Cats May Be Tampering With Crime Scenes, Scientists Say

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Cats, ever the mischievous and frisky pets, may be harboring a lot more human DNA than once thought, possibly tampering crime scenes, a new study says.

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

The post Cats May Be Tampering With Crime Scenes, Scientists Say appeared first on Futurism.

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Cats May Be Tampering With Crime Scenes, Scientists Say

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

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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

APAC will be the ‘epicentre’ of global AI development – report – IT Brief Australia

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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

Will AI Take Your Jobor Make It Better? – WIRED

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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

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

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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

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

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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.

Before you continue reading, how about a follow on LinkedIn?

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

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

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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

Scientists Found a Way to Control How High Mice Got on Cocaine

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A team of neuroscientists at the University of Wisconsin claim to have found a way to control how high mice can get on cocaine.

A team of neuroscientists at the University of Wisconsin claim to have found a way to control how high mice can get on a given amount of cocaine.

And don't worry — while that may sound like a particularly frivolous plot concocted by a team of evil scientists, the goal of the research is well-meaning.

The team, led by University of Wisconsin neuroscientist Santiago Cuesta, was investigating how the gut microbiome can influence how mice and humans react to ingesting the drug.

The research, detailed in a new paper published this week in the journal Cell Host & Microbe, sheds light on a vicious feedback loop that could explain cases of substance abuse disorders — and possibly lay the groundwork for future therapeutic treatments.

In a number of experiments on mice, the researchers found that cocaine was linked to the growth of common gut bacteria, which feed on glycine, a chemical that facilitates basic brain functions.

The lower the levels of glycine in the brain, the more the mice reacted to the cocaine, exhibiting abnormal behaviors.

To test the theory, the scientists injected the mice with a genetically modified amino acid which cannot break down glycine. As a result, the behavior of mice returned to normal levels.

In other words, the amino acid could curb cocaine addiction-like behaviors — at least in animal models.

"The gut bacteria are consuming all of the glycine and the levels are decreasing systemically and in the brain," said Vanessa Sperandio, senior author, and microbiologist from the University of Wisconsin, in a statement. "It seems changing glycine overall is impacting the glutamatergic synapses that make the animals more prone to develop addiction."

It's an unorthodox approach to treating addiction, but could be intriguing — if it works in people, that is.

"Usually, for neuroscience behaviors, people are not thinking about controlling the microbiota, and microbiota studies usually don't measure behaviors, but here we show they’re connected," Cuesta added. "Our microbiome can actually modulate psychiatric or brain-related behaviors."

In short, their research could lead to new ways of treating various psychiatric disorders such as substance use by adjusting the gut microbiome and not making changes to the brain chemistry.

"I think the bridging of these communities is what's going to move the field forward, advancing beyond correlations towards causations for the different types of psychiatric disorders," Sperandio argued.

READ MORE: How gut bacteria influence the effects of cocaine in mice [Cell Press]

More on addiction: Study: Magic Mushrooms Helped 83% of People Cut Excessive Drinking

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Scientists Found a Way to Control How High Mice Got on Cocaine

Scientists Spot "Stripped, Pulsating Core" of Star Caused By Horrific Accident

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In a

Core Dump

Scientists studying a group of stars made an astonishing but "serendipitous" discovery when they realized that Gamma Columbae, a fairly average celestial body, might actually be the "stripped pulsating core of a massive star," according to a study published this week in Nature Astronomy.

If true, that means Gamma Columbae is missing the envelope, or vast shroud of gas, that hides a star's nuclear fusion powered core.

What caused the stripping of this atmospheric envelope is not definitively known, but the scientists posit that Gamma Columbae running out of hydrogen could've caused its envelope to expand and swallow up a nearby star, likely its binary partner. But in the middle of that relatively common process, something appears to have horrifically gone wrong and ejected the envelope — and possibly even led to the two stars merging.

