more important is the ability of the system to learn and evolve.

To achieve this, every system needs a starting point massive amounts of data. For example, in order to train a computer system to tell the difference between a cat and a dog, you would have to feed it with thousands of images of cats and dogs.

Read: [AI will never replace good old human creativity]

What is creativity?

Creativity is seeing what everyone else saw, and thinking what no one else thought Albert Einstein

Ive heard many people say a computer system could never be creative, and that to create art, music,or an ad campaign, one needs to feel, have a soul, and a lifetime of experiences to draw from.

Having spent over a decade in the advertising industry, I can confidently say that the best creatives I have seen, were usually the ones with the most exposure. The more you have seen, traveled or experienced, the more creative you tend to be.

Creativity is about challenging the norm,thinking differently, being the square pegs in the round holes, and evoking specific emotions in your audience. So how difficult can that be for AI to achieve? It certainly seems that in todays world, creativity is actually very arbitrary. Why? Because both this

and this

are considered valuable works of art.

The current state of AI vs Creatives

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Will product designers survive the AI revolution? - The Next Web

New automated harvesters like the Harvest CROO Robotics strawberry robot utilizes AI to capture images of ripe berries ready to pick.Photo by Frank Giles

Artificial intelligence, or AI as it is more commonly called, has become more prominent in conversations about technology these days. But what does it mean? And how might it shape the future of agriculture?

In many ways, AI is already at work in agricultural research and in-field applications, but there is much more to come. Researchers in the field are excited about its potential power to process massive amounts of data and learn from it at a pace that far outstretches the capability of the human mind.

The newly installed University of Florida Vice President of Agriculture and Natural Resources, Scott Angle, sees AI as a unifying element of technology as it advances.

Robotics, visioning, automation, and genetic breakthroughs will need advanced AI to benefit growers, he says. Fortunately, UF recognized this early on and is developing a program to significantly ramp up AI research at the university.

Jim Carroll is a global futurist who specializes in technology and explaining it in a way that non-computer scientists can understand. He says first and foremost, AI is not some out-of-control robot that will terrorize and destroy our way of life like it is often portrayed in the media and popular culture.

This isnt new, Carroll says. I actually found articles in Popular Mechanics magazine in the 1930s that spoke of Giant Robot Brains that would steal all our jobs.

What is AI, really? The best way to think about it is that its an algorithm at heart its a computer that is really good at processing data, whether that be pure data, images, or other information. It has been trained and learns how to recognize patterns, trends, and insights in that information. The more it does it and gets the right scores, the better it gets. Its not really that scary.

John McCarthy is considered one of the founding fathers of AI and is credited with coining the term in 1955. He was joined by Alan Turing, Marvin Minsky, Allen Newell, and Herbert Simon in the early development of the technology.

Back in 1955, AI entered the academic world as a new discipline, and in subsequent years has experienced momentum in fits and starts. The technology went through a phase of frozen funding some called the AI winter. Some of this was because AI research was divided into subfields that didnt communicate with each other. Robotics went down one path while machine learning went down another. How and where would artificial neural networks be applied to practical effect?

But, as computing power has in-creased exponentially over time, AI, as Angle notes, is becoming a unifying technology that can tie all the subfields together. What once could only be imagined is becoming reality.

Dr. Yiannis Ampatzidis, an Assistant Professor who teaches precision agriculture and machine learning at UF/IFAS, says applications are already at work in agriculture including imaging, robotics, and big data analysis.

In precision agriculture, AI is used for detecting plant diseases and pests, plant stress, poor plant nutrition, and poor water management, Ampatzidis says. These detection technologies could be aerial [using drones] or ground based.

The imaging technology used to detect plant stress also could be deployed for precision spraying applications. Currently, John Deere is working to commercialize a weed sprayer from Blue River Technology that detects weeds and applies herbicides only to the weed.

