Cat Burglar

Cats are known for not really minding their own business, getting their furry paws on just about anything they can.

And it turns out, this makes them effective vectors for DNA evidence, according to a study published last month in the journal Forensic Science International: Genetic Supplement Series.

Researchers collaborating with the Victoria Police Forensic Services Department in Australia found detectable human DNA in 80 percent of the samples collected from 20 pet cats, with 70 percent of the samples strong enough that they could be linked to a person of interest in a crime scene investigation.

"Collection of human DNA needs to become very important in crime scene investigations, but there is a lack of data on companion animals such as cats and dogs in their relationship to human DNA transfer," said study lead author Heidi Monkman, a forensic scientist at Flinders University, in a statement.

"These companion animals can be highly relevant in assessing the presence and activities of the inhabitants of the household, or any recent visitors to the scene."

Here Kitty

One possible takeaway is that cats — and other companion pets like dogs — could be harboring DNA that could help solve a case.

The bigger issue, though, is that pets could introduce foreign DNA that muddles a crime scene, possibly leading to an innocent person being implicated. A pet could be carrying the DNA of a complete stranger, or it might bring the DNA of its owner into a crime scene that they had nothing to do with.

Monkman's colleague and co-author of the paper, Maria Goray, is an experienced crime scene investigator and an expert in DNA transfer. She believes their findings could help clear up how pets might tamper a crime scene by carrying outside DNA.

"Are these DNA findings a result of a criminal activity or could they have been transferred and deposited at the scene via a pet?" Goray asked.

It's a question worth asking — especially because innocent people have been jailed off botched DNA science far too often.

More on DNA evidence: Cops Upload Image of Suspect Generated From DNA, Then Delete After Mass Criticism

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Cats May Be Tampering With Crime Scenes, Scientists Say

Spaceplane Buddy

After launching into orbit roughly three months ago, China's top-secret spaceplane has released a mysterious object, which is now circling the Earth behind it, SpaceNews reports.

There's very little we know about China's "reusable experimental spacecraft," except that it launched atop a Long March 2F rocket back in August. We don't know its purpose, what it looks like, or what cargo it was carrying during launch — but it's an intriguing development, nonetheless, for China's reusable launch platform.

Mysterious Object

The object was released between October 24 and October 31, according to tracking data being analyzed by the US Space Force's 18th pace Defense Squadron.

We can only hazard a guess as to what the mysterious object's purpose is. According to Harvard astronomer and space tracker Jonathan McDowell, it "may be a service module, possibly indicating an upcoming deorbit burn."

Based on the size and weight of payloads Long March rockets usually carry, China's mysterious spaceplane is likely similar to the Air Force's X-37B spaceplane, which is similarly shrouded in mystery and currently on its sixth mission.

We also don't know when the Chinese model will make its return back to Earth, but given recent activity at the Lop Nur base in Xinjiang suggests, it may land there in the near future, according to the report.

It's a puzzling new development for China's secretive spacecraft — but it does raise the possibility of a renewed interest in spaceplanes, a potentially affordable and reusable way to launch payloads into orbit.

More on the spaceplane: China Launches Mysterious "Reusable Test" Spacecraft

The post Chinese Spaceplane Releases Mystery Object Into Orbit appeared first on Futurism.

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Chinese Spaceplane Releases Mystery Object Into Orbit

Observatory Offline

The Atacama Large Millimeter Array (ALMA) Observatory in Chile has been hit with a cyberattack that has taken its website offline and forced it to suspend all observations, authorities there said.

Even email services were limited in the aftermath, illustrating the broad impact of the hack.

Nested high up on a plateau in the Chilean Andes at over 16,000 feet above sea level, ALMA is one of the most powerful and advanced radio telescopes in the world. Notably, ALMA helped take the first image of a black hole in 2019, in a collaborative effort that linked radio observatories worldwide into forming the Event Horizon Telescope.

Thankfully, ALMA's impressive arsenal of 66 high-precision antennas, each nearly 40 feet in diameter, was not compromised, the observatory said, nor was any of the scientific data those instruments collected.

In High Places

What makes ALMA so invaluable is its specialty in observing the light of the cooler substances of the cosmos, namely gas and dust. That makes ALMA a prime candidate for documenting the fascinating formations of planets and stars when they first emerge amidst clouds of gas.

Since going fully operational in 2013, it's become the largest ground-based astronomical project in the world, according to the European Southern Observatory, ALMA's primary operators.

So ALMA going offline is a distressing development, especially to the thousands of astronomers worldwide that rely on its observations and the some 300 experts working onsite. Getting it up and running is obviously a top priority, but the observatory said in a followup tweet that "it is not yet possible to estimate a date for a return to regular activities."

As of now, there's no information available on who the hackers were, or exactly how they conducted the attack. Their motivations, too, remain a mystery.

More on ALMA: Astronomers Think They Found the Youngest Planet in the Galaxy

The post Hackers Just Took Down One of the World's Most Advanced Telescopes appeared first on Futurism.

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Hackers Just Took Down One of the World's Most Advanced Telescopes

Latest Feud

Another day, another Elon Musk feud on Twitter — except now, he's the owner of the social network, and he's beefing with a sitting member of Congress.

The whole thing started innocently enough earlier this week, when firebrand Rep. Alexandria Ocasio-Cortez (D-NY, and better known by her initials, "AOC") subtweeted the website's new owner.

"Lmao at a billionaire earnestly trying to sell people on the idea that 'free speech' is actually a $8/mo subscription plan," the New York Democratic Socialist tweeted in a post that, upon Futurism's perusal, appeared to load only half the time.

Sweat Equity

Not one to be shown up, Musk later posted a screenshot of an AOC-branded sweatshirt from the congressperson's website, with its $58 price tag circled and an emoji belying the billionaire's alleged affront at the price.

In response, Ocasio-Cortez said she was proud her sweatshirts were made by union labor, and that the proceeds from their sales were going to fund educational support for needy kids. She later dug in further, noting that her account was "conveniently" not working and joking that Musk couldn't buy his way "out of insecurity."

Yo @elonmusk while I have your attention, why should people pay $8 just for their app to get bricked when they say something you don’t like?

This is what my app has looked like ever since my tweet upset you yesterday. What’s good? Doesn’t seem very free speechy to me pic.twitter.com/e3hcZ7T9up

— Alexandria Ocasio-Cortez (@AOC) November 3, 2022

Bricked

To be clear, any suggestion that Musk personally had anything to do with any Twitter glitches on AOC's part would seem ludicrously petty. But then again, this is a guy who once hired a private detective to investigate a random critic.

Occam's razor, though, suggests that it was probably AOC's mega-viral tweet that broke the site's notoriously dodgy infrastructure. Of course, that's not a ringing endorsement of the site that Musk just acquired for the colossal sum of $44 billion.

More on Twitter: Twitter Working on Plan to Charge Users to Watch Videos

The post AOC Says Her Twitter Account Broke After She Made Fun of Elon Musk appeared first on Futurism.

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AOC Says Her Twitter Account Broke After She Made Fun of Elon Musk

Jeff Bezos' former housekeeper is suing the Amazon founder for workplace discrimination that she says forced her to literally climb out out the window of his house to use the bathroom.

In the suit, filed this week in a Washington state court, the former housekeeper claimed that she and Bezos' other household staff were not provided with legally-mandated eating or restroom breaks, and that because there was no "readily accessible bathroom" for them to use, they had to clamber out a laundry room window to get to one.

In the complaint, lawyers for the ex-housekeeper, who is described as having worked for wealthy families for nearly 20 years, wrote that household staff were initially allowed to use a small bathroom in the security room of Bezos' main house, but "this soon stopped... because it was decided that housekeepers using the bathroom was a breach of security protocol."