Naked Core

Before the disaster, the scientists believe Gamma Columbae could have been up to 12 times the mass of our Sun. Now, it's a comparatively meager 5 stellar masses.

Although a naked stellar core missing its envelope has been theorized to exist, it's never been observed in a star this size.

"Having a naked stellar core of such a mass is unique so far," said study co-author Norbert Pryzbilla, head of the Institute for Astro- and Particle Physics at the University of Innsbruck, in an interview with Vice.

Astronomers had an idea of what the cores of massive and low mass stars looked like, Pryzbilla continued, but there wasn't "much evidence" for cores of masses in between.

Star Power

It's an exceedingly rare find because the star is in a "a short-lived post-stripping structural re-adjustment phase" that will only last 10,000 years, according to the study.

That's "long for us humans but in astronomical timescales, very, very short," Przybilla told Vice. "It will always stay as a peculiar object."

The opportunity to study such a rarely exposed stellar core could provide scientists an invaluable look into the evolution of binary star systems. And whatever astronomers learn from the star, it's a fascinating glimpse at stellar destruction at a nearly incomprehensible scale.

More on stars: Black Hole Spotted Burping Up Material Years After Eating a Star

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Scientists Spot "Stripped, Pulsating Core" of Star Caused By Horrific Accident

Scientists Use Actual Lunar Soil Sample to Create Rocket Fuel

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A team of Chinese researchers claim to have turned lunar regolith samples brought back by the country's Chang'e 5 mission into a source of fuel.

Fill 'Er Up

A team of Chinese researchers say they managed to convert actual lunar regolith samples into a source of rocket fuel and oxygen — a potential gamechanger for future space explorers hoping to make use of in-situ resources to fuel up for their return journey.

The researchers found that the lunar soil samples can act as a catalyst to convert carbon dioxide and water from astronauts' bodies and environment into methane and oxygen, as detailed in a paper published in the National Science Review.

"In situ resource utilization of lunar soil to achieve extraterrestrial fuel and oxygen production is vital for the human to carry out Moon exploitation missions," lead author Yujie Xiong said in a new statement about the work. "Considering that there are limited human resources at extraterrestrial sites, we proposed to employ the robotic system to perform the whole electrocatalytic CO2 conversion system setup."

That means we could have a much better shot at carrying out longer duration explorations of the lunar surface in the near future.

Set It, Forget It

According to the paper, which builds on previous research suggesting lunar soil can generate oxygen and fuel, this process can be completed using uncrewed systems, even in the absence of astronauts.

In an experiment, the team used samples from China's Chang'e-5 mission, which landed in Inner Mongolia back in December 2020 — the first lunar soil returned to Earth since 1976.

The Moon soil effectively acted as a catalyst, enabling the electrocatalytic conversion of carbon dioxide into methane and oxygen.

"No significant difference can be observed between the manned and unmanned systems, which further suggests the high possibility of imitating our proposed system in extraterrestrial sites and proves the feasibility of further optimizing catalyst recipes on the Moon," the researchers conclude in their paper.

Liquified

But there's one big hurdle to still overcome: liquifying carbon dioxide is anything but easy given the Moon's frosty atmosphere, as condensing the gas requires a significant amount of heat, as New Scientist reported earlier this year.

Still, it's a tantalizing prospect: an autonomous machine chugging away, pumping out oxygen and fuel for future visitors. But for now, it's not much more than a proof of concept.

READ MORE: Scientists investigate using lunar soils to sustainably supply oxygen and fuels on the moon [Science China Press]

More on lunar soil: Bad News! The Plants Grown in Moon Soil Turned Out Wretched

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Scientists Use Actual Lunar Soil Sample to Create Rocket Fuel

NASA Sets Launch Date for Mission to $10 Quintillion Asteroid

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After disappointing setbacks and delays, NASA has finally got its mission to an invaluable asteroid made of precious metals back on track.

Rock of Riches

After disappointing setbacks and a delay over the summer, NASA says it's finally reviving its mission to explore a tantalizing and giant space rock lurking deep in the Asteroid Belt.