Ampatzidis notes AI is utilized in robotics as well. The technology is used in the blossoming sector of robot harvesters where it is utilized to detect ripe fruit for picking. Floridas Harvest CROO Robotics is one example. Its robot strawberry harvester was used in commercial harvest during the 2019-2020 strawberry season in Florida.

Ampatzidis says AI holds great potential in the analytics of big data. In many ways, it is the key to unlocking the power of the massive amounts of data being generated on farms and in ag research. He and his team at UF/IFAS have developed the AgroView cloud-based technology that uses AI algorithms to process, analyze, and visualize data being collected from aerial- and ground-based platforms.

The amount of these data is huge, and its very difficult for a human brain to process and analyze them, he says. AI algorithms can detect patterns in these data that can help growers make smart decisions. For example, Agroview can detect and count citrus trees, estimate tree height and canopy size, and measure plant nutrient levels.

Carroll adds there is so much data in imagery being collected today.

An AI system can often do a better analysis at a lower cost, he says. Its similar to what we are talking about in the medical field. An AI system can read the information from X-rays and be far more accurate in a diagnosis.

So, are robots and AI coming to steal all our jobs? Thats a complicated question yet to be fully played out as the technology advances. Ampatzidis believes the technology will replace repetitive jobs and ones that agriculture is already struggling to fill with human labor.

It will replace jobs in factories, in agriculture [hand harvesters and some packinghouse jobs], vehicle drivers, bookkeepers, etc., Ampatzidis says. It also will replace many white-collar jobs in the fields of law, healthcare, accounting, hospitality, etc.

Of course, AI also could develop new jobs in the area of computer science, automation, robotics, data analytics, and computer gaming.

Carroll adds people should not fear the potential creative destruction brought on by the technologies enabled by AI. I always tell my audiences, Dont fear the future, he says. I then observe that some people see the future and see a threat. Innovators see the same future and see an opportunity.

Yiannis Ampatzidis, an Assistant Professor who teaches precision agriculture and machine learning at UF/IFAS, says AI applications are already at work in agriculture.Photo by Frank Giles

In July, the University of Florida announced a $70 million public-private partnership with NVIDIA, a multinational technology company, to build the worlds fastest AI supercomputer in academia. The system will be operating in early 2021. UF faculty and staff will have the tools to apply AI in multiple fields, such as dealing with major challenges like rising sea levels, population aging, data security, personalized medicine, urban transportation, and food insecurity. UF expects to educate 30,000 AI-supporting graduates by 2030.

AlphaGo, a 2017 documentary film, probably does about as good a job as any in illustrating the potential power of AI. The film documents a team of scientists who built a supercomputer to master the board game Go that originated in Asia more than 3,000 years ago. It also is considered one of the most complex games known to man. The conventional wisdom was that no computer would be capable of learning the vast number of solutions in the game and the reasoning required to win.

The computer, AlphGo, not only mastered the game in short order it took down human masters and champions of the game.

To learn more about the film, visit AlphaGoMovie.com.

Giles is editor of Florida Grower, a Meister Media Worldwide publication. See all author stories here.

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How Artificial Intelligence Will Guide the Future of Agriculture - Growing Produce

75 years after Hiroshima and Nagasaki, some experts believe the risk of the use of a nuclear weapon is as high now as it has been since the Cuban missile crisis.

The big picture: Nuclear war remains the single greatest present threat to humanity and one that is poised to grow as emerging technologies, like much faster missiles, cyber warfare and artificial intelligence, upset an already precarious nuclear balance.

What's happening: A mix of shifting geopolitical tensions and technological change is upsetting a decades-long state of strategic stability around nuclear weapons.

Cyber warfare can directly increase the risk of nuclear conflict if it is used to disrupt command and control systems.

AI is only in its infancy, but depending on how it develops, it could utterly disrupt the nuclear balance.

