Web3, or web 3.0, is generally recognised as the latest evolutionary step in the makeup and use of data found on the web. Difficult to boil down to a single feature, a number of new technologies have fundamentally changed our information and how we interact with it. Defining it requires pointing out the multi-leveled effect it is enacting.
At its core, we’ve moved data storage to the blockchain model and we are increasingly using AI to automate how we access and analyse this data. The significance of automation available with AI and ML has risen as we continue to create data at an astonishing rate. IoT devices, for example, are allowing us to see the greater picture by providing the mountain of information needed to simulate massive systems. Moving up, the computation itself is moving from simply cloud to distributed cloud. Modern platforms benefit from being able to deploy on to any environment whether it be cloud, hybrid, on prem or the edge. We’re moving the cloud to a serverless, decentralised form of computation. Then, regarding how we access and observe this information, technologies like AR and VR are merging the physical and digital spaces together, moving our focus from screens into a more cohesive connection to the real world.
Web3 is often also referred to as the spatial web, where advanced spatial computing is driving changes in simulation technology. Representing and analysing physical entities has long been an area of IT, with Computer Aided Design programmes being a key early example. Increasing computational power allowed these simulations to mature and grow in complexity, but ultimately the underlying framework remained the same. Web3 marks a distinct change in this framework due to the availability of new platforms and tools that compliment each other.
Consider how designing and monitoring machines in factories has changed with the advent of IoT devices. By providing a way to measure and collect huge amounts of real time data, our simulations can become living, breathing replicas. They can be stress tested and optimised to improve efficiency, with IoT devices providing insight that was previously unavailable. Similarly, we can view these simulations through completely fresh perspectives. Building Information Modelling, for example, has been a staple of architecture and urban planning for a number of years. Now VR is allowing us to literally walk around them before they’ve even been built. Or you can use AR to project features onto already existing structures. These changes are not minor improvements or cases of streamlining – they are representative of an entirely new approach.
But these new technologies come with a price, as well as further challenges. For one, they simply demand constant access to high compute power. Secondly, they demand the correct kind of computation. Time sensitive properties on something like a digital twin are often better processed at the edge to remove the problems of latency, therefore a compute platform has to be able to enable this. IoT and AI/ML use copious amounts of data, meaning applications need to be able to scale effectively in order to meet the demand.
For a number of years, processing data on the web occurred in on-premise systems. The cloud introduced a greater flexibility and efficiency to IT, but even this is beginning to become decentralised. Distributed cloud gives an organisation the option to enable any public or private cloud, hybrid, on-prem or edge environment for its IT functions. Each part of your infrastructure can be mapped to the one it suits best, rather than having to choose a lowest common denominator.
So what exactly does the endgame of web3 look like? Not unlike the web itself it is a vast network of pieces coming together, so it’s fair to say the future won’t arrive overnight. However we can certainly point out the few key pillars such as distributed cloud, blockchain and AI/ML that will define it. To best prepare, we ultimately need our underlying infrastructure ready to deal with what web3 offers us. We need secure, scalable computation that can take advantage of an exciting future.
Web3, or web 3.0, is generally recognised as the latest evolutionary step in the makeup and use of data found on the web. Difficult to boil down to a single feature, a number of new technologies have fundamentally changed our information and how we interact with it. Defining it requires pointing out the multi-leveled effect it is enacting.
At its core, we’ve moved data storage to the blockchain model and we are increasingly using AI to automate how we access and analyse this data. The significance of automation available with AI and ML has risen as we continue to create data at an astonishing rate. IoT devices, for example, are allowing us to see the greater picture by providing the mountain of information needed to simulate massive systems. Moving up, the computation itself is moving from simply cloud to distributed cloud. Modern platforms benefit from being able to deploy on to any environment whether it be cloud, hybrid, on prem or the edge. We’re moving the cloud to a serverless, decentralised form of computation. Then, regarding how we access and observe this information, technologies like AR and VR are merging the physical and digital spaces together, moving our focus from screens into a more cohesive connection to the real world.
Web3 is often also referred to as the spatial web, where advanced spatial computing is driving changes in simulation technology. Representing and analysing physical entities has long been an area of IT, with Computer Aided Design programmes being a key early example. Increasing computational power allowed these simulations to mature and grow in complexity, but ultimately the underlying framework remained the same. Web3 marks a distinct change in this framework due to the availability of new platforms and tools that compliment each other.
Consider how designing and monitoring machines in factories has changed with the advent of IoT devices. By providing a way to measure and collect huge amounts of real time data, our simulations can become living, breathing replicas. They can be stress tested and optimised to improve efficiency, with IoT devices providing insight that was previously unavailable. Similarly, we can view these simulations through completely fresh perspectives. Building Information Modelling, for example, has been a staple of architecture and urban planning for a number of years. Now VR is allowing us to literally walk around them before they’ve even been built. Or you can use AR to project features onto already existing structures. These changes are not minor improvements or cases of streamlining – they are representative of an entirely new approach.
But these new technologies come with a price, as well as further challenges. For one, they simply demand constant access to high compute power. Secondly, they demand the correct kind of computation. Time sensitive properties on something like a digital twin are often better processed at the edge to remove the problems of latency, therefore a compute platform has to be able to enable this. IoT and AI/ML use copious amounts of data, meaning applications need to be able to scale effectively in order to meet the demand.
For a number of years, processing data on the web occurred in on-premise systems. The cloud introduced a greater flexibility and efficiency to IT, but even this is beginning to become decentralised. Distributed cloud gives an organisation the option to enable any public or private cloud, hybrid, on-prem or edge environment for its IT functions. Each part of your infrastructure can be mapped to the one it suits best, rather than having to choose a lowest common denominator.
So what exactly does the endgame of web3 look like? Not unlike the web itself it is a vast network of pieces coming together, so it’s fair to say the future won’t arrive overnight. However we can certainly point out the few key pillars such as distributed cloud, blockchain and AI/ML that will define it. To best prepare, we ultimately need our underlying infrastructure ready to deal with what web3 offers us. We need secure, scalable computation that can take advantage of an exciting future.