Known as 16 Psyche, the NASA-targeted asteroid comprises a full one percent of the mass of the Asteroid Bet, and is speculated to be the core of an ancient planet. But Psyche's size isn't what intrigues scientists so much as its metal-rich composition, believed to be harboring a wealth of iron, nickel, and gold worth an estimated $10 quintillion — easily exceeding the worth of the Earth's entire economy. Although, to be clear, they're not interested in the metals' monetary value but rather its possibly planetary origins.

Back On Track

Initially slated to launch in August 2022, NASA's aptly named Psyche spacecraft became plagued with a persistent flight software issue that led the space agency to miss its launch window that closed on October 11.

But after surviving an independent review determining whether the mission should be scrapped or not, NASA has formally announced that its spacecraft's journey to Psyche will be going ahead, planned to launch aboard a SpaceX Falcon Heavy rocket as early as October 10, 2023.

"I'm extremely proud of the Psyche team," said Laurie Leshin, director of NASA's Jet Propulsion Laboratory, in a statement. "During this review, they have demonstrated significant progress already made toward the future launch date. I am confident in the plan moving forward and excited by the unique and important science this mission will return."

Although the new launch date is only a little over a year late, the expected arrival at the asteroid Psyche is set back by over three years — 2029 instead of 2026 — due to having to wait for another opportunity to slingshot off of Mars' gravity.

Peering Into a Planet

Once it arrives, the NASA spacecraft will orbit around the asteroid and probe it with an array of instruments, including a multispectral imager, gamma ray and neutron spectrometers, and a magnetometer, according to the agency.

In doing so, scientists hope to determine if the asteroid is indeed the core of a nascent planet known as a planetesimal. If it is, it could prove to be an invaluable opportunity to understand the interior of terrestrial planets like our own.

More on NASA: NASA Announces Plan to Fix Moon Rocket, and Maybe Launch It Eventually

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NASA Sets Launch Date for Mission to $10 Quintillion Asteroid

Twitter Working on Plan to Charge Users to Watch Videos

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According to an internal email obtained by The Washington Post, Musk wants to have Twitter charge users to view videos posted by content creators.

Now that Tesla CEO Elon Musk has taken over Twitter, the billionaire has been frantically shuffling through ambitious plans to turn the ailing social media platform into a revenue-driving business.

Case in point, according to internal email obtained by The Washington Post, Musk is plotting for Twitter to charge users to view videos posted by content creators and take a cut of the proceeds — a highly controversial idea that's already been met with internal skepticism.

The team of Twitter engineers has "identified the risk as high" in the email, citing "risks related to copyrighted content, creator/user trust issues, and legal compliance."

In short, Musk is blazing ahead with his infamously ambitious timelines — a "move fast and break things" approach that could signify a tidal change for Twitter's historically sluggish approach to launching new features.

Musk has already made some big structural changes to Twitter, having fired high-up positions at the company and dissolved its board of directors.

The company will also likely be facing mass layoffs, according to The Washington Post.

The new feature detailed in the new email, which is being referred to as "Paywalled Video," allows creators to "enable the paywall once a video has been added to the tweet" and chose from a preset list of prices, ranging from $1 to $10.

"This will also give Twitter a revenue stream to reward content creators," Musk tweeted on Tuesday, adding that "creators need to make a living!"

But whether Twitter users will be willing to pay for stuff that was previously free remains anything but certain.

Musk has already announced that he is planning to charge $8 a month for Twitter users to stay verified, which has been met with derision.

The billionaire CEO is facing an uphill battle. Now that the company is private, he has to pay around $1 billion in annual interest payments, a result from his $44 buyout, according to the WaPo.

Compounding the trouble, Reuters reported last week that Twitter is bleeding some of its most active users.

Meanwhile, Musk's chaotic moves are likely to alienate advertisers, with the Interpublic Group, a massive inter-agency advertising group, recommending that its clients suspend all paid advertising for at least the week.