The suit also alleges that housekeepers in the billionaire's employ "frequently developed Urinary Tract Infections" that they believed was related to not being able to use the bathroom when they needed to at work.

"There was no breakroom for the housekeepers," the complaint adds. "Even though Plaintiff worked 10, 12, and sometimes 14 hours a day, there was no designated area for her to sit down and rest."

The housekeeper — who, like almost all of her coworkers, is Latino — was allegedly not aware that she was entitled to breaks for lunch or rest, and was only able to have a lunch break when Bezos or his family were not on the premises, the lawsuit alleges.

The Washington Post owner has denied his former housekeeper's claims of discrimination through an attorney.

"We have investigated the claims, and they lack merit," Harry Korrell, a Bezos attorney, told Insider of the suit. "[The former employee] made over six figures annually and was the lead housekeeper."

He added that the former housekeeper "was responsible for her own break and meal times, and there were several bathrooms and breakrooms available to her and other staff."

"The evidence will show that [the former housekeeper] was terminated for performance reasons," he continued. "She initially demanded over $9M, and when the company refused, she decided to file this suit."

As the suit was just filed and may well end in a settlement, it'll likely be a long time, if ever, before we find out what really happened at Bezos' house — but if we do, it'll be a fascinating peek behind the curtain at the home life of one of the world's most powerful and wealthy men.

More on billionaires: Tesla Morale Low As Workers Still Don't Have Desks, Face Increased Attendance Surveillance

The post Jeff Bezos' Housekeeper Says She Had to Climb Out the Window to Use the Bathroom appeared first on Futurism.

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Jeff Bezos' Housekeeper Says She Had to Climb Out the Window to Use the Bathroom

You know that "research" going around saying humans are going to evolve to have hunchbacks and claws because of the way we use our smartphones? Though our posture could certainly use some work, you'll be glad to know that it's just lazy spam intended to juice search engine results.

Let's back up. Today the Daily Mail published a viral story about "how humans may look in the year 3000." Among its predictions: hunched backs, clawed hands, a second eyelid, a thicker skull and a smaller brain.

Sure, that's fascinating! The only problem? The Mail's only source is a post published a year ago by the renowned scientists at... uh... TollFreeForwarding.com, a site that sells, as its name suggests, virtual phone numbers.

If the idea that phone salespeople are purporting to be making predictions about human evolution didn't tip you off, this "research" doesn't seem very scientific at all. Instead, it more closely resembles what it actually is — a blog post written by some poor grunt, intended to get backlinks from sites like the Mail that'll juice TollFreeForwarding's position in search engine results.

To get those delicious backlinks, the top minds at TollFreeForwarding leveraged renders of a "future human" by a 3D model artist. The result of these efforts is "Mindy," a creepy-looking hunchback in black skinny jeans (which is how you can tell she's from a different era).

Grotesque model reveals what humans could look like in the year 3000 due to our reliance on technology

Full story: https://t.co/vQzyMZPNBv pic.twitter.com/vqBuYOBrcg

— Daily Mail Online (@MailOnline) November 3, 2022

"To fully realize the impact everyday tech has on us, we sourced scientific research and expert opinion on the subject," the TollFreeForwarding post reads, "before working with a 3D designer to create a future human whose body has physically changed due to consistent use of smartphones, laptops, and other tech."

Its sources, though, are dubious. Its authority on spinal development, for instance, is a "health and wellness expert" at a site that sells massage lotion. His highest academic achievement? A business degree.

We could go on and on about TollFreeForwarding's dismal sourcing — some of which looks suspiciously like even more SEO spam for entirely different clients — but you get the idea.

It's probably not surprising that the this gambit for clicks took off among dingbats on Twitter. What is somewhat disappointing is that it ended up on StudyFinds, a generally reliable blog about academic research. This time, though, for inscrutable reasons it treated this egregious SEO spam as a legitimate scientific study.

The site's readers, though, were quick to call it out, leading to a comically enormous editor's note appended to the story.

"Our content is intended to stir debate and conversation, and we always encourage our readers to discuss why or why not they agree with the findings," it reads in part. "If you heavily disagree with a report — please debunk to your delight in the comments below."

You heard them! Get debunking, people.

More conspiracy theories: If You Think Joe Rogan Is Credible, This Bizarre Clip of Him Yelling at a Scientist Will Probably Change Your Mind

The post That "Research" About How Smartphones Are Causing Deformed Human Bodies Is SEO Spam, You Idiots appeared first on Futurism.

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That "Research" About How Smartphones Are Causing Deformed Human Bodies Is SEO Spam, You Idiots

Theres a lot of debate about what Artificial Intelligence really means, and how we should feel about it. Will it transform our world for the better? Will the machines take over? Will it simply make processes we already perform faster and smoother? As Gartner says in A Framework for Applying AI in the Enterprise, The artificial intelligence acronym AI might more appropriately stand for amazing innovations that do what we thought technology couldnt do.

One way and another, were talking about smart machines machines that are trained on existing, historical data, and use that to make accurate deductions or predictions about examples with which theyre presented. The applications are wide-ranging, from medicine to retail to self-driving cars and beyond.

For e-commerce, AI means the ability to deliver capabilities that simply were not possible before. There are two main directions in which this expresses itself:

1) Uncovering trends and audiences: A well-trained e-commerce AI can identify trends of buyer behavior, or interests in new products or experiences and adapt quickly.

2) Personalization: The experience can be tailored to each customer in ways that were not an option when companies had to configure/design the experience for everyone at once (or maybe have a few versions based on geographies). Customers can be offered the information and products they want, when they want them, in the ways that are best suited to them.

Why Ive Come to Love AI

As someone who travels a lot, I often have a fairly complex customer story when I shop online. I might be on a work trip to China, using a proxy to shop on a favorite U.S. store with my credit card, which has a New York billing address, sending something to an office in San Francisco to pick up on my next stop. Theres a good chance Ill be on a mobile device, and since I like to explore new things, Im often buying something of a kind Ive never bought before.

All of this makes me unpopular with e-commerce fraud prevention systems. Ive lost count of the number of times Ive been rejected, or delayed for days while my order is painstakingly reviewed. Sometimes Ive moved on by the time the package finally arrives at the place to which I had ordered it.

The thing is, I get it. I was a fraud prevention analyst myself, back in the time before AI was an option. I know exactly how hard these transactions are to get right, from the human perspective. I know how long it can take to review a transaction, and that as an analyst the tendency is always to play it safe even if that means sending a good customer away.

AI isnt a magic tool, but properly leveraging AI can enable retailers to eat the cake driving their sales upward by creating frictionless, speedy buying experiences for consumers and have it, too be completely protected against online payment fraud.

The 3 Unmatched Advantages of AI-based Fraud Protection Systems

Scale:An AI system can look at 6,000 data points in every transaction, and match them with billions of other transactions to look for patterns, discrepancies, and simple coincidences of events in just a fraction of a second. This means that all fraud decisions can happen 100 percent in real-time, regardless of how much traffic the site is receiving, or whether the fraud team is down with the flu.

Accuracy:In the last year a well-built and trained fraud protection AI has proven repeatedly that it outperforms even the best human reviewers in accuracy. For retailers the reduction in false declines (good customers mistakenly rejected as fraud) means more sales, and happier consumers, and the reduction in fraud chargebacks means lower costs, and lower risk. Beyond that, it enables new business models that were previously considered too risky, like the growing popularity of the try-and-buy model.

Adaptivity:In fraud prevention, one of the great challenges is the speed of learning necessary in order to deal with new fraudulent modaoperandi. If a fraudster finds a new technique that works, it will spread like wildfire and hundreds of fraudsters will attack thousands of retailers at once. An AI-based solution is the only realistic way for retailers to fight fraud together in this highly dynamic environment, combining their efforts and sharing data in a centralized way to prevent fraudsters from abusing one retailer after another. In fact, AI has the potential to actually reverse the asymmetry and push the fraudsters back. From the criminal point of view, if a new method to defraud is blocked almost immediately after it is first conceived and tried out, it isnt worth investing in.

