Facebook, Microsoft: We’ll pay out $10m for tech to spot deepfake videos

If AI-generated ‘deepfake’ videos are going to spread like wildfire and cause social chaos in the future, it’s probably going to happen on Facebook… The aim is to create tech that everyone can use to detect when a video has been manipulated with AI.  However, to do that, it needs to have a larger dataset of deepfake content to work with, and so far the industry doesn’t have it or a benchmark for detecting deepfakes, according to Facebook.

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Scammers find powerful way to impersonate you and empty your bank accounts

Criminals are using AI-generated audio to impersonate a CEO’s voice and con subordinates into transferring funds to a scammer’s account.  … The Wall Street Journal reports that the CEO of an unnamed UK-based energy company thought he was talking on the phone with his boss, the CEO of the German parent company, who’d asked him to urgently transfer €220,000 ($243,000) to a Hungarian supplier. However, the UK CEO was in fact taking instructions from a scammer who’d used AI-powered voice technology to impersonate the German CEO.

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AI is changing the entire nature of compute

The world of computing, from chips to software to systems, is going to change dramatically in coming years as a result of the spread of machine learning. We may still refer to these computers as “Universal Turing Machines,” as we have for eighty years or more. But in practice they will be different from the way they have been built and used up to now. Such a change is of interest both to anyone who cares about what computers do, and to anyone who’s interested in machine learning in all its forms. … The rise of deep learning, starting in 2006, came about not only because of tons of data, and new techniques in machine learning, such as “dropout,” but also because of greater and greater compute power. … Machine learning is now poised to take over the majority of the world’s computing activity, …

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The Weaponization Of Artificial Intelligence

In the competition to lead the emerging technology race and the futuristic warfare battleground, artificial intelligence (AI) is rapidly becoming the center of the global power play.

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Startups are capitalizing on DeepFakes’ powerful AI

Deepfakes … made it possible for anyone to master complex machine learning; you just needed the time to collect enough photographs of a person to train the model. You dragged these images into a folder, and the tool handled the convincing forgery from there. The anonymous user had sparked “a war on what’s real,”

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4 Ways Every Business Needs To Use Artificial Intelligence

What makes artificial intelligence systems so powerful is that, unlike purely statistical approaches, they can learn. That allows them to adapt when market behavior changes as well as continually improve performance as more data comes in.

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The biggest tech trends of 2019, according to top experts

A new paradigm in personal computing is around the corner. That will be helped along by enabling technologies such as 5G networks, which will be stretching far and wide by the end of 2020. And, artificial intelligence will become infused in all kinds of products, allowing gadgets and services to subtly begin to anticipate our wants.

These tectonic shifts are already creating opportunity and chances for innovation.

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Five emerging cyber-threats to worry about in 2019

We’re going to see more mega-breaches and ransomware attacks in 2019. … But cyber-defenders should be paying attention to new threats, too.  Here are some that should be on watch lists:

Thanks to advances in artificial intelligence, it’s now possible to create fake video and audio messages that are incredibly difficult to distinguish from the real thing. These “deepfakes” could be a boon to hackers in a couple of ways. AI-generated “phishing” e-mails that aim to trick people into handing over passwords and other sensitive data have already been shown to be more effective than ones generated by humans. Now hackers will be able to throw highly realistic fake video and audio into the mix, either to reinforce instructions in a phishing e-mail or as a standalone tactic.

MITTechnologyReview.com click the link to read the rest of the story.

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2019 Cyber Security – What to expect next

During 2019 we expect to see an increase… If a sophisticated attack involves not one but five top-notch threats synergistically working together, the defense panorama could become very blurry. Security experts have a recipe for disaster. …

The purchase of cybersecurity has led to expanding attacks that will become more sophisticated in 2019 and beyond. We will continue to influence societal expectations on security, which will trickle down to companies through hundreds of thousands of vulnerable and easy targets for attackers to profit. Driven by many falling victim to feature misconceptions, more will become key targets. Cyber products that provide consolidated feature sets have a hard time understanding each customer’s specific pain points and the bad guys know this.

In 2019, even more high-profile breaches will push the security and privacy, finally. Security is argued about until we die. That’s a particularly terrifying threat.

Medium.com  click the link to read the rest of the story.

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How to tell if you’re talking to a bot

It’s important not to be swayed by fake accounts or waste your time arguing with them, and identifying bots in a Twitter thread has become a strange version of the Turing test. Accusing posters of being bots has even become an oddly satisfying way to insult their intelligence.

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This is how the robot uprising finally begins

Workplace robots equipped with AI will let automation creep into many more areas of work. They could replace people anywhere that products need to be sorted, unpacked, or packed.

TechnologyReview.com click the link to read the rest of the story.

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A Tour of The Top 10 Algorithms for Machine Learning Newbies

In machine learning, there’s something called the “No Free Lunch” theorem. In a nutshell, it states that no one algorithm works best for every problem, and it’s especially relevant for supervised learning (i.e. predictive modeling).

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Who Is Going To Make Money In AI?

As I started thinking about who was going to make money in AI I ended up with seven questions. Who will make money across the (1) chip makers, (2) platform and infrastructure providers, (3) enabling models and algorithm providers, (4) enterprise solution providers, (5) industry vertical solution providers, (6) corporate users of AI and (7) nations?

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