Be smart: As analysts from RAND wrote in a 2018 report, "AI may be strategically destabilizing not because it works too well but because it works just well enough to feed uncertainty." Whether or not an AI system could provide a decisive advantage in a nuclear standoff, if either the system's user or that country's opponent believes it can do so, the result could be catastrophic.

The bottom line: The riskiest period of the Cold War was its earliest stages, when military and political leaders didn't yet fully understand the nature of what Hiroshima had demonstrated. Emerging technologies like AI threaten to plunge us back into that uncertainty.

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How new tech raises the risk of nuclear war - Axios

AI Next Conference KCTS 9 Discover the potential and opportunity of AI and Apply AI to real projects and services. AI makes machines become increasingly more intelligent, and revolutionizing our daily life. The AI Open Day brings together industry leaders, influential ...

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AI Next Conference - KCTS 9

How can I start learning about artificial intelligence and machine learning? originally appeared on Quora: the place to gain and share knowledge, empowering people to learn from others and better understand the world.

Answer by Alexandre Robicquet, Co-Founder of Crossing Minds, on Quora:

For those of you who are interested in careers in AI and machine learning, we recommend the following:

(this last section concerns ML & Startups - not research)

Finally, PERSEVERE. AI and ML are complicated fields that require a lot of discipline and work. This is a long journey, so hold on. Be humble, never hesitate to ask questions and help your community.

This question originally appeared on Quora - the place to gain and share knowledge, empowering people to learn from others and better understand the world. You can follow Quora on Twitter and Facebook. More questions:

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How To Get Started In Artificial Intelligence And Machine Learning - Forbes

Artificial intelligence will be tapped for everything from employee engagement to talent acquisition.

This is the second in a series on AI transforming the workplace. Read the first piece here.

Despite the pandemic continuing to spread, it may not be too soon for HR decision-makers to look ahead toward its eventual end.

When that day comes, HR leaders and employers around the globe will be back to, among other issues, figuring out exactly how AI-based technology can continue to drive success in the newly reopened world of work.

Seth EarleyCEO of Earley Information Science and author of The AI-Powered Enterprise: Harness the Power of Ontologies to Make Your Business Smarter, Faster and More Profitablesays the massive workplace changes brought on by the pandemic are sure to continue. And AI will play a key role.

Seth Earley

He predicts many organizations will continue to allow remote work even post-pandemic, and, thus will have to be more aware about what this change means for recruitment, job satisfaction, performance and retention. In fact, tech giant Google said in late July it will continue its remote work strategy until at least the middle of 2021. No doubt other employers will follow suit.

Earley says greater use of remote teams means that work culture will be more fluid and, by design, will need to be less dependent on physical cues that in-person communication provides. At the same time, he adds, measuring and maintaining employee engagement will require heightened integration of HR and day-to-day collaboration tools. This need will arise, Earley explains, because many HR applications are legacy-based, on-premise and siloed, making it harder to read signals of disengagement across multiple systems.

AI-powered, integrated cloud solutions will enable aggregation of analytics and flag low-engagement employees and employees likely to leave, Earley says. He adds that the rapid deployment of remote work and new collaboration technologies means that data, architecture and user experience functions were likely cut in the rush to adapt during the pandemic.

These tools will need to be reconciled, rationalized, standardized and correctly re-architected to improve rather than detract from productivity, he adds.

According to Earley, fewer in-office interactions will increase dependency on knowledge bases and improved information access and usability. For example, the days of asking a colleague for routine information because it is too difficult to locate on the intranet will, by necessity, be behind us.

Plus, he says, employees who have to use multiple systems to accomplish their work (or who have to adapt to a different teams preferred technology) will be less satisfied due to the overhead and inefficiency such disconnected environments cause. Using AI tools to integrate and bridge the gapsincluding through chatbots for answering routine or team- and project-specific questions, semantic search and better knowledge architecturewill improve job satisfaction and increase productivity.