AI is the future of e-commerce fraud prevention. It brings scale, accuracy and adaptivity to improve customer experience, block fraud and increase sales. Some retailers have already started leveraging AI, and theyre gaining a competitive advantage in this highly competitive field. Better fraud prevention is about to become standard. No site can afford to get left behind.

Michael Reitblat is chief executive officer of Forter.

For More Business News From WWD, See:

Amazon, Wal-Mart and Apple Top List of Biggest E-commerce Retailers

Consumer Preferences Reshaping Retail Landscape

Supima Design Competition Set for Sept. 7 at Pier 59 Studios

Read more:

Think Tank: Is AI the Future of E-commerce Fraud Prevention? - WWD

Artificial Intelligence, as a key part of any smart city initiative, can help keep people safe. Yanbu has successfully shown how AI manages some pressing issues amid urbanisation. As one of the biggest cities in Saudi Arabia, Yanbu has applied Huaweis Intelligent Traffic Management system to reduce road fatalities, with the ultimate goal to change the behaviour of road users and thus becoming a smarter, safer and better city.

As urbanisation progresses, innovative technologies are applied to help build or rebuild cities. Governments and administrations are thus looking for more diverse ways to manage increasing complex issues related to peoples livelihood. Meanwhile, the number of vehicles and how well the road systems are developed have become major indicators to reflect the level of urbanisation.

While such developed cities are getting busier, so are their traffic. The World Health Organisation has estimated that about 1.35 million people are killed on roadways all around the world each year. It means an average of 3,700 road fatalities were recorded every day. More than half of these are pedestrians, motorcyclists, and cyclists. In advanced cities, the number is even higher as traffic control is much more complicated than we could imagine.

Saudi Arabia is a forerunner in embracing digital innovations and new technologies. In 2016, the country announced the Vision 2030 programme, aiming to transform into a smart nation with a series of goals to achieve in three key stages. As one of the major industrial cities of the country, Yanbu Industrial City has taken up the same vision and begun its transformation.

Yanbu Industrial City, commonly known as Yanbu in short, is a major Red Sea port city in the Al Madinah Province of western Saudi Arabia. It has a population of some 240,000 in an area of roughly 606 square kilometres. Many of them are foreign expatriates working in the oil refineries and petrochemical industry.

Though most of them are from Asia, there are still large numbers from the Middle East, Europe, and North America. Known for its industry activities, especially when it is the worlds third largest refining centre, the road traffic is usually busy.

Saudi Arabia is a forerunner in embracing digital innovations and new technologies

Like all other stories of advanced development, Yanbu began with a limited number of surveillance cameras at some major interactions. The devices couldnt do more than just capturing still images, not to mention any functions like video recording, zooming, or some sophisticated recognition and search capability.

The set-up was simply not enough to catch up with the rapid changes stemmed from enlarging population and more frequent road commutation. And with limited surveillance, people just didnt care much about breaking traffic laws putting road users in a more dangerous situation.

This is where artificial intelligence (AI) can play a big role. Collaborating with Huawei, Yanbu installed the e-Police system in 2019. The eyes of the system are indeed the 256 high-definition cameras working at 16 major intersections, providing numerous quality images and videos, which allow authority to trace vehicles or impose different controlling measures to keep the whole road network smooth and safe.

The upgraded hardware in the software defined cameras (SDCs) can feed data into the system to further action. The track-and-trace and the occasional real-time controls require more than just sophisticated programming gimmicks.

Not only are the cameras come with improved image quality and 20 TOPs computing power, but the systems are optimised for extreme environments with intelligent light compensation mechanisms.

Pattern recognition is not new to AI, so the system is already capable to run video search based on license plate number and structured vehicle data such as makes and colours, looking to find out the vehicles of interest.

The Intelligent Traffic Management System (ITMS) puts AI into a more intelligent practice by running smart algorithms to automatically identify traffic violations, such as running red lights, crossing lanes, reverse driving, and lane marking infractions, etc. The query response is much faster, running about 100,000 data records and getting a response within seconds.

The precision is also stunning at 50-centimetre lane-level track recognition, with target and tracking recognition rates both over 95 per cent per cent. Traffic incidents can be detected in just eight seconds, with a monitoring distance of 200 metres, covering the major parts of the scene. Violation snapshots and information are then transferred to the central platform for unified storage and query, while the system automatically processes violation cases.

Continued here:

With AI, Yanbu has become smarter and safer - SmartCitiesWorld

Last Chance: Register for Transform, VB's AI event of the year, hosted online July 15-17.

To kick off three days of AI panels, discussions, fireside chats, and networking at Transform 2020, VentureBeat presented the second annual AI Innovation Awards. Drawn both from our daily editorial coverage and the expertise, knowledge, and experience of our nominating committee members, these awards give us a chance to shine a light on the people and companies making an impact in AI.

Amid four nominees in each in our five categories Natural Language Processing/Understanding Innovation, Business Application Innovation, Computer Vision Innovation, AI for Good, and Startup Spotlight the winners have emerged.

Natural Language Processing/Understanding Innovation: StereoSet

Research continues to uncover bias in AI models; StereoSet is a dataset designed to measure discriminatory behaviors like racism and sexism in language models while ensuring that the models otherwise offer strong performance. Researchers Moin Nadeem, Anna Bethke, and Siva Reddy built StereoSet and have made it available to anyone who makes language models. They maintain a leaderboard to show how models like BERT and GPT-2 measure up.

Business Application Innovation: Jumbotail

Jumbotails technology revolutionizes traditional mom & pop stores in India, often known as kirana stores, by connecting them with brands and other high-quality product producers to help them emerge as modern convenience stores. Jumbotail does so without raising the cost to customers, by collecting and mining in real time millions of data points everyday. Thanks to its AI backend, Jumbotail became Indias leading online wholesale food and grocery marketplace, with a full stack that includes integrated supply chain and logistics, as well as an in-house fintech platform for payments and credit. The insights generated and tech developed around this new business model empowers producers and customers, and is poised to extend to other continents.

Computer Vision Innovation: Abeba Birhane and Dr. Vinay Prabhu

In their powerful work, Large image datasets: A pyrrhic win for computer vision?, researchers Abeba Birhane, PhD candidate at University College Dublin, and Dr. Vinay Prabhu, principal machine learning scientist at UnifyID, examined the problematic opacity, data collection ethics, labeling and classification, and consequences of large image datasets. These datasets, including ImageNet and MITs 80 Million Tiny Images, have been cited hundreds of times in research. This paper is under peer review, but already its resulted in MIT voluntarily and formally withdrawing the Tiny Images dataset on the grounds that it contains derogatory terms as categories as well as offensive images, and that the nature of the images in the dataset makes it infeasible to remedy the problems.

AI for Good: Dr. Timnit Gebru

Dr. Timnit Gebru continues to be one of the strongest voices in the AI community fighting racism, misogyny, and other biases not just in the actual technology, but within the wider community of AI researchers and practitioners. Shes the co-lead of Ethical AI at Google and cofounded Black in AI, a group dedicated to sharing ideas, fostering collaborations, and discussing initiatives to increase the presence of Black individuals in the field of AI. Her work includes Gender Shades, the landmark research exposing the racial bias in facial recognition systems, and Datasheets for Datasets, which aims to create a standardized process for adding documentation to datasets to increase transparency and accountability.

