It’s Gartner Hype Cycle Day! This is roughly analogous to the Oscars for emerging technologies, in which the Gartner Group looks through their telescopes to see what could end up being the next big thing over the course of the next decade. The idea behind the hype cycle is an intriguing concept – emerging technologies seem to come out of nowhere, explode into prominence while the technology is still less than fully mature, then seemingly disappear for a while as the promise of the hype gives way to the reality of implementation and real-world problems. Once these are worked out, the technology in question gets adopted into the mainstream.
The hype cycle is frequently the source of investor bingo, where young startups pick a term that most closely reflects their business model, then pitch it to angel investors to provide supporting evidence that their product is worth investing in. It also gets picked up by the marketing departments of existing companies that are working at marketing their newest offerings to customers, For this reason, the Gartner Hype Cycle (GHC) should always be taken as a speculative guide, not a guarantee.
Nonetheless, from the standpoint of data science, this year’s graph is quite intriguing. The GHC looks at emerging technologies, which in general can be translated to mean that even the most immediate items on the curve are at least two years out, with the rest either between five and ten years out or beyond. In the immediate term, what emerges is that distributed identity, of individuals, organizations (LEIs), or things (NFTs) will become a critical part of any future technologies. This makes sense – these effectively provide the hooks that connect the physical world and its virtual counterpart, and as such become essential in the production of digital twins, one of the foundations of the metaverse. Similarly, generative AI, which takes data input and uses that to create relevant new content, has obvious implications for virtual reality (which is increasingly coming under the heading of Multiexperience).
A second trend that can be discerned is the shift away from application development as a predominantly human activity to become instead something that is constructed by a subject matter expert, data analyst, or decision-maker. This is the natural extension of the DevOps movement, which took many of the principles of Agile and concentrated primarily on automating that which could be automated. This can also be seen in the…
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