A year and a half into the AI boom, there's growing evidence that the hype machine is slowing down. Drastic warnings about AI posing an existential threat to humanity or taking everyone's jobs have mostly disappeared, replaced by technical conversations about how to cajole chatbots into helping summarize insurance policies or handle customer service calls. Some once-promising start-ups have already cratered and the suite of flashy products launched by the biggest players in the AI race -- OpenAI, Microsoft and Google -- have yet to upend the way people work and communicate with each other. While money keeps pouring into AI, very few companies are turning a profit on the tech, which remains hugely expensive to build and run.

The hype around artificial intelligence has been building for years, and you could say it reached a crescendo with OpenAI's recent release of ChatGPT (and now GPT-4). It only took two months for ChatGPT to reach 100 million users, making it the fastest-growing consumer application in history (it took Instagram two and a half years to gain the same user base, and TikTok nine months). In Ian Beacraft's opinion, we're in an AI hype bubble, way above the top of the peak of inflated expectations on the Gartner Hype Cycle. But it may be justified, because the AI tools we're seeing really do have the power to overhaul the way we work, learn, and create value. Beacraft is the founder of the strategic foresight agency Signal & Cipher and co-owner of a production studio that designs virtual worlds. In a talk at South by Southwest last week, he shared his predictions of how AI will shape society in the years and decades to come.

Artificial intelligence has been touted as the "next big thing in cyber" for some time, even though the concept is as old as the first email viruses. The clamour around the technology, which started in late 2015 / early 2016, was quickly amplified as it became a tool in heavy use with analysts, sales teams and marketers. AI adoption continues to accelerate, and according to Capgemini's Reinventing Cybersecurity with Artificial Intelligence report, 48 per cent of respondents said budgets for AI in cybersecurity will increase by an average of 29 per cent in 2020. However, it's important to note that potentially only a few vendors exist with the R&D budget to pour tens or hundreds of billions of dollars required into building pure AI for cybersecurity. Typically, instead of AI, what people are usually talking about when it comes to uses in cybersecurity is machine learning and its associated subfields: Supervised, Unsupervised, Reinforcement and Deep Learning.