Startup Spotlight: Dr. Daniela Braga, DefinedCrowd Corp

DefinedCrowd Corp creates high-quality training data for enterprises AI and machine learning projects, including with voice recognition, natural language processing, and computer vision workflows. The company crowdsources data labeling and more from hundreds of thousands of paid contributors and passes the massive curation on to its enterprise customers. Customers include several Fortune 500 companies. The startups cofounder and CEO, Dr. Daniela Braga, has credentials in speech technology and crowdsourcing dating back nearly two decades, including nearly seven years at Microsoft that included work on Cortana. Shes led DefinedCrowd Corp through several rounds of funding most recently, a large $50.5 million round in May 2020.

We congratulate these winners, and all the nominees, for their important contributions to the field of AI!

Read more:

Announcing the AI Innovation Awards winners at Transform 2020 - VentureBeat

Q2 2020 saw 458 deals worth $7.2 billion

The fortunes of startups that leverage artificial intelligence have soared dramatically in recent years.

These AI-powered startups have seen quarterly investment totals rise from a few hundred rounds and a few billion dollars each quarter to 1,245 rounds and $17.3 billion in the second and third quarters of 2019, according to data from CB Insights. The rise in dollars chasing AI startups has been huge, demonstrating strong venture capital interest in the cohort.

But in recent quarters, the trend has slowed as VC deals for AI-powered startups fell off.

The Exchange explores startups, markets and money. You can read it every morning on Extra Crunch, or get The Exchange newsletter every Saturday.

A new report from the business-data company looking at the second quarter of venture capital results for global AI startups shows historically strong but declining investing rates for the upstart firms. During a pandemic and widespread recession, this is not a complete surprise; other areas of VC investment have also fallen in recent quarters. This is The Exchanges second look at quarterly data in the startup category, something partially spurred by our interest in the economics of the startups that make up the group.

The scale of decline is notable, however, as is the national breakdown of VC investment into AI. (The United States is doing better than you probably guessed, if you have only listened to politicians lately.)

Lets unpack the latest results, determine how investing patterns have changed by stage and examine how different countries compare when it comes to deal and dollar volume for AI-powered startups.

In the second quarter of 2020, global investment into AI startups fell to 458 deals worth $7.2 billion. According to the CB Insights dataset, the deal volume is the lowest for 12 quarters, or since Q2 2017 when 387 investments into AI startups were worth $4.7 billion.

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Investment in AI startups slips to three-year low - TechCrunch

The Asia-Pacific (APAC) region is expected toemerge as the global leader in artificial intelligence (AI) growth, due in large part to widespread government support and policies.

Thats according to new data from GlobalData, which has recorded progress in the region when it comes to leveraging AI to enhance productivity and while countries in the region differ in their approaches, all of them want to leverage their strengths to emerge either as AI innovation drivers or leaders.

Despite their different priorities, countries strive to accomplish four common and prime objectives by leveraging AI: formulate policies for workforce in an automated economy, job creation across emerging sectors which leverage new technologies, build data ecosystem to be leveraged by cross-verticals to foster innovations and intelligent mitigation of impact on workers impacted by adopting AI and risk reduction, says GlobalData lead ICT analyst Sunil Kumar Verma.

AI is not a new technology in the APAC region, as it is for others. Many countries in the region have had significant AI policies in place for at least the last five years.

Japans Artificial Intelligence Technology Strategy seeks to develop the power of AI and harness it for use in industrialisation and manufacturing, while South Korea boasts a US$21 billion budget just for the development of science and technology and AI sectors.

China is currently in the midst of the first development phase of its New Generation of Artificial Intelligence Development Plan, with the second phase to begin in 2025 and the final to commence in 2030.

Indias National Strategy for Artificial Intelligence is focused on five key areas: agriculture, mobility, healthcare, transportation and urban/smart-city infrastructure. Thailands newly created AI ethics guidelines aims to boost the countrys competitiveness on the regional and global stage, as well as push sustainable development.

Certainly, the APAC region is expected to emerge as a major market for AI-led initiatives, since most countries in the region are establishing committees or task forces for creating national AI strategies, which have either been launched or are on the course of being launched in next few years, says Verma.

While some countries in the region may be ahead of others in AI development, there are still many with plans in the works.

Malaysia recently announced the formation of a National Data and Artificial Intelligence (AI) Policy, aimed at making the country an epicentre for AI talent in South-East Asia.

Similarly, its neighbour Indonesia is expected to unveil a national strategy for supporting AI-related technology development, according to GlobalData. The same goes for the Philippines.

Application scenarios across various verticals continue to move from divided to a unified and customised methodology, says Verma.

The need for digital governance and collaborative approach with the technology companies would further facilitate in the scaling up of enterprises and government priorities in the AI industry chain.

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APAC will be the 'epicentre' of global AI development - report - IT Brief Australia

Wally Kankowski owns a pool repair business in Florida and likes 12 creams in his McDonalds coffee each morning. What he doesnt like is the way the company is pushing him to place his order via a touchscreen kiosk instead of talking with counter staff, some of whom he has known for years. The thing is knocking someone out of a job, he says.

Wally is one of several humans who discuss the present and future of workplace automation in the seventh installment of the Sleepwalkers podcast, which offers an atlas of the artificial intelligence revolution. The episode explores how work and society will change as AI begins to take over more tasks that people currently do, whether in apple orchards or psychiatry offices.

Some of the portents are scary. Kai-Fu Lee, an AI investor and formerly Googles top executive in China, warns that AI advances will be much more disruptive to workers than other recent technologies. He predicts that 40 percent of the worlds jobs will be lost to automation in the next 15 years.

AI will make phenomenal companies and tycoons faster, and it will also displace jobs faster, than computers and the internet, Lee says. He advises governments to start thinking now about how to support the large numbers of people who will be unable to work because automation has made their skills obsolete. Its going to be a serious matter for social stability, he adds.

The episode also looks at how automation could be designed to assist humans, not replace themand to narrow divisions in society, not widen them.

Toyota is working on autonomous driving technology designed to make driving safer and more fun, not replace the need for a driver altogether.

George Kantor from Carnegie Mellon University describes his hope that plant-breeding robots will help develop better crop varieties, easing the impacts of climate change and heading off humanitarian crises. Better seeds means better crops, and that could ultimately lead to a more well-nourished world, he says.

Kantor and Lee both argue that thinking about the positive outcomes of automation is necessary to fending off the bad ones. Whether we point at a future that is utopia or dystopia, if everybody believes in it, then it becomes a self-fulfilling prophecy, Lee says. Id like to be part of that force which points toward a utopian direction, even though I fully recognize the possibility and risks of the negative ending.

More Great WIRED Stories

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Will AI Take Your Jobor Make It Better? - WIRED

This week, as the heads of four of the largest and most powerful tech companies in the world were called before a virtual congressional antitrust hearing to answer inquiries into how they built and run their respective behemoths, you could see that the bloom on the rose of Big Tech has faded.

Facebooks Mark Zuckerberg, once the rascally college dropout boy genius you loved to hate, still doesnt seem to grasp the magnitude of the problem of globally destructive misinformation and hate speech on his platform. Tim Cook struggles to defend how Apple takes a 30% cut from some of its app store developers revenue a policy he didnt even establish that is a vestige of Apples mid-2000s vise grip on the mobile app market. The plucky young upstarts who founded Google are both middle-aged and have stepped down from executive roles, quietly fading away while Alphabet and Google CEO Sundar Pichai runs the show. And Jeff Bezos wears the untroubled visage of the worlds richest man.

Amazon, Apple, Facebook, and Google all created tech products and services that have undeniably changed the world, some in ways that are undeniably good. But as these tech titans moved fast and broke things, they also largely excused themselves from asking difficult ethical questions, from how they built their business empires to the impacts their products and services have on the people who use them.

