By the year 2021, cybercrime losses will cost upwards of $6 trillion annually. It's no surprise, then, that the cybersecurity industry is exploding as it grows to protect the networks and systems on which companies and organizations operate and store data. Because effective information security requires smarter detection, many cybersecurity companies are upping their game by using artificial intelligence to achieve that goal. A new wave of AI-powered solutions and products keep bad actors on their toes while giving IT teams much needed relief. Here are 30 companies merging artificial intelligence and cybersecurity to make the virtual world safer.

Email Protection: Uses artificial intelligence (AI) and machine learning to block spam and phishing attacks.

It's watching what the person is doing, what they look like when they're talking,

New York (CNN Business)Robots are getting better at doing human jobs. That's probably good for the economy -- but there are some serious downsides, too. Machines are expected to displace about 20 million manufacturing jobs across the world over the next decade, according to a report released Wednesday by Oxford Economics, a global forecasting and quantitative analysis firm. That means about 8.5% of the global manufacturing workforce could be displaced by robots. The report also notes that the move to robots tends to generate new jobs as fast as it automates them, however it could contribute to income inequality.

As artificial intelligence becomes a standard laboratory tool, scientists are quickly discovering both the promise and perils of algorithmically driven research. Artificial intelligence (AI) is cropping up everywhere these days, according to major news sources that are themselves increasingly driven by computer algorithms. Marketers use AI to target advertisements, engineers use it to anticipate device failures, and AI-driven social media platforms wield outsize influence on everything from fashion to politics. While all types of AI--also called machine learning--entail programming a computer to learn from examples and make inferences, practitioners distinguish different forms of it. Within the broader field of AI, a subset of strategies employ artificial neural networks. These mimic biological brains, with elements of a program connecting to each other like neurons.

In Asia, no economic or business sector is as vibrant or commands more attention of policymakers as the digital sphere. This trend is well documented in a landmark study by United Nations Conference on Trade and Development (UNCTAD)'s first annual Digital Economy Report. The timely study was released earlier this month as countries across Asia grapple with a complex digital future. Digital technologies help cut costs, enable delivery of services without leakages, reduce opportunities for graft, promote ease of doing business, leverage an increasingly non-tactile world, grow economies, have the potential to create millions of new jobs and, it appears, even help fight fake news. On the flip side, there are concerns of the cost of the emerging digital economy in terms of loss of traditional employment sectors, eroding the right to privacy, abetting authoritarian statecontrol of citizens' lives, causing a spike in cybercrimes and, according to some, promoting a deracinated, atomised existence for human beings.

Western democracies are confronted with collapsing trust in their governments and surging nationalist movements. These phenomena have a particularly cruel timing, occurring contemporaneously with the rise of complex, global problems that urgently require coordinated, collective action. As the world becomes increasingly complicated and interconnected, the decisions of governments, corporations, and large institutions have become less accessible to the average citizen. Whether in relation to data privacy, climate change, or automation and the Fourth Industrial Revolution, citizens are being asked to accept decisions made by experts whose knowledge they can't match or evaluate. The average citizen, whose voice and consent was once proclaimed as essential to the functioning of democracy and legitimized political power, is now being asked to yield more authority to experts.

Doing business in Sudan isn't easy, but back in 2011, it should have been possible. "We were working with major telecoms company Zain based out of southern Sudan at the time – before the country split in two," explains Charlie Tryon, chief executive of Maris, an investment holding company that operates across east and southern Africa. "Sudan was on the US's Office of Foreign Assets Control (OFAC) sanctions list, but the south was exempt, so it should have been OK for us to work here. We took out all the precautions we needed – did all the necessary paperwork, spoke to all the right people, told the banks, made sure we had permission from OFAC and notified all other regulatory bodies about our cross-border transaction – everything. "But the money we transferred from our business bank account to Zain was still stopped," he says. Tryon's transaction failed to pass compliance tests. In a bind, he was forced to physically move thousands of dollars from a bank account in Uganda to Sudan to pay his suppliers – at great personal risk. "We had suitcases full of cash that we took via plane and car into Sudan," says Tryon. "This isn't the ideal way to run a business, but at the time we had very little choice." A lot has changed since 2011. Know-your-customer and anti-money laundering (AML) screening is increasingly automated, helping to remove some of the delays caused by strict compliance measures. On top of this, banks, retailers, payment service providers (PSPs) and other businesses involved in the money transfer process are using artificial intelligence (AI) to make much more accurate decisions about payments. "At the time, we spent a huge amount of money and time trying to set this right," says Tryon. "It included international travel, lobbying, meetings with banks and regulators.

The term Artificial Intelligence was coined in 1956, but AI has become more popular today thanks to increased data volumes, advanced algorithms, and improvements in computing power and storage. In the 1960s, the US Department of Defense took interest in this type of work and began training computers to mimic basic human reasoning. For example, the Defense Advanced Research Projects Agency (DARPA) completed street mapping projects in the 1970s. And DARPA produced intelligent personal assistants in 2003, long before Siri, Alexa or Cortana were household names. This early work paved the way for the automation and formal reasoning that we see in computers today, including decision support systems and smart search systems that can be designed to complement and augment human abilities.

Imagine a world where killer robots, powered by artificial intelligence (AI), have the ability to decide who lives and who dies on the basis of deep learning and algorithms, without any human intervention. This scenario has been criticised by naysayers as alarmist. But experts, including United Nations Secretary-General Antonio Guterres and Tesla co-founder Elon Musk, have warned of the risk that AI can be put to nefarious use in the wrong hands. Please subscribe or log in to continue reading the full article.