Metaverse

Here’s how the metaverse will evolve

The metaverse will transform how people interact with the world across three overlapping phases, each with its own distinctive influences across technology, market and product characteristics.

Right now, the metaverse seems to be both everywhere and nowhere, simultaneously touted as the next great innovation and criticized as over-hyped and over-promised. But what exactly is the metaverse, and which end of the spectrum is closer to reality?

There are many differing definitions of the metaverse, but Gartner defines it as “A collective virtual shared space, created by the convergence of virtually enhanced physical and digital reality.” In this view, the metaverse is persistent, providing enhanced immersive experiences, and once matured it will serve as a device-independent ecosystem for further innovation.

The transition to the mature metaverse will be similar to previous technology shifts, such as the Industrial Revolution or the mobile era, in that its evolution will introduce a new set of technology leaders while potentially displacing some from the previous era. The metaverse will be an evolutionary step in the development of the internet, acting as a collective, shared space born from the convergence of physical and persistent digital content and experiences.

Therefore, there will be only one metaverse in the same sense that there’s only one internet; just as no single entity or organization owns or controls the internet, the same will apply to the metaverse.

The metaverse will evolve across three overlapping phases: emerging, advanced and mature. Here is what technology leaders need to know about each of these phases and the distinctive technology, market and product/service influences that will define them.

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Mots-clés : cybersécurité, sécurité informatique, protection des données, menaces cybernétiques, veille cyber, analyse de vulnérabilités, sécurité des réseaux, cyberattaques, conformité RGPD, NIS2, DORA, PCIDSS, DEVSECOPS, eSANTE, intelligence artificielle, IA en cybersécurité, apprentissage automatique, deep learning, algorithmes de sécurité, détection des anomalies, systèmes intelligents, automatisation de la sécurité, IA pour la prévention des cyberattaques.

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