As AI continues to lead the next wave of transformative technology, skating over these difficult questions is a mistake the world cant afford to repeat. Whats more, AI technologies wont actually work properly unless companies address the issues at their heart.

Smart and ruthless was the tradition of Big Tech, but AI requires people to be smart and wise. Those working in AI have to not only ensure the efficacy of what they make, but holistically understand the potential harms for people AI tech impacts. Thats a more mature and just way of building world-changing technologies, products, and services. Fortunately, many prominent voices in AI are leading the field down that path.

This weeks best example was the widespread reaction to a service called Genderify, which promised to use natural language processing (NLP) to help companies identify customers gender using only their name, username, or email address. The entire premise is absurd and problematic, and when AI folks got ahold of it to put it through its paces, they predictably found it to be terribly biased (which is to say, broken).

Genderify was such a bad joke that it almost seemed like some kind of performance art. In any case, it was laughed off the internet. Just a day or so after it was launched, the Genderify site, Twitter account, and LinkedIn page were gone.

Its frustrating to many in the field that such ill-conceived and poorly executed AI offerings keep popping up. But the swift and wholesale deletion of Genderify illustrates the power and strength of this new generation of principled AI researchers and practitioners.

The burgeoning AI sector is already experiencing the kind of reckoning Big Tech is only facing after decades. Other recent examples include an outcry over a paper that promised to use AI to identify criminality from peoples faces (really just AI phrenology), which led to the paper being withdrawn from publication. Landmark studies on bias in facial recognition have led to bans and moratoriums on the technologys use in several U.S. cities, as well as a raft of legislation to eliminate or combat its potential abuses. Fresh research is finding intractable problems with bias in well-established data sets like 80 Million Tiny Images and the legendary ImageNet and leading to immediate (if overdue) change. And theres more.

Although advocacy groups play a role in pushing for changes and posing tough questions, the authority for such inquiry and the research-based proof is coming from people inside the field of AI ethicists, researchers looking for ways to improve AI techniques, and actual practitioners.

There is, of course, an immense amount of work to be done and many more battles ahead as AI fuels the next dominant set of technologies. Look no further than problematic AI in surveillance, military, the courts, employment, policing, and more.

But seeing tech giants like IBM, Microsoft, and Amazon pull back on massive investments in facial recognition is a sign of progress. It doesnt actually matter whether their actions are narrative cover for a capitulation to other companies market dominance, a calculated move to avoid potential legislative punishment, or just a PR stunt. For whatever reason, these companies acknowledged the value of slowing down and reducing damage rather than continuing to move fast and break things.

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AI Weekly: Big Techs antitrust reckoning is a cautionary tale for the AI industry - VentureBeat

A number of articles have been published recently predicting that the largest cyberattack in history is destined to happen soon, one of the main underlying factors behind this assertion is the overnight explosion of the enterprise attack surface and large increase in noted hacks that weve witnessed during the COVID-19 Pandemic.

As an example, a recent Forbes article by Stephen McBride claims that, The Largest Cyberattack In History Could Happen Within Six Months. Although it is entirely possible and even potentially probable that the largest cyber security breach in history is right around the corner, it is also entirely avoidable. Solutions to protect networks in the changing enterprise cyber landscape we are witnessing due to events like COVID-19 do exist, but they are not your typical legacy tools utilizing AI that is based on human labeling or Supervised Learning Algorithms which most companies are relying on for their cybersecurity now.

According to McBride, switching to remote work, with employees now sharing computers with their loved ones, who are using them for everything from zoom get-togethers to school work, on such a massive scale has caused the attack surface to grow by an astounding 500 percent, virtually overnight. Before the pandemic, remote employees would have specially secured laptops and other devices, but it has been impossible, due to the quick transition, to effectively secure corporate devices now that the vast majority of employees are working from home.

As a result, hacking, phishing and ransomware attempts have increased substantially since the start COVID-19. This is due to more entry points for hackers than ever before because of our remote work situation.

With an overwhelming shortage of cybersecurity talent in the market before the pandemic struck, its completely infeasible to believe that hiring out of this situation is an option. Luckily the advent of solutions utilizing advanced AI may be the cure we need.

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The word AI tends to scare people off due to overuse and under-delivery, but by finding and using valuable and effective artificial intelligence based cybersecurity solutions that dont add to the workload of your already overworked SOC team, but instead automate and increase efficiency, enterprises can solve this problem. AI is the only viable solution to the potential D-Day style attack were facing in the near future.

Traditional cybersecurity systems are based on signatures. If you assume that any computer with endpoint software installed on it has a probability of failure, suddenly that probability is massively increased by an order of magnitude because it is enough for just one computer to become a host for the whole companys network to potentially get compromised.

Endpoint protection is not enough and is futile in this current context because now the probability that the network is going to get infected is much higher.

When we are not working remotely the situation is very different because everyone is in a sort-of envelope, but now everyone is out and their network habits are completely different than before, with much higher rates of online shopping and visiting malicious sites pertaining to COVID-19.

In some sense the only solution to the coming attack, because its just a game of probabilities, is to gain an understanding of all network traffic or what is being sent and received over the wire and monitor for abnormalities.

For example, if an IP has behaved oddly on the inbound side, maybe moved laterally in a strange way and then exported something out, and if thats usually not what that user should be doing, you could take a look and find traces of these actions on the wire, but not on the endpoint.

There is no reason to diminish the importance of endpoint solutions, you still want to protect and monitor endpoints as much as you can, but in this situation because of the fast and overwhelming growth of the attack surface users need an additional solution which monitors the interaction on the network. The probability that one of your computers will get infected and gain access to the rest of the network increased exponentially along with the attack surface, leaving enterprises more vulnerable than ever before.

Its easy to come to the conclusion that we will be seeing an event of great magnitude very soon in the cybersecurity sphere. When is anybodys guess, but there are things we can do to prevent and mitigate it when it happens. Its almost like with the pandemic, if a local government does a great job of shutting things down, keeping people indoors, and implements contact tracing the pandemic is not going to spread as quickly and do as much damage. Like that same local government, your security team can do things now to prevent and contain a coming attack, for example implementing an AI based solution to monitor and trace potential weak points in your network and identify attacks in real time.

I believe it is probable that we will see a serious, potentially catastrophic attack in the next six months, but if enterprises are proactive about implementing these types of technologies, and employing Unsupervised or Self-Supervised AI based cybersecurity systems, we would see a drastic decrease in the probability of this big attack.

Endpoint protection may no longer be enough with more people doing online shopping and visiting malicious sites related to COVID-19. #security #respectdata Click to Tweet

The idea is really contact detection and prevention. If one computer gets breached or infected we want to keep it from infecting the whole network. A team of cybersecurity professionals who has to sift through thousands of false positive alerts might spend hours or even days trying to find a breach when alerted, and every second that passes means the network becomes more and more infected, whereas an advanced AI system can monitor the network, sift through alerts, and surface a potentially deadly attack in seconds. If were going to stop the largest cyber attack of all time before it does catastrophic damage, we need to be armed with the most intelligent and advanced tools possible.

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The Largest Cyber Attack of All Time Is Coming. And AI Could Help Stop It. - CPO Magazine

In Brief A new image generator created as part of the pix2pix project can transform a crude doodle of a face into a more realistic looking image. It's powered by a next-level machine learning technique called generative adversarial networks, which could help us create machines that have a better understanding of the world. Ugly Doodles

Machine learning is, perhaps, the most common platform for existing artificial intelligence (AI) networks. The basic idea is that an AI can be taught to reach its own decisions throughexposure to usually huge datasets. Its similar to how we canlearn something by seeing it again and again.