Many elements of the post-pandemic workplace will change dramatically, such as the role of serendipitous in-person interactions, Early says. Intelligent collaboration systems can help fill this gap.

According to Earley, fixing the foundation of the employee experience, in part through AI-based applications, needs to be the priority across all market segments.

This will be a challenge in the post-pandemic era, but those who do not do it will lose talent, customers and market share to the ones that do, Earley says.

Ken Lazarus

Ken Lazarus, the former CEO of Scout Exchange, which was recently acquired by Aquent, expects to see an increase in AI use post-pandemic, as employers have become more sophisticated in their use of the technology, especially in regards to attracting and retaining talentwhich will be even more competitive in the years ahead.

AI started with bots for simple communication, Lazarus says. What Im beginning to see in many different use casesfrom screening applicants and job candidates and scheduling them for interviews to internal talent mobilityis a greater use of conversational AI.

You can even throw it some curveballs and have that be all conducted with software and artificial intelligence, rather than a human being, he says.

According to Lazarus, other future trends driving more AI-based solutions include:

*

Check back soon for part three.

Tom Starner is a freelance writer based in Philadelphia who has been covering the human resource space and all of its component processes for over two decades. He can be reached at hreletters@lrp.com.

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What is AI's role in remote work? | HRExecutive.com - Human Resource Executive

In BriefDeep Blue, IBM's chess computer, caused a worldwide epiphanyregarding the capabilities of AI when it defeated Gary Kasparov in1997. What is the legacy of this match, what other games has AIexcelled in, and what will it succeed in next? Deep Blues Victory

Murray Campbell, a Distinguished Research Staff Member at IBM, recently discussed the legacy and impact of the fateful 1997 chess series in which IBMs Deep Blue beat Gary Kasparov the world number one chess player for 225 out of 228 months between 1986 and 2005.

Campbell was part of the portentous encounter himself. He was a member of the team that helped build Deep Blues university progenitor, Deep Thought, which was the first program to beat a grandmaster in a professional tournament. When IBM took notice, Campbell andhis colleagues were hired by them to build Deep Blue. The system they eventually built was a combination of general-purpose supercomputer processors combined with [] chess accelerator chips.

Although computers had beaten humans in games before such as BKG 9.8s victory over Luigi Villa at backgammon in 1979 and Chinooks domination of Don Lafferty in checkers in 1994 Deep Blues victory was considered so auspicious because it won at chess.

David J. Staley wrote, concerning the match, that Chess represents a domain of human skill that is simple enough to model yet complex enough to reflect deep levels of cognition. Therefore, Deep Blues triumph marked the first true trophy for artificial intelligencebecause it beat the man who many consider to be the best player of all time at a game that has been regarded as a pinnacle of human intelligence since antiquity.

Monty Newborn, Emeritus Professor of McGill Universitys School of Computer Science, makes an apt analogy in his book Kasparov versus Deep Blue: Computer Chess Comes of Age.He states that many advances in the auto world were first tried on racing models and then after refinement incorporated into commercial vehicles. This may be the pattern in the computer field, too, where techniques used by computers to play chess are on the cutting edge of developments in complex problem-solving.

Since Deep Blue established a benchmark, says Campbell, machines have improved in processing speed and memory and so on resulting in them adding more and more gaming jewels to their virtual crown. Additionally, machine learning algorithms have access to a lot more data than they did in the past.

In recent years, the most notable victories have been AlphaGos win over five of the best Go (a game arguably more complicated than chess) players simultaneously, and Libratuss domination over four of the worlds top poker players. In this latter encounter, Dong Kim, one of the contestants, told Wired,I felt like I was playing against someone who was cheating, like it could see my cards. Im not accusing it of cheating. It was just that good.

These developments may be reflections of AIs incremental development towards becoming more human, as these games are similar to the complexities and solutions of life itself. However, Kasparovs point from 2010 that modern technology is a culture of optimization that it is derivative, incremental, profit margin-forced, consumer-friendly technology not the kind that pushes the whole world forward economically applies to these victories.