That doesn't bode well. It's not out of the question that a paywalled video feature may facilitate the monetization of pornographic content, which may end up scaring off advertisers even further — but Twitter's exact intentions for the feature are still unclear.

According to Reuters, around 13 percent of the site's content is currently marked not safe for work (NSFW).

It's part of Musk's attempt to shift revenue away from advertising on the platform. In a tweet last week, he promised advertisers that Twitter wouldn't become a "free-for-all hellscape."

But that hasn't stopped advertisers from already leaving in droves.

All in all, a paywalled video feature could mark a significant departure for Twitter, a platform still primarily known for short snippets of text.

For now, all we can do is watch.

READ MORE: Elon Musk’s Twitter is working on paid-video feature with ‘high’ risk [The Washington Post]

More on Twitter: Elon Musk Pleads With Stephen King to Pay for Blue Checkmark

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Twitter Working on Plan to Charge Users to Watch Videos

There’s Something Strange About How These Stars Are Moving, Scientists Say

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Astronomers are puzzled by the strange behavior of a crooked cluster of stars, which appears to be following an alternative theory of gravity.

Astronomers are puzzled by the strange behavior of certain crooked clusters of stars, which appear to be violating our conventional understanding of gravity.

Massive clusters of stars usually are bound together in spirals at the center of galaxies. Some of these clusters fall under a category astrophysicists call open star clusters, which are created in a relatively short period of time as they ignite in a huge cloud of gas.

During this process, loose stars accumulate in a pair of "tidal tails," one of which is being pulled behind, while the other moves ahead.

"According to Newton’s laws of gravity, it’s a matter of chance in which of the tails a lost star ends up," Jan Pflamm-Altenburg of the University of Bonn in Germany, co-author of a new paper published in the Monthly Notices of the Royal Astronomical Society, in a statement. "So both tails should contain about the same number of stars."

But some of their recent observations seemingly defy conventional physics.

"However, in our work we were able to prove for the first time that this is not true," Pflamm-Altenburg added. "In the clusters we studied, the front tail always contains significantly more stars nearby to the cluster than the rear tail."

In fact, their new findings are far more in line with a different theory called "Modified Newtonian Dynamics" (MOND).

"Put simply, according to MOND, stars can leave a cluster through two different doors," Pavel Kroupa, Pflamm-Altenburg's colleague at the University of Bonn and lead author, explained in the statement. "One leads to the rear tidal tail, the other to the front."

"However, the first is much narrower than the second — so it’s less likely that a star will leave the cluster through it," he added. "Newton’s theory of gravity, on the other hand, predicts that both doors should be the same width."

The researchers' simulations, taking MOND into consideration, could explain a lot. For one, they suggest that open star clusters survive a much shorter period of time than what is expected from Newton's laws of physics.

"This explains a mystery that has been known for a long time," Kroupa explained. "Namely, star clusters in nearby galaxies seem to be disappearing faster than they should."

But not everybody agrees that Newton's laws should be replaced with MOND, something that could shake the foundations of physics.

"It’s somewhat promising, but it does not provide completely definitive evidence for MOND," University of Saint Andrews research fellow Indranil Banik told New Scientist. "This asymmetry does make more sense in MOND, but in any individual cluster there could be other effects that are causing it — it’s a bit unlikely that would happen in all of them, though."

The researchers are now trying to hone in on an even more accurate picture by stepping up the accuracy of their simulations, which could either support their MOND theory — or conclude that Newton was, in fact, correct the first time around.

More on star clusters: Something Is Ripping Apart the Nearest Star Cluster to Earth

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There's Something Strange About How These Stars Are Moving, Scientists Say

This Deepfake AI Singing Dolly Parton’s "Jolene" Is Worryingly Good

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Holly Herndon uses her AI twin Holly+ to sing a cover of Dolly Parton's

AI-lands in the Stream

Sorry, but not even Dolly Parton is sacred amid the encroachment of AI into art.

