Then you have enterprises getting into this space, forming an industrial metaverse, which is a 3D digital copy of a real-world, physical place like a factory, city or supply chain that’s driven by real-time sensors and data. This allows businesses to trial and test scenarios and products before implementing them inside the physical world. We are at a really interesting place with these technologies: moving everyone in this direction will require us to increase our computing, processing and networking power, which also means we need to increase our energy because we are essentially moving from 2D to 3D. We are moving our data, too, and creating all that complex data creates a greater footprint. This year, I think we’re going to see a major breakthrough when it comes to populating the spatial internet. That’s going to come at the
convergence of generative AI. Today, we can input text and speech and images to get a 2D output. Very soon we’re going to be able to input text and speech and images to get a 3D output. We’re already seeing signs of this from gaming metaverses like Roblox. We know that Nvidia, the largest AI chip manufacturer, has teamed up with WPP, the world’s largest advertising agency, to come up with a 3D design ecosystem. We can expect this to be a really big breakthrough: it will mean that anybody has the ability to start populating the spatial internet without needing to know how to code. This is also going to be a very vulnerable year, because we have a gap in regulation and policy. It’s a year where 49% of the world’s population have the opportunity to vote across at least 64 countries. You take the fact that these technologies that disrupted previous election cycles have matured, people have gotten better at using them and the cost of content creation and distribution has gone down, while loneliness and isolation has gone up. You couple that with this gap in policy, and we’re looking at our most vulnerable election cycle yet. FEED: You specialise in identifying the opportunities and risks of AI and XR technologies. Could you share some of these with us? With the opportunities and risks of AI, we’ve heard a lot about efficiencies and productivity. To quantify that, MIT have recently done a study where they empowered customer-service workers with AI assistants, and they found that they became 14% more productive. It also meant that people who only had two months’ worth of experience became equal with those who had six. Looking at this kind of instant upskilling could redefine what entry-level positions look like. One of the trends we’re going to start to see this year is large language models embedded into our chatbots and smart home speakers, which will allow them to fulfil their original intention: to become a new sales and marketing channel. By the end of this year, I might be able to say to my smart home speaker: ‘I want to go on holiday. These are the four days I have; this is my budget. I want to get there by train and I want to go to the seaside. I want to go someplace where the weather’s nice and it must be dog friendly.’ Not only will the speaker be able to make recommendations based on my preferences, but I’ll also be able to say ‘I like the sound of that,’ and have it book everything for me. We will see the customer journey and experience accelerate and become more personalised. When it comes to things like supply chain, it’s fascinating: we can take AI we have already implemented, with computer vision and deep learning, and add large language models which can turn any physical environment into an employee. I could ask it for daily summaries or reports, or even make suggestions on how to improve efficiencies.
Our 2D internet is becoming more 3D, spatial, immersive and social
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