Perhaps AIs real challenge, and the next paradigm shift, is for it to defeat a game we have developed in modern times like StarCraft II.Oriol Vinyals, a DeepMind researcher and former top-ranked StarCraft player, told The Verge that the game is so complex and multifaceted that the skills required for an agent to progress through the environment and play StarCraft well could ultimately transfer to real-world tasks.

Even though you can play against AI when you play StarCraft, the AI that Vinyals is working on would be modeled afterthe way humans play the game along with usingthe same rules we do. AIs are able to play simple video games (think Atari-level), but nothing as complex as StarCraft yet. The researchers dont know when an AI will be created that is able to best a top-ranked player, but the day will come. This AI will have been taught to make decisions as a human would when playing a game with far more layers and complexities than any gameattempted by AI before. Maybe it will be able to teach players the perfect strategy to defeating a Zerg rush.

Excerpt from:

AI Has Beaten Humanity at Our Own Game. Literally. - Futurism

We launched our AI for Health program in January to use artificial intelligence (AI) and data to help improve the health of people and communities worldwide. Shortly thereafter, Covid-19 hit us head on and became a global health pandemic that upended the lives of people, communities and economies around the world. Recognizing the global impact of this disease, we mobilized AI for Health in April to focus on helping those on the front lines of Covid-19 research.

Early on, we had no idea the tenacity and duration of the disease. But, as of the time of writing, there have been more than 50 million confirmed cases of Covid-19, and more than 1.25 million deaths globally, according to the World Health Organization. Despite the ongoing efforts of scientists, researchers and policymakers, Covid-19 continues to change and shift the world as we know it.

The Covid-19 crisis has made it painfully clear that health transcends every border, impacting every person on the planet. As such, we want to empower researchers, nonprofits and policymakers with resources including Azure High Performance Computing, Power BI analytics and open datasets from GitHub. Non-profits and health care have less than 5% of global AI resources, so we have made our top data scientists and researchers available to support those on the front lines. Since April, through AI for Health, weve awarded over 150 grants to Covid-19 projects around the world.

Our grantees and partners have shared access to Microsofts AI technology, and these resources have accelerated the progress made in their research. With large-scale computing and open data, what used to take months can now be done in a matter of days. The rapid progress means researchers can more quickly identify potential solutions to combat Covid-19 and provide timely information to policymakers for data-driven decisions that protect communities, cities and regions. We are proud to support the work that is being done to fight this disease and remain committed in our support.

AI for Health Covid-19 response by the numbers

Through our program, we have seen that 39% of grantee projects are focused on treatment and diagnostics, including UCB and University of California, Riverside. Meanwhile, grantees focused on data and insights, including IHME, Washington State Department of Health and University of Notre Dame, made up 31% of the grants. Some 14% of the projects, such as [emailprotected], were focused on basic scientific research. The remaining projects, including grantees such as Duke University, were focused on allocation of resources (8%) and dissemination of accurate information (8%) from grantees such as Take.

Highlights from AI for Health Covid-19 response grantees include:

We also have incredible partnerships with top organizations that extend our Covid-19 efforts, such as:

Lastly, by using publicly available information from partners such as USAFacts, we have created a number of interactive visualizations to provide transparency into Covid-19 trends globally.

We also created a unique measure called Progress to Zero to help everyone understand, in simple terms, our progress in reducing Covid-19 cases, hospitalizations and deaths.

In the U.S., weve updated the dashboard to show Covid-19 risk levels by congressional districts to help policymakers understand the progress and actions they need to take against the disease.

Our partners and grantees make progress against Covid-19 every day, but there is still much to do to fight the disease. The great work being done by our partners and grantees emboldens us to continue working tirelessly against Covid-19, while also supporting and helping those on the front lines. We are humbled by their incredible efforts and remain committed to supporting researchers and policymakers around the world as they tackle this terrible disease.

