Introduction and overview of the McKinsey report

The McKinsey Technology Trends Outlook 2024 sheds light on which technological developments are currently particularly significant and how they are influencing various industries. McKinsey produces this report annually to provide companies with an overview of the most important technology trends and their long-term impact. This year, the focus is on topics that are fundamentally changing our daily lives and work, such as:

• Artificial intelligence (especially generative AI)
• Electrification and
• Renewable energies

For us as a provider of storage and server solutions, the report provides valuable insights that help us to better understand future trends in the hardware market - especially in the area of storage and servers. Although we cannot make exact predictions about prices or availability, the report gives us a good big picture from which we can deduce where the market is heading.

In this article, we summarize the most important findings of the McKinsey report in a compact and practical way. If you would like to read the full report, you will find the link below**.

Research methodology - How McKinsey gains its insights

McKinsey analyzes patents, research, search queries, news, and investments. In addition, executives around the world are surveyed to understand the extent to which these technologies are already in use. This creates a comprehensive picture of the most important technology trends.

**Link to the McKinsey Technology Trends Outlook 2024: https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-top-trends-in-tech

How advanced connectivity influences the IT infrastructure

More networking and new perspectives. Advanced connectivity describes the growing trend towards faster and more efficient network solutions. Technologies such as 5G, satellite connections and the future 6G could fundamentally change many industries. Particularly in areas such as edge computing and data centers, these advances offer new opportunities to process data in near real time while ensuring a secure and stable network connection.

What significance does Advanced Connectivity have for providers of server and storage solutions?

For us as a provider of server and storage solutions, these developments will be particularly important in the future when companies rely more heavily on local computing capacities and networked infrastructures. However, the actual use of these technologies, especially 6G, is still some way off and is not yet the focus of our business.

That is why our focus remains on edge and server solutions, which already offer the performance and flexibility required today. While advanced connectivity will gain in importance in the future, we are concentrating on optimally serving the current needs of our customers.

Cloud and Edge Computing

The trend and why it is important

More flexibility and efficiency. Cloud and edge computing demonstrate the transition from traditional IT systems to distributed infrastructures. Companies are using the public cloud to outsource workloads flexibly and scalably, which enables faster provisioning and cost benefits. At the same time, edge computing offers the possibility of processing data directly at the point of origin - this reduces latency times, lowers data transfer costs and improves data protection.

How AI is used in the context of cloud and edge computing

This trend is particularly evident in the area of AI applications. While the training of large AI models continues to take place in the cloud due to the enormous computing requirements, inference - the real-time processing of these models - is increasingly shifting to the edge of the networks. This shift enables faster and more efficient processing of data directly at the point of use.

What significance does this trend have for providers of server and storage solutions?

These developments are of great importance to us as a provider of server and storage solutions, as companies are increasingly relying on hybrid infrastructures that combine cloud and edge technologies. As this trend continues to grow, we are focusing on solutions that already offer our customers the flexibility and performance they need.

What does "shift to the edge" mean for AI applications?

Shifting to the edge means that certain AI applications that were previously executed in the cloud are increasingly being processed directly at the point of use.

• Training of AI models is still carried out in the cloud, as the necessary computing capacity is centrally available there.
• Inference - i.e. the use of trained models in real-time applications - is increasingly taking place locally at the edge, which significantly reduces latency times and enables faster data processing.

In industries such as factories, retail stores or hospitals, it is often beneficial to use AI models directly at the edge to respond faster, minimize data transmission costs and improve data protection.

To summarize: Cloud computing and edge computing complement each other. While the cloud continues to be used for training AI models, the edge is becoming increasingly important for the efficient use of these models in real time.

Adoption drivers and obstacles

• Companies are looking for better latency, cost reductions and more security, which is driving the shift of workloads to the edge.
• AI-supported use cases such as self-driving cars or virtual reality applications require fast processing of data on site (edge) to minimize delays.
• For small and medium-sized businesses, reducing the cost of edge connectivity could make it easier to move expensive cloud workloads to the edge.

Real application examples

• McDonald's is using cloud edge computing for its apps and self-service kiosks in a partnership with Google to improve device performance and simplify work processes for staff.
• An edge computing system is used on the International Space Station (ISS), which performs data processing tasks directly in space and reduces dependence on ground stations.

What implications this has for hardware requirements

Server

More performance in a smaller format. Based on current developments, it can be deduced that the demand for edge server solutions is likely to grow in the medium to long term. Companies are increasingly looking for on-premise solutions that can process data directly at the point of origin in order to reduce latency times and keep data on site - particularly relevant in industries such as manufacturing, retail and healthcare.

What requirements do the servers have to meet?
While the large cloud solutions for AI applications continue to play an important role, we see a clear trend in edge computing towards smaller, flexible server solutions that can be seamlessly integrated into existing infrastructures. These on-premise servers must be robust, energy-efficient and compact in order to function in demanding or remote environments.

What solutions does Supermicro offer for edge computing?
Supermicro has a broad portfolio of edge and embedded servers that meet these requirements. Solutions such as the SuperEdge series offer the flexibility and performance required for edge computing applications and are designed for use in a wide range of environments. These systems enable companies to carry out their data processing closer to the point of use and thus take full advantage of the benefits of edge computing.