While machine learning does an almost perfect job of classifying images, it seems to fumble a bit with generating them. The latest example is an image generator shared as part of the pix2pix project. Itsrecently been making the rounds on social media, sowe tried it out, and heres the result:

The end results of the generator are either abstract or hideous, depending on your perspective. But it is undeniably able toturn a simple and arguably poor doodle into afar more realistic-looking image.

Like so much of the internet, the pix2pix projectstarted with cats. The same mechanics applied: a user drew an image, and the algorithm transformedit into a (relatively) more realistic-looking cat.

For their generators, the developers used a next-generation machine learning technique called generative adversarial networks (GANs). Essentially, the system determines whether its own generated output (in this case, the realistic face) is real (looks like one of the images of actual faces from the dataset used to train it) or fake. If the answer is fake, it then repeats the generation process until an outputted image passes for a real one.

The pix2pix projects image generator is able to take the random doodles and pick out the facial features it recognizes using a machine learning model. Granted, the images the system currently generates arent perfect, but a person could look at them and recognize an attempt at a human face.

Obviously, the system will require more training to generate picture perfect images, but the transition from cats to human facesreveals an already considerable improvement. Eventually, generative networks could be usedto create realistic-looking images or even videos from crude input. They could pave the way for computers that better understand the real world and how to contribute to it.

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Draw a Doodle of a Face, and Watch This AI Image Generator Make It Look More Human - Futurism

Artificial intelligence has slowly moved from a science fiction topic to something that has a huge impact on peoples livelihoods and the world around us. Still, its common for many companies to use AI as a simple buzzword. But it would be a mistake to think that AI is just jargon though.

At this point, the power of artificial intelligence is growing exponentially. As such, look for AI-driven technologies to make a massive impact over the next decade. That will, of course, have a major effect on the stock market. Right now, many tech investors are primarily focused on cloud and software-as-a-service stocks. And with good reason those have been booming.

But with all the data accumulating online, its only a matter of time until more powerful AI turns that data into new understanding and new profits. Heres seven stocks to harness the power of artificial intelligence in your portfolio.

Source: Piotr Swat / Shutterstock.com

Alphabet (NASDAQ:GOOG, NASDAQ:GOOGL) is far from a pure play on artificial intelligence. The company still pays the bills with search advertising, after all. And its dominant Android operating system will continue reaping rewards for Alphabet for many years to come.

That said, if you want a company that undoubtedly will be a major part of artificial intelligence in coming years, look no further. Google launched Google AI in 2017 as a separate entity to show the importance of AI to the companys future.

Already, Alphabet has made moves with DeepMind, its roughly 700-employee division that has achieved things such as beating humans at the board game Go. Recently, Alphabets artificial intelligence topped humans in deciphering ancient Greek text. Turning to more practical matters, Google is using AI to help customers solve important although perhaps mundane tasks such as filling in online forms automatically or responding better and faster to voice-inputted questions.

All this plays back into Alphabets core products, as well. The better Google Search is, for example, the more advertising revenue Google will be able to bring in. Artificial intelligence is at the core of GOOGL stock, and its further advances in the field should help power profits across the companys other lines of business.

Source: Laborant / Shutterstock.com

International Business Machines (NYSE:IBM) isnt having a great year. Its not had a great past five years in fact. IBMs stock price has stagnated as the company has struggled to adapt to a changing tech market. The companys hugeRed Hat acquisition will be critical in trying to get its cloud division going again.

That said, while IBM has had its struggles, you cant deny its excellent positioning in AI. IBMs Watson is one of the most exciting applications. Not only does it have its high-profile appearances, such as competing in game shows and chess matches, it is also being used for chat applications, healthcare, weather prediction and assisting teachers.

As Watson is able to answer questions in natural language, the range of potential uses is immense. And IBM is constantly upgrading Watsons capabilities. Just this week, it added new functionality to Watson Assist, Watson Discovery and a drift function that can show when the AIs prediction is moving away from actual real world results.

Some investors have grown fed up with IBM, and its not hard to see why. In a raging bull market IBM stock has offered little besides its dividend. But dont let bad past performance make you write off the companys technology. Watson could emerge as a leading AI asset in coming years.

Source: Pe3k / Shutterstock.com

Like IBM,Nvidia (NASDAQ:NVDA) has had a rather forgettable past 12 months. NVDA stock peaked at $290 a share last year, and is almost a full $100 below that now, even after the recent rally. Investors havent necessarily made a mistake either. Nvidia has faced plenty of pressure between the fall in crypto-related demand, the trade war and a general glut of inventory in some of its main product lines.

This severe-but-temporary weakness in main business lines is giving investors a chance to get in on Nvidias artificial intelligence story at a reasonable price, however.

Nvidias deep learning AI offers a great deal of promise. For now, it focuses on self-driving vehicles a major strength for Nvidia in general. Over time, however, Nvidia is aiming to create an ecosystem based around Nvidia GPUs where developers can combine many deep learning concepts into their AI solutions that span various industries. Nvidia will need to demonstrate more success and revenues from automotive AI-driven sales first. But if and when it does, expect investors to take notice and bid NVDA stock back up again.

Source: Katherine Welles / Shutterstock.com

Texas Instruments (NASDAQ:TXN) has some similarities with the previous pick, Nvidia. Both are diversified semiconductor companies that are making a big push in the automotive market. Texas Instruments already has a huge position in autos, via its sensors and processing chips that convert real-world conditions into digital data. That position, along with its wide array of analog chips, has given Texas Instruments one of the most profitable and sustainable businesses in the semiconductor space.

In particular, for those looking for AI stocks, consider Texas Instruments. Its Sitara family of ARM processors enable deep learning. Sitaras have been on the market for a few years now and clients have already incorporated them into applications ranging from smart snow goggles to video players, and Lego programmable robots. Whats most exciting is Texas Instruments place in Googles Nest, a smart thermostat capable of becoming more aware over time as it acquires more data.

Even the giants stumble, however. TXN stock fell sharply following Tuesdays earnings report where the company low-balled forward guidance. That gives investors with a long-term horizon an opportunity. Following the earnings decline, TXN stock is selling at just 24x forward earnings. Thats the cheapest its shares have been in awhile and makes for a nice entry point.

Source: Piotr Swat / Shutterstock.com

CrowdStrike (NASDAQ:CRWD) has had an eventful few months. The company completed its initial public offering in June, and CRWD stock started trading around $60. Traders soon bid it up to $100 on the back of strong earnings and jaw-dropping revenue growth rates.

Things went south in a hurry though. People have been dumping SaaS stocks since September, and Crowdstrike has gotten hit hard. Some analysts are worried about political concerns as well. CrowdStrike helped provide security services to the Democratic National Committee following its 2016 hack. The led to President Donald Trump calling out CrowdStrike during his call with Ukraine. CrowdStrikes CEO said it was a surprise that the company has been dragged into the political circus and that the firm is only focused on customers security.

Regardless, all this noise has created a strong opportunity to pick up a leading AI stock on a steep discount. While plenty of companies do cybersecurity, CrowdStrike has an innovative approach. Its software uses deep machine learning to not only identify threats, but also learn from each attempted attack. Over time, CrowdStrikes AI evolves and becomes more sophisticated as it encounters more and more hacking attempts. Combine that with multiple endpoint security CrowdStrike can defend a user across all their devices and the company has a large and growing lead against other cybersecurity firms. With CRWD stock down nearly 50% since its recent highs, this AI stock is on sale.

Source: Peteri / Shutterstock.com

Not surprisingly, the other huge cloud hosting company is also a leading AI play. Thats right, Microsoft (NASDAQ:MSFT) has a major position in the future of artificial intelligence as well. While Microsoft has missed other major computing trends in the past, under current management, it seems to be much more adept at seeing the future rather than reacting as change happens.

