Content delivery platform provider Akamai announced Wednesday platform security enhancements intended to increase cybersecurity protections for web applications, APIs and user accounts. Akamai said its machine learning algorithms leverage insights from a dataset of over 1.3 billion daily client interactions to automate threat detections, time-consuming tasks and security logic to help cybersecurity analysts make better decisions faster. The company said it is taking these steps to keep up with attackers who are using AI, machine learning and automation to increase the frequency and sophistication of their attacks. "At Akamai, our latest platform release is intended to help resolve the tension between security and ease of use, with key capabilities around automation and machine learning specifically designed to intelligently augment human decision-making," said Aparna Rayasam, Akamai's senior vice president and general manager for Application Security, in a press release. "Smart automation adds immediate value and empowers users with the right tools to generate insight and context to make faster and more trustworthy decisions ... while anticipating what attackers might do next."

The arms race between cybercriminals and cybersecurity professionals continues to escalate. And anyone watching the trajectory of this perpetual game of one-upmanship can see that this is a race towards implementing AI in the service of each side's goals. For instance, a report by Nokia revealed that AI-powered botnets look for vulnerabilities in Android devices, then load data-stealing malware that is only detected after the damage has been done. Networks now incorporate multi-cloud environments that are dynamic and often temporary, SD-WAN connections to branch offices to support critical business applications, and an increasingly mobile workforce. At the same time, devices are proliferating inside networks at an unprecedented pace, from a multitude of different end-user devices to IoT technology.

Artificial intelligence (AI), robots, automation and machine learning are concepts that are appearing more frequently in mainstream media as the technology behind them is constantly improved. But do people in the UK see these making a real difference to how they live their lives? According to a survey this week by Lightspeed, 83% of UK adults believe that AI will one day be smart enough to take over from humans in many types of job, with 27% of respondents claiming this day will come'in my lifetime.' Will machines take over from real people in manufacturing and industry? With Brexit (and a drop in the cost of robots), it's hardly surprising that so many people see this scenario on the horizon.

For cybersecurity pros who fight unseen cloud adversaries every day, the rise of faceless security automation might feel uncomfortably familiar. But is automation yet another shapeless enemy, this time intent on slashing cybersecurity jobs? Or is it something else? Fortunately, the demand for cloud security experts far outstrips the supply. The smart players don't fear automation, they embrace it as a better way to catch the bad guys.

Threat actors are increasingly adopting security automation and machine learning – security teams will have to follow suit, or risk falling behind. Many organizations still conduct incident response based on manual processes. Many playbooks that we have seen in our customer base, for example, hand off to other stakeholders within the organization to wait for additional forensic data, and to execute remediation and containment actions. While this may seem like good practice to avoid inadvertent negative consequences such as accidentally shutting down critical systems or locking out innocent users, it also means that many attacks are not contained in a sufficiently short time to avoid the worst of their consequences. Reports are mounting about threat actors and hackers leveraging security automation and machine learning to increase the scale and volume, as well as the velocity of attacks.

Today's workforce and automation of key functions is moving us toward an unprecedented level of innovation. One recent study from KPMG found that about three out of every four U.S. tech industry CEOs believe automation and machine learning are likely to replace at least 5 percent of their manufacturing, technology, sales, and marketing workforce by 2019. Yet the same study found that over half of the executives expect their organization's headcount to grow by at least 6 percent. While some big businesses might assume A.I. is their ticket to paying less in labor costs, if we go this route we're selling our workforces short. The human brain possesses something computers still don't: mindfulness.

In the move toward automation, machine-learning and predictive analytics, many are seeing dark times ahead for the human component of the IT workforce. Others, however, are seeing it as a time for the IT workers to become more powerful than ever before. At the HPE Discover EU event in London, Dana Gardner, president and principal analyst at Interarbor Solutions LLC, and Paul Teich, principal analyst at TIRIAS Research, sat down with Dave Vellante (@dvellante) and Paul Gillin (@pgillin), co-hosts of theCUBE*, from the SiliconANGLE Media team, to talk about the changing state of tech in a variety of areas. In the initial consideration, Teich felt that HPE had been doing "a credible job at trying to simplify their message" and "creating a set of overarching themes for … a bag of parts. They're a huge company; they have a very extensive portfolio. What we haven't seen in previous years is what ties that all together. Trying to be everything to everyone has its limits," he noted.

Asia-based senior executives at global companies believe that the impact of artificial intelligence (AI) and robotics on their business performance in Asia will be profound and positive--and will be felt sooner than we may think. Outside of global robotics industry leaders Korea and Japan, most of Asia currently lacks the depth of technical skills and R&D facilities needed to keep pace with AI development. However, China, India, and other large Asian economies generate a copious amount of data, a tremendous "natural resource" that is critical to pushing AI's capabilities forward. Ironically, given the commonly held view that AI will be responsible for disintermediation of jobs at all levels, it is Asia's massive human capital dividend--the billions of constantly Internet-connected workers and consumers--that will propel AI development in the region farther and faster. MIT Technology Review's International Markets division surveyed more than 60 Asia-based senior executives to gather perspective on the impact of AI and robotics on Asia's business landscape.

Apple has reportedly purchased artificial intelligence and machine learning startup Turi over the weekend, another signal that the world's biggest tech firms see a bright future in AI applications. The acquisition was first reported by the tech blog GeekWire. Turi, a Seattle-based company, offers a selection of tools aimed at helping developers easily scale machine learning applications, including Predictive Services, a server product for hosting and managing machine learning models, and GraphLab Create, an extensible machine learning framework that enables developers and data scientists to build and deploy intelligent applications and services. Apple responded to the publication with its standard comment explaining that the company buys smaller technology companies from time to time, and does not generally discuss the purpose or plans behind the deal. In October 2015, Apple acquired Perceptio, which has developed deep learning and AI capabilities that could be added to Siri.

The firm queried 138 U.S. tech CEOs, and 95 percent expect to increase the size of their workforces over the next three years. Some 55 percent expect to grow at least 6 percent. This growth in tech jobs for humans might have been even larger, however, but some positions will be filled by automation and machine learning systems: about three quarters of the tech CEOs expect automation and machine learning tools to replace at least 5 percent of their sales, marketing, technology, and manufacturing workforces. "The majority of technology companies plan to increase their human workforce at least 6 percent over the next three years while adding cognitive systems to create a new class of digital labor that can enhance human skills and expertise." Does this mean tech companies are going to start issuing reports on their digital labor force?