Holly Herndon, an avant garde pop musician, has released a cover of Dolly Parton's beloved and frequently covered hit single, "Jolene." Except it's not really Herndon singing, but her digital deepfake twin known as Holly+.

The music video features a 3D avatar of Holly+ frolicking in what looks like a decaying digital world.

And honestly, it's not bad — dare we say, almost kind of good? Herndon's rendition croons with a big, round sound, soaked in reverb and backed by a bouncy, acoustic riff and a chorus of plaintive wailing. And she has a nice voice. Or, well, Holly+ does. Maybe predictably indie-folk, but it's certainly an effective demonstration of AI with a hint of creative flair, or at least effective curation.

Checking the Boxes

But the performance is also a little unsettling. For one, the giant inhales between verses are too long to be real and are almost cajolingly dramatic. The vocals themselves are strangely even and, despite the somber tone affected by the AI, lack Parton's iconic vulnerability.

Overall, it feels like the AI is simply checking the boxes of what makes a good, swooning cover after listening to Jeff Buckley's "Hallelujah" a million times — which, to be fair, is a pretty good starting point.

Still, it'd be remiss to downplay what Herndon has managed to pull off here, and the criticisms mostly reflect the AI's limited capabilities more than her chops as a musician. The AI's seams are likely intentional, if her previous work is anything to go off of.

Either way, if you didn't know you were listening to an AI from the get-go, you'd probably be fooled. And that alone is striking.

The Digital Self

Despite AI's usually ominous implications for art, Herndon views her experiment as a "way for artists to take control of their digital selves," according to a statement on her website.

"Vocal deepfakes are here to stay," Herndon was quoted saying. "A balance needs to be found between protecting artists, and encouraging people to experiment with a new and exciting technology."

Whether Herndon's views are fatalistic or prudently pragmatic remains to be seen. But even if her intentions are meant to be good for artists, it's still worrying that an AI could pull off such a convincing performance.

More on AI music: AI That Generates Music from Prompts Should Probably Scare Musicians

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This Deepfake AI Singing Dolly Parton's "Jolene" Is Worryingly Good

Greta Thunberg Says UN Climate Conference Is a Scam and She’s Not Attending

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The UN's upcoming COP27 climate conference in Egypt is basically a

COP Out

Ever since she lambasted world leaders at a UN conference in 2018 when she was only 15 years old, Swedish environmental activist Greta Thunberg has had the ear of the international community.

Now, Thunberg says she's skipping out on next week's COP27 UN climate summit in Egypt. Why? Because it's rife with "greenwashing."

"I'm not going to COP27 for many reasons, but the space for civil society this year is extremely limited," Thunberg said at a press event for her book, "The Climate Book," as quoted by The Guardian. "The COPs are mainly used as an opportunity for leaders and people in power to get attention, using many different kinds of greenwashing."

Ultimately, in Thunberg's view, the COP conferences "are not really meant to change the whole system" and instead only promote incremental change. Bluntly put, they're feel-good events that don't accomplish much, so she's bowing out.

Wasted Breath

It's not an unfair assessment. For all the pledges made to drastically cut back emissions and achieve net carbon zero by 2050, very few nations have followed through in the short term. And in Europe, the energy crisis in the wake of the war in Ukraine has further sidelined those climate commitments.

So we can't blame her for not going. But it's a bit disheartening that even a tenacious young spokesperson like Thunberg has given up on convincing world leaders at the biggest climate summit in the world.

Maybe it's indicative of the frustrations of her generation at large. When Thunberg was asked what she thought about the recent wave of Just Stop Oil protests that included activists throwing soup on a Van Gogh painting, she said that she viewed what many detractors perceived as a dumb stunt to be symptomatic of the world's failure to effect meaningful environmental change.

"People are trying to find new methods because we realize that what we have been doing up until now has not done the trick," she replied, as quoted by Reuters. "It's only reasonable to expect these kinds of different actions."