Whats that mean for Microsoft and AI specifically? Good question. Microsoft has aimed to give its customers the first access to human-equivalent level intelligence across a growing number of fields. Microsoft claims to have achieved this sort of AI parity in machine language translation, object detection and speech recognition. Over time, Microsoft expects to be able to broaden its reach to more and more crucial fields.

Of course, rivals like Google would dispute Microsofts leadership in these capabilities. However, Microsoft has a huge advantage over its competition due to Azure. It has access to more data than anyone other than, arguably, Amazon (NASDAQ:AMZN). This gives Microsofts scientists a huge treasure trove of information to process. Its not hard to imagine Microsofts AI becoming the dominant player in coming years.

Source: Jonathan Weiss / Shutterstock.com

A credit card issuer probably isnt the first place youd go looking for artificial intelligence investments. Make no mistake, though, there will be big winners from smart AI applications outside of tech companies. Look no further than Discover Financial Services (NYSE:DFS).

Earlier this year, Discover announced that it has partnered withZest AI (formerly known as ZestFinance) to create a leading credit scoring platform. Through AI the companies are creating a system that will automatically score consumers by credit riskiness and learn from the models underwriting successes and failures over time. Using a growing pile of historical data, a sophisticated AI algorithm should be able to find certain patterns and trends that humans have so far overlooked.

Discovers CEO minced no words in explaining why the company is making such a huge push into AI credit modeling. He said, Banks that fail to invest in machine learning will end up fundamentally uncompetitive in a couple of years. For investors in DFS stock, you could be surprised by the benefits as Discover pulls ahead of less technologically savvy rivals. At less than 9x forward earnings, the price is certainly right to invest in this financial firm.

At the time of this writing, Ian Bezek owned IBM, TXN, CRWD and DFS stock. You can reach him on Twitter at @irbezek.

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7 AI Stocks to Buy to Profit from the Recent Tech Correction - Investorplace.com

Luckily, foretelling such dire consequences may help doctors to stave them off. "Predicting the future of a patient is useful because it may enable doctors to tailor treatments to the individual," lead author Dr. Luke Oakden-Rayner told the University of Adelaide. "Instead of focusing on diagnosing diseases, the automated systems can predict medical outcomes in a way that doctors are not trained to do, by incorporating large volumes of data and detecting subtle patterns."

For this study, the system was looking for things like emphysema, an enlarged heart and vascular conditions like blood clotting.The deep learning system was trained to analyze over 16,000 image features that could indicate signs of disease in those organs. Machines have become adept at it surprisingly quickly, even though it's "something that requires extensive training for human experts," said Oakden-Rayner.

The goal was not to build a grim diagnostic system, and the AI only analyzed retrospective patient data. Rather, the team is looking to lay the groundwork for algorithms that can diagnose your overall health, rather than just spotting a single disease. They also want to "motivate the use of routinely collected, high resolution radiologic images as sources of high quality data for precision medicine," according to the paper. In other words, they're encouraging more scans as a way to improve the results of future diagnostic systems.

"Our research opens new avenues for the application of artificial intelligence technology in medical image analysis, and could offer new hope for the early detection of serious illness, requiring specific medical interventions," says Oakden-Rayner.

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AI can predict if you'll die soon by examining your organs - Engadget

SAN FRANCISCO, July 21, 2020 /PRNewswire/ --Sitecore, the global leader in digital experience management software, released version 3.4 of Sitecore Content Hubtoday, offering new robust, streamlined and scalable capabilities to help brands accelerate their digital transformations.

Brands today manage thousands of digital assets to create engaging digital experiences for their customers. Leading organizations are quickly realizing the necessity of augmenting their content management with world-class digital asset management capabilities to support the current content explosion and improve their marketing efficacy and efficiency in the process. Sitecore Content Hub version 3.4 offers enhanced Digital Asset Management (DAM) capability with leading edge innovations in artificial intelligence (AI) and video capabilities, in addition to improving workflows and ease of use with extended integration to third-party solutions.

A recent study by marketing advisory firm Econsultancy1 found that 65% of marketers spend more of their time creating content than any other activity supporting digital campaigns.To offer time-savings, Sitecore Content Hub 3.4 adds Content AI to analyze image similarity so brands have instantaneous access to alternative images in the DAM, with more options made immediately available to fit their particular need. Marketers can then choose to reuse or repurpose these rather than create new onessaving their company time and money. For example, when using a photo of a family on the beach, Content Hub will recognize the makeup of the photo and offer similar images of groups on the beach, reducing content creation timelines and expense for marketing teams.

Consumption of video content has grown and continues to grow exponentially, with 85% of U.S. internet users saying they watch online video content,2 and viewers report spending 59% more time watching online videos in 2019 than they had three years before.3 To help brands manage their video content more effectively, Content Hub version 3.4 also includes the ability to automatically generate metadata as well as transcripts for video using AI analysis from Microsoft Azure Cognitive Services. In addition, video management capabilities now include support for time- and range-based annotation, cropping and subtitles, giving marketers more automated capabilities to make their videos more consumable by different audiences.

"Our vision has always been to streamline work and take the tedium out of the creative process for our customers," said Tom De Ridder, CTO, Sitecore. "With version 3.4 of Content Hub, we've taken several massive steps to further drive this mission with new capabilities, enhancements and integrations in a SaaS product that makes it easier for all content stakeholders in a distributed environment to work together to solve the content crisisall in a single solution that distributes content to all channels."

Recent research from SoDA found that 95% of marketers say producing and publishing personalized digital content more quickly is a priority and 39% say manual processes are holding them back. 4 Additional workflow and ease-of-use functionality new to version 3.4 helps to support these demands, including smarter navigation, mass-edit templates, and on-the-fly tagging. Now, Marketing Resource Management and Content Marketing Platform (MRM and CMP) integration empowers DAM users to manage both agile workflows of content items and timeline-based project management workflows from a single location.

Content Hub 3.4 also improves workflow and ease-of-use for DAM users who use Adobe Creative Cloud. With a DAM search panel, users can upload, check in, and check out assets from InDesign, Photoshop, and Illustrator. They can preview work-in-progress within InDesign documents directly in the DAM without packaging, and package finished assets directly into the DAM from InDesign.

CHILI publisher integration

Producing graphics the traditional way can be fraught with challenges for today's marketer. It takes time, requires money, and involves risk. Marketers face brand compliance and governance challenges, scale challenges, and time-to-market challenges.

With Content Hub 3.4, enhanced Web to Print capabilities with tight integration to CHILI publisher are now available to simplify and automate graphic production across digital and print publishing. This integration connects Content Hub data and assets to CHILI Smart Templates that enable preset customizable elements while embedding brand identity guidelines. Users can now self-service anywhere in the world with just a browser to deliver customized, brand-compliant, and ready-to-use printed assets at scale.

Javascript development kit

And to make it easier for assets and content to flow to and from other applications in the marketing technology stack, Sitecore has also released a Javascript SDK, making Content Hub more extensible with accelerated and minimized development and integration efforts for third-party solutions.

To learn more about Content Hub, please visit Sitecore.com. Developers interested in the new Content Hub Javascript SDK can find more details available here.

About Sitecore

Sitecore delivers a digital experience platform that empowers the world's smartest brands to build lifelong relationships with their customers. A highly decorated industry leader, Sitecore is the only company bringing together content, commerce, and data into one connected platform that delivers millions of digital experiences every day. Leading companies including American Express, ASOS, Carnival Cruise Lines, Kimberly-Clark, L'Oral, and Volvo Cars rely on Sitecore to provide more engaging, personalized experiences for their customers. Learn more atSitecore.com.

Sitecore and Sitecore Content Hub are registered trademarks or trademarks of Sitecore Corporation A/S in the USA and other countries. All other brand names, product names or trademarks belong to their respective holders.