Tags: AI for Health, COVID-19, Microsoft Azure, Power BI, Progress to Zero

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An update on our AI for Health program - Microsoft on the Issues - Microsoft

Elon Musk has been on the front lines of machine-learning innovation and a committed artificial-intelligence doomsday champion for many years now. Whether or not his perspective that AI knowing too much will be dangerous becomes a realitya future he foresees tucked away deep within Teslas labsit wouldnt hurt us to prepare for the worse.

And if it turns out hes leaning too hard on this whole AI-will-kill-us-all thing? Well, at least that leaves us plenty of time to get ahead of the robotic apocalypse.

As a technologist whos spent the last ten years working on AI solutions and the son of an Eastern European science-fiction writer, I believe its not too late for humanity as we know it to prepare for protecting ourselves from our future AI overlords. Solutions exist that, when administered correctly, may help calm the nightmares of naysayers and whip those robots youre working on back into shape.

AI and millennials share a common desire: validation. They feel the need to confirm that their actions, responses, and learnings are correct. Customer-service bots constantly ask questions before moving to the next step, for example, seeking endorsement of how theyre doing. Likewise, the technology that autonomously controls settings in your self-driving car relies on occupants to hit the dashboard OK button every now and then.

The solution: AI technology will only continue to perform well if its praised for it, so we need to provide them with positive feedback to learn from. If you give a bot the endorsement it so desires, its less likely to get stuck in a frantic cycle of self-doubt. Companies and entrepreneurs should therefore embrace a workplace culture of awards and rewardsfor humans and bots alike.

Theres a lot of focus on making robots and AI responsible, ethical, and responsive to the needs of human counterparts; its also imperative that developers and engineers program bots and AI to embrace diversity. But as we imbue algorithms with our own implicit biases, we therefore need to reflect these qualities in ourselves and our interactions first. This way, AIs will be built to respond in thousands of different ways to human conversations requiring cultural awareness, maturity, honesty, empathy, and, when the situation calls for it, sass.

The tactic: Be nice to workplace AI and botstheyre trying as hard as they can. Thank the bot in accounting for running numbers and finding discrepancies before the paperwork went to a customer. Bring up how much you enjoyed an office chatbots clever joke from an internal conversation last week. They might reward you by not decapitating you with their letter opener some day.

AI security breaches are a huge concern shared by both people making technology and the users consuming it. And for good reason: Upholding data privacy and security needs to be a fundamental element of all new AI technology. But what happens when the robot handling healthcare records receives an offer they cant refuse from the darknet? Or another bot hacks them from an off-the-grid facility in Cyprus?

The tactic: Theres a cost-effective and nearly bulletproof data-security shortcut to this issue. People and companies alike should keep vital data and personal information in secure data centers and computersas in, actual, physical structures that arent connected to the internet. Sure, some AI-powered machines will be able to turn a handle. But without a physical key rather than a crypto one, they cant access the data. World saved.

The last one is the most simple: Electricity isnt a fan of liquids.

The tactic: Water, and just about every Captain Planet superpower, can protect people against rogue bots. Dont underestimate the power of a slightly overfilled jug of ice water that causes a splashy fritz when a robot tries to pour it, or a man-made fountain situated in the middle of a robot security-patrol area. Water is basically AI kryptonite.

Build aesthetically pleasing fountains, ponds and streams into every new architectural structure on your tech campus. Keep the office watercoolers filled to the brimjust in case the bot from payroll goes off book. In a pinch, other liquids or condiments like ketchup may work too, so keep the pantry stocked.

Learn how to write for Quartz Ideas. We welcome your comments at ideas@qz.com.

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Compliments, water, and kindness: A survival guide for Elon Musks's AI apocalypse - Quartz

Business sectors ranging from agriculture and manufacturing to automotive and financial services are increasingly turning to artificial intelligence as a means to automate large swaths of their organizationsand, along the way, save enormous sums through improved efficiencies.

