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【For Hong Kong Investors Only】Since late last year, OpenAI’s conversational AI product ChatGPT started to gain exponential popularity. It is estimated to have reached 100 million monthly active users in January, just two months after launch, making it one of the fastest-growing consumer applications in history. ChatGPT stems from OpenAI’s multimodal LLM (large language model) GPT. The increasing polarity of ChatGPT has proved that ongoing innovations in generative AI are materializing at a faster-than-expected pace.

A significant breakthrough in Generative AI to empower the overall content industry

Following OpenAI’s release of ChatGPT and several iterations of its GPT model upgrades, we’ve also seen numerous companies announced to develop their LLMs. The rapid proliferation of AI led to substantial demands for computing power resources, especially graphics processing units (GPUs). Meanwhile, AI also brings new functions to software, enhancing human-machine interaction, which could expand the potential user base. For the online game industry, AI can be used for image enhancement, automated level generation, balancing in-game complexity, adding intelligence to non-playing characters (NPCs), etc. Adoption of AI throughout new game development can help reduce developers’ workload, accelerate the content development cycle, as a result, enhance game studios’ operation efficiency and improve profitability. AI pattern recognition also creates the opportunity for targeted ad and product placement within gameplay. Publishers stand to benefit from an increased mix of ad revenue, which would also result in improved margin profiles.

Leading game engine Unity revealed two new AI-based products Sentis and Muse for creators to enhance their real-time 3D (RT3D) content. These two products are currently available in closed beta, with plans to launch them globally later this year. In addition, Unity also announced it’s launching a dedicated AI marketplace in the Asset Store that offers several other tools for creators.

In March 2023, Roblox rolled out generative AI coding tools for its game creators, including a material generator that simulates lighting and AI code, assist that helps developers code faster using natural language. The incorporation of AI tools for game development community means a much lower entry barrier for game-related content creation. Roblox’s ecosystem of millions of developers is expected to grow at an unprecedented speed.

Into the second half of 2023, we’re excited to see more advancements in generative AI. With the continuous upgrade of hardware, the incremental time required for a full iteration of model training should continue to reduce.  As generative AI technology continues to develop, it is likely to have an even greater impact on the gaming industry in the years to come. Going forward, AI will accelerate its adoption by the online gaming industry, as it makes games more realistic, more immersive, and opens up new possibilities for game development.

Nvidia announced a new computing system to power industrial Metaverse Applications

The metaverse, a virtual world where people can interact with digital environments and each other in real-time, is becoming a reality with the help of advanced technologies such as artificial intelligence (AI) and simulation. NVIDIA, a leading provider of GPUs, has recently announced the launch of the third generation of its NVIDIA OVX computing system, designed to power large-scale digital twins built on NVIDIA Omniverse Enterprise.

The OVX system is set to revolutionize how industrial products are created and how people interact with the digital world. It can help enterprises tackle complex new workloads, optimize simulations, and speed up workflows. The third-generation OVX system features a new architecture with a dual-CPU platform and four NVIDIA L40 GPUs, delivering revolutionary neural graphics, AI computing, and performance needed for the most demanding Omniverse workloads.

The BlueField-3 data processing unit offloads accelerates, and isolates CPU-intensive infrastructure tasks. This is particularly useful for deploying Omniverse at the data center scale, providing a secure foundation for running the data center control plane, enabling higher performance, limitless scaling, zero-trust security, and better economics. The accelerated NVIDIA Spectrum Ethernet platform provides high bandwidth and network synchronization to enhance real-time simulation capabilities, helping users keep up with networking performance.

The latest OVX systems will be available to customers worldwide later this year, providing enterprises with the technology to handle complex manufacturing, design, and Omniverse-based workloads. Businesses can take advantage of the real-time, true-to-reality capabilities of OVX to collaborate on the most challenging visualization, virtual workstation, and data center processing workflows.

The third-generation OVX system has many potential applications, including modeling factories, cities, and autonomous vehicles in immersive digital twins before deployment in the real world. This will help maximize operational efficiency and predictive planning capabilities. For example, DB Netze’s Digitale Schiene Deutschland is leveraging the capabilities of OVX to power large-scale digital twins of dynamic physical systems, including rail networks. Jaguar Land Rover is also leveraging the graphics and simulation capabilities of OVX systems in conjunction with the NVIDIA DRIVE Sim platform to accelerate the testing and development of next-generation autonomous vehicles.

As the metaverse continues to evolve, OVX is set to play a key role in transforming how we interact with the digital world. By combining AI and simulation, digitalization is redefining how industrial products are created and transforming how people interact with the digital world. OVX is a breakthrough technology that provides the graphics and AI needed to accelerate massive digital twin simulations and other demanding applications, enabling enterprises to handle complex manufacturing, design, and Omniverse-based workloads.

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