The Metaverse itself is a powerful concept. Imagine how impactful it can be when you add the problem-solving capability of AI into the equation.
Posted On: 31 March 2022 | (Source) | By : Vineet Kumar. Co-Founder and Chief Solutions Architect, Affine.
The Metaverse itself is a powerful concept. Imagine how impactful it can be when you add the problem-solving capability of AI into the equation. The Metaverse will bring forward an interactive environment that will enable enterprises to create a virtual reality environment with interactive life-like elements. As a technology, AI’s relevance to the growth and profitability of companies is evident. For example, a McKinsey survey estimates that at least 22% of companies conveyed a 5% increase of EBIT attributed to AI.
By combining the capabilities of AI and the Metaverse, we can think of numerous probabilities. For instance, many expensive real-world experiments can be carried out cost-effectively while adhering to strict timelines in the Metaverse to generate more data. This valuable data can be used to feed and train AI algorithms for accurate business decision-making. Similarly, any possible recommendations from AI solutions can be implemented with minimum risk in a Metaverse to understand the impact before implementing it in the real world. AI can also help with hyper-personalizing businesses in the Metaverse.
Let’s drill down a few potential use cases across industries and how they can transform the future landscape of day-to-day life:
In a Metaverse environment, there are interesting use cases. For example, simulations that are considered too hard to conduct in real factory settings can be executed seamlessly in a Digital Twin factory. Similarly, production line robots or warehouse robots can be trained and retrained in a Metaverse environment till they are perfect in handling a process such as a production schedule which is difficult to replicate in a physical factory.
Training the robots can happen within the Digital Twin, and the manufacturer can then import the trained models into the physical robots. A product manufacturer can also test the sensor machinery in a digital counterpart of the factory under extreme conditions such as very high RPM for long periods with intermittent breaks and observe the failing points of the equipment. The manufacturer can then use the observations from these test runs to fine-tune predictive maintenance models and reduce unscheduled downtime. These are just some of the possibilities that can be explored by combining AI and the Metaverse in the manufacturing space.
In a Metaverse retail environment, AI can determine which products to present (dynamic user-level personalization), how to present those products (dynamic store layout, planograms, number of product facings), and what prices or promotions to respective products (user-level price recommendation engine), to drive user experience and conversion. The insights gained from the Metaverse environment can be used to transfer the learning and customer insights back into real-world stores. At the same time, AI engines for physical stores can learn from augmented data derived from customer preferences displayed in metaverse stores. Metaverse environments can also be used to build a Digital Twin of a retail store. The Digital Twin can be used to not only check the response of customers towards the store layout but also to understand customer traffic movements to plan store associate placement and predict shelf stock-outs in real-time.
A Metaverse environment can be used to check the performance of a multi-specialty hospital when exposed to different parameters and conditions. From guiding the right doctor or caregiver to the right patient and allowing frontline workers to direct their energies efficiently, the combination of AI and Metaverse can do wonders.
Any new development in a proposed smart city can be simulated in the Digital Twin of the city to measure short-term and long-term impact on different ecosystems (utilities, traffic, waste management, etc.). The buildings or structures can be checked for structural integrity. Disasters can also be simulated without risk to evaluate their impact. These simulations can be used as data points to train AI algorithms that can be used to improve the city with respect to varying parameters.
One of the most common challenges for modern cities is running a highly efficient traffic system. Traffic conditions can be simulated in the Metaverse, and AI can optimize traffic techniques and gauge how best the traffic can be re-routed to minimize congestion.
Maturation of the Metaverse is imminent. By combining AI and the Metaverse, organizations can achieve transformational business impact from both the real world and the new virtual world. These are some of my thoughts on how AI and the Metaverse can help solve problems in real-world scenarios. The collective potential of AI and Metaverse in the Manufacturing sector, Retail, Healthcare, and Smart city is far-reaching.
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