Maybe the real question is: if even a UN climate conference isn't the place to get the message out and change hearts, where's the right place, and what's the right way? If the headlines are any indication, zoomers are struggling to figure that out.

More on Greta Thunberg: Greta Thunberg Thinks Germany Shutting Down Its Nuclear Plants Is a Bad Idea

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Greta Thunberg Says UN Climate Conference Is a Scam and She's Not Attending

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

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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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AI can predict if you’ll die soon by examining your organs – Engadget

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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

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

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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...

Manslaughter Case Has a Strange Twist: Tesla That Killed Couple Was on Autopilot

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A court case is about to kick off in Los Angeles later this month, involving a fatal crash caused by a Tesla vehicle, which was on Autopilot.

A provocative manslaughter case is about to kick off in Los Angeles later this month, involving a fatal crash caused by a Tesla vehicle that had the company's controversial Autopilot feature turned on.

It's the first case of its kind, and one that could set a precedent for future crashes involving cars and driver-assistance software, Reuters reports.

We won't know the exact defense until the case gets under way, but the crux is that the man who was behind the wheel of the Tesla is facing manslaughter charges — but has pleaded not guilty, setting up potentially novel legal arguments about culpability in a deadly collision when, technically speaking, it wasn't a human driving the car.

"Who's at fault, man or machine?" asked Edward Walters, an adjunct professor at the Georgetown University, in an interview with Reuters. "The state will have a hard time proving the guilt of the human driver because some parts of the task are being handled by Tesla."

The upcoming trial is about a fatal collision that took place in 2019. The crash involved Kevin George Aziz Riad, who ran a red light in his Tesla Model S, and collided with a Honda Civic, killing a couple who were reportedly on their first date.

According to vehicle data, Riad did not apply the brakes but had a hand on the steering wheel. Perhaps most critically, though, the Tesla's Autopilot feature was turned on in the moments leading up to the crash.

Riad is facing manslaughter charges, with prosecutors arguing his actions were reckless.

Meanwhile, Riad's lawyers have argued that he shouldn't be charged with a crime, but have so far stopped short of publicly placing blame on Tesla's Autopilot software.

Tesla is not directly implicated in the upcoming trial and isn't facing charges in the case, according to Reuters.

A separate trial, however, involving the family of one of the deceased is already scheduled for next year — but this time, Tesla is the defendant.

"I can't say that the driver was not at fault, but the Tesla system, Autopilot, and Tesla spokespeople encourage drivers to be less attentive," the family's attorney Donald Slavik told Reuters.

"Tesla knows people are going to use Autopilot and use it in dangerous situations," he added.

Tesla is already under heavy scrutiny over its Autopilot and so-called Full Self-Driving software, despite conceding that the features "do not make the vehicle autonomous" and that drivers must remain attentive of the road at all times.

Critics argue that Tesla's marketing is misleading and that it's only leading to more accidents — not making the roads safer, as Tesla CEO Elon Musk has argued in the past.

In fact, a recent survey found that 42 percent of Tesla Autopilot said they feel "comfortable treating their vehicles as fully self-driving."

Regulators are certainly already paying attention. The news comes a week after Reuters revealed that the Department of Justice is investigating Tesla over Autopilot.

Last year, the National Highway Traffic Safety Administration (NHTSA) announced an investigation of accidents in which Teslas have smashed into emergency response vehicles that were pulled over with sirens or flares.

This month's trial certainly stands the chance of setting a precedent. Was Riad fully at fault or was Tesla's Autopilot at least partially to blame as well?

The answer now lies in the hands of a jury.

READ MORE: Tesla crash trial in California hinges on question of 'man vs machine' [Reuters]

More on Autopilot: Survey: 42% of Tesla Autopilot Drivers Think Their Cars Can Drive Themselves

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Manslaughter Case Has a Strange Twist: Tesla That Killed Couple Was on Autopilot

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

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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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