Sources: EConsultancy1, Statisa2, Limelight Networks3, SODA4

Contact Shannon Lyman Sr. Director, Communications at Sitecore [emailprotected]

SOURCE Sitecore

http://www.sitecore.net

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Sitecore Leverages AI for Smarter Management of Images and Video, Reduces Content Creation Pressure and Saves Brands Time and Money With New Sitecore...

New carbon emission tracking technology will quantify emissions of greenhouse gas, holding the energy industry accountable for its CO2 output. Backed by Google, this cutting-edge initiative will be known as Climate TRACE (Tracking Real-Time Atmospheric Carbon Emissions).

Advanced AI and machine learning now make it possible to trace greenhouse gas (GHG) emissions from factories, power plants and more. By using image processing algorithms to detect carbon emissions from power plants, AI technology makes use of the growing global satellite network to develop a more comprehensive global database of power plant activity. Because most countries self-report emissions and manually compile results, scientists often rely on data that is several years out of date. Moreover, companies often underreport carbon emissions, rendering existing data inaccurate.

Climate TRACE addresses these issues by partnering with other leaders in sustainability practicesincluding former U.S. Vice President Al Gore, WattTime, CarbonPlan, Carbon Tracker, Earthrise Alliance, Hudson Carbon, OceanMind, Rocky Mountain Institute, Blue Sky Analytics and Hypervine. The Climate TRACE coalition aims to help countries in meeting Paris Agreement targets and place the world on a path to sustainability.

The carbon tracking efforts of Climate TRACE will result in a conglomeration of data to be made available to the public, which may assist plaintiffs in climate liability cases and lead to enhanced enforcement of environmental laws. The slow pace of international climate negotiations has led to an increase in lawsuits demanding action on global warming. As of this year, 1,600 climate-related lawsuits have been filed worldwide, including 1,200 lawsuits in the United States alone. Currently, climate liability cases rely predominantly on a database run by the Carbon Disclosure Project and the Climate Accountability Institute. This database, initially released in 2013 as the Carbon Majors Report, attempts to link carbon pollution to emitters. The 2013 report pinpointed 100 producers responsible for 71% of global industrial GHG emissions. Its 2017 report, for instance, indicated that 25 corporate and state producing entities account for 51% of global industrial GHG emissions. While the Carbon Majors Report has assisted in determining the largest carbon emitters on a global scale, Climate TRACE will provide more frequent and accurate monitoring of pollutants.

Data from Climate TRACE will also help hold countries accountable to the Paris Climate Agreement, expanding upon European efforts to monitor global warming. Early last year, a space budget increase put Europe in the lead to monitor carbon from space using satellite technology. In December 2019, member governments awarded the European Space Agency $12.5 billion. This substantial increase allowed the ESA to devote $1.8 billion to Copernicus, a satellite technology program which continuously tracks Earths atmosphere. The program allowed Europe to analyze human carbon emissions regularly. With Copernicus, the ESA became the only space agency to monitor pledges made under the Paris Climate Agreement. The Climate TRACE coalitionwith members spanning across three continentswill make carbon monitoring a global effort.

Climate TRACE has created a working prototype that is currently in its developmental stages. The coalition intends to release its first version of the AI project by the summer of 2021.

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Artificial Intelligence and Satellite Technology to Enhance Carbon Tracking Measures - JD Supra

Download the Collaboration Market Guide

Video collaboration has emerged as one of the most crucial tools in our communication kit for the modern workplace. As trends like remote and distance working continue to gain speed, video collaboration ensures that team members can maintain crucial connections at a distance. Not only can we communicate freely through video collaboration, but we can also access essential aspects of human connectivity that cant be unlocked with other types of communication, such as body language.

As the demand for video collaboration technology has increased, so too has the need for innovative new tools and features that make this method of discussion more appealing. According to Frost and Sullivan, AI is beginning to bring more reliability and productivity into the meeting room. Virtual assistants can take notes or schedule follow-up meetings with nothing but a voice command.

At the same time, artificial intelligence and bots can transcribe and translate conversations between global team members in seconds, while making the meeting room safer with tools like biometric security. So, whats driving video collaboration forward in 2020?

Artificial intelligence is beginning to play a role in various aspects of our lives. In the office, a voice-enabled smart assistant can arrange meetings and take notes for us in seconds. In the meeting room, AI-driven devices can make sessions run more efficiently by automating tasks like rescheduling calls or sending crucial notifications. AI assistants can even suggest which resources or documents a person may need for a meeting and make them available to access when the conference begins.

Artificial intelligence with natural language processing also improves video collaboration applications in various ways. It can facilitate the automatic transcription or translation of meetings, ensuring that people from around the world can collaborate more efficiently. AI can also improve audio quality by automatically detecting echo and minimizing background noise.

Some businesses are even bringing AI into the video collaboration space with computer vision, helping to frame meeting participants and ensure that everyone can appears clearly. Some tools can even ensure that whiteboards and presentation screens always get enough attention in a video.

Its not just the arrival of new bots and assistants in the collaboration space thats changing the way that we work together. Video collaboration is also affected by the transformation of the meeting spaces that we work in. Ad-hoc huddle rooms and more impromptu spaces are overtaking large board rooms and complicated video meeting environments are being quickly replaced by.

Huddle rooms allow employees to tap into high-quality meeting environments within a matter of minutes. There are video collaboration software and hardware kits that come with plug and play functionality today, so that team members can instantly start a meeting, without having to wait for set-up help from an IT expert.

Advanced and flexible new meeting room spaces ensure that employees from all backgrounds can still enjoy efficient and effective collaboration experiences. Anywhere can now become a meeting space, from a shared environment in a co-working space, to a home environment, or a small spare office in the workplace. AI can even make these spaces more effective by enabling things like blurred backgrounds that eliminate distractions in a busy setting or using noise features to improve the clarity of a users voice.

The video conferencing market alone will be worth around $6.7 billion by 2025.

While the world is beginning to see the benefits of video collaboration at an incredible scale, its important to remember that any new technology does come with challenges. For instance, now that team members can tap into a video meeting from anywhere in the world, there are security and compliance issues to consider.

Business leaders will need to ensure that the right policies are in place to stop team members from signing into dangerous applications and websites using business credentials. VPNs and other security measures may need to be implemented for those who want to join a meeting from an environment with a less secure connection. Just like bringing external devices into the office environment requires a BYOD policy, taking video collaboration outside of the traditional office will require its own protection measures. Business leaders will need to:

Embracing the age of visual communication means making it as easy as possible for your team members to access the tools that they need to interact with. Choosing video collaboration tools that offer things like one-click join facilities, and the ability to dial in from any phone could be an excellent way to get started. Some companies are even using strategies like Microsoft Teams with Direct Routing to ensure that their employees can get all the benefits of their favourite collaboration tools, without having to switch to a new phone service provider.

However, theres more to consider when it comes to ensuring adoption than simplicity. Businesses will also need to think about how theyre going to ensure that their video collaboration strategy works with the rest of the tools that their teams use every day.

Interoperability is often a crucial consideration in ensuring adoption. Creating an environment where your employees can start a video meeting naturally from within the applications that theyre using to connect with coworkers already will make it much easier for video to become a part of your culture.

Most business leaders and technology experts agree that the future is in visual communications. From a collaboration perspective, video gives team members an excellent way to work with each other face-to-face, no matter where they are. In a time when remote and distance working are becoming more popular, video is the only way to preserve the crucial intimate human connections and facial expressions that exist in real-life interactions.

However, preparing for the implementation of visual communication and collaborations in your business means considering a range of things, from how youre going to ensure adoption, to how you can maintain security and compliance.

If you havent started planning for a visual future yet, now is the time to start.

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The Collaboration Market: The Role of AI and Disruption - UC Today