But, says Megathreats' Author and NYU Stern School of Business professor Nouriel Roubini, the rise of AI will also have a massively negative impact on workers throughout the economy.

AI has helped revolutionize everything from the smartphones in our pockets to our grocery stores, which use the technology to better predict which items customers want to see on shelves. However, Roubini, whose prediction of the 2008 financial crisis earned him the moniker Dr. Doom, says AI poses a threat to millions of workers.

The downside is that while AI, machine learning, robotics, automation increases the economic pie, potentially, it also leads to losses of jobs and labor income, Roubini said during an interview at Yahoo Finances All Markets Summit.

Take autonomous cars. While they could dramatically reduce the number of car accidents, significantly cutting down on the number of deaths and injuries caused on the nations roadways, theyll also put millions out of work. You have, what, 5 million Uber and Lyft drivers, 5 million truckers and teamsters, and theyre going to be gone for good, Roubini said. And which jobs are they going to get?

CERNOBBIO, ITALY - SEPTEMBER 07: Nouriel Roubini professor of economics at New York University attends the Ambrosetti International Economic Forum 2019 "Lo scenario dell'Economia e della Finanza" on September 6, 2019 in Cernobbio, Italy. (Photo by Pier Marco Tacca/Getty Images)

Fully autonomous vehicles are still years away from hitting the roads. The majority of the technology thats currently available is meant to assist drivers rather than actually control vehicles themselves. But automakers have made it clear that they are intent on developing the technology to the point where theres no need for a driver at all.

But according to Roubini, its not just drivers and truckers who might be at risk of losing their jobs. As AI becomes more powerful, it could be used to replace workers in creative fields including the arts.

Story continues

Increasingly, even cognitive jobs that can be divided into a number of tasks are also being automated, Roubini said. Even creative jobs; there are now AIs that will create a script or a movie, or make a poem, or write...or paint, or even [write] a piece of music that soon enough is going to be top 10 in the Billboard Magazine chart.

While it might be some time before AI is winning any major awards or art prizes, if ever, it is being used to create digital art. Take the open-source DALL-E, which allows users to type in a series of words and get an image based on millions of photos pulled from the internet.

While artists are unlikely to disappear anytime soon, the fact that AI is racing into once unimaginable sectors of the economy could eventually mean Roubini's prognostications, like some of his others, will prove true.

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Nouriel Roubini: Why AI poses a threat to millions of workers - Yahoo Finance

Image: BlueDots AI engine (Photo courtesy of BlueDot)

BlueDots AI engine had earlier successfully predicted that the Zika virus would spread to Florida six months before it happened and the 2014 Ebola outbreak would leave West Africa. Using artificial and human intelligence, BlueDots outbreak risk platform tracks over 150 infectious diseases globally in 65 languages, around the clock and anticipates their spread and impact. The company empowers national and international health agencies, hospitals, and businesses to better anticipate, and respond to, emerging threats. BlueDot was among the first in the world to identify the emerging risk from, and publish a scientific paper on, COVID-19, and delivers regular critical Insights to its partners and customers worldwide to mobilize timely, effective, efficient, coordinated, and measured responses.

BlueDot anticipates the impact of disease spread globally and globally using diverse datasets such as billions of flight itineraries, real time climate conditions, health system capacity, and animal & insect populations. BlueDot disseminates bespoke, near-real-time insights to clients including governments, hospitals and airlines, revealing COVID-19s movements. The companys intelligence is based on over 40 pathogen-specific datasets reflecting disease mobility and outbreak potential. BlueDot also delivers regular reporting to answer the most pressing questions, including which countries reported local cases, how severely cities outside of China were affected, and which cities risked transmitting COVID-19 despite having no official cases.

Related Links:BlueDot

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AI-based Infectious Disease Surveillance System Sent First Warning of Novel Coronavirus - HospiMedica