A staggering total of $329 billion is at risk globally because of poor cybersecurity applied to operational technology (OT) systems, which control facilities such as manufacturing and energy storage, according to cybersecurity company, Dragos. The days are long gone when OT systems from online hackers were protected by the airgap, effectively a digital moat where all data was transferred manually. Today OT systems are linked to online IT systems to facilitate communication and increase efficiency. But organisations relying on OT systems are now finding that they must now pay too high a price for these gains.
Companies are already becoming disenchanted with the initial rollout of Big Tech’s new artificial intelligence (AI) technology. Rapidly diminishing return on investment (ROI) and poor initial outcomes are forcing companies to rethink their earlier strategies, according to a new report from AI data services company, Appen. “As enterprises gain more AI experience, they are becoming more selective about which projects to pursue, and fewer initiatives are reaching deployment. Appen believes this trend is likely driven by diminishing ROI or the lack of significant outcomes,” says Appen. Gartner also recently issued a stern warning to organizations across all sectors that the cost of introducing artificial intelligence (AI) to the workplace could easily balloon by a staggering 500 -1,000 percent.
America’s leading technology companies are now engaged in their own nuclear power race. Advertising and search giant Google has announced that it has signed the world’s first corporate agreement to purchase nuclear energy from multiple small modular reactors (SMR), to be developed by Kairos Power. By investing in its own nuclear energy facilities, Google has now joined the ranks of Amazon, Microsoft, and Oracle in investing heavily in nuclear facilities to power the rollout of new services based around their prematurely launched artificial intelligence (AI) services. According to a recent report from US Madison Avenue investment bankers, Jeffries: “If it feels like Graphics Processing Units (GPUs) are suddenly everywhere, it’s because they are. GPUs drive computation across a wide range of industries and applications, from big data analytics to machine learning [AI].”
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