Changing 2022 and the Future - Technology for Human-Machine Dialogue

With the rapid expansion of the data ecosystem in China, we are in an economic system that is not geographically restricted to do anything. It is estimated that 65% of global GDP this year will come from the digital economy. The influx of data not only presents opportunities but also many challenges. After all, the success of current and future digital development depends on the ability to protect and maintain increasingly complex IT systems. Here, I examine these near-term and long-term forecasts for the IT industry offering a variety of platforms and capabilities that will disrupt the work, home, and learning experience.

Outlook for 2022

Discussions on the margins focus on two areas: margin platforms where diverse margin ecosystems provide stable pools of secure capacity, and software-defined margin workloads/software stacks that extend applications and data systems to various real-world environments. It is critical at this margin to separate marginal platforms and marginal workloads, and if each marginal workload were to build its dedicated platform, we would face a proliferation of marginal infrastructure, a massive sprawl, and unmanageable infrastructure.

Imagine a marginal environment where you can deploy a marginal platform that provides compute, storage, I/O, and other basic IT functions in a stable, secure, and easy-to-use manner. When you extend various public and private cloud data and applications to the edge environment along with the on-premises IoT and data management edge, the system can be provisioned in a way like a software-defined suite using IT's common edge platform. This means that marginal workloads can evolve and change as quickly as software revisions because the underlying platform is composed of a stable pool of features.

We are now observing this shift. Dell Technologies now provides edge platforms for all major cloud stacks using common hardware and delivery mechanisms. As we move towards 2022, these platforms are expected to become more powerful and pervasive. We've seen most marginal workloads -- and even most public cloud marginal architectures -- move to containerized software-defined architectures, with dial tone for supposed standard features like Kubernetes. The combination of modern edge platforms, and software-defined edge systems, will become the mainstream way to deploy various edge systems in a multi-cloud world.

As more cloud and IT players participate in the development of 5G, the opening of the dedicated mobile ecosystem will become faster. It's too early for businesses to adopt 5G. In fact, in most enterprise use cases today, there is no significant difference between 5G and Wi-Fi. That will change in 2022 as more powerful and modern versions of 5G become available to enterprises. We will see the higher performance, higher scalability 5G with various new features, such as ultra-reliable low-latency communication (UR-LLC), and massive multi-machine type communication (MTC), gradually becoming more than traditional telecom More dominance (think: open source ecosystem, infrastructure vendors, non-traditional telecom).

 

 

As more cloud and IT players participate in the development of 5G, the opening of the dedicated mobile ecosystem will become faster.

 

 

More importantly, we expect the ecosystem to offer new and more functional dedicated mobility, gradually expanding to include IT providers like Dell Technologies, public cloud providers, and even open-source focused on accelerating the development of the open 5G ecosystem.

As data management becomes an entirely new class of workload, the margin will also become the new battleground for data management. The data management ecosystem needs a margin, and the modern data management industry has begun to turn to the public cloud to process and analyze non-instant centralized data on the public cloud. As the global digital transformation continues to accelerate, most data is generated and operated outside of centralized data centers. It is expected that the entire data management ecosystem will not only actively develop and use marginal IT as the input and output of the data pipeline but also use marginal remote processing and digest data.

As the data management ecosystem expands to the edge, the volume of marginal workloads and overall marginal demand will also increase dramatically. This also echoes our first prediction for edge platforms, which will be modern software-defined solutions for data management. Data management and margins will be integrated and strengthened. IT infrastructure providers like Dell Technologies have a unique opportunity to provide an orchestration layer for marginal and multi-cloud environments by offering marginal data management strategies.

The security industry has moved from talking about emerging security concerns to taking action. Businesses and governments face more complex threats and the impact these complexities have on revenue and services. At the same time, as the wave of remote work and digital transformation accelerates, the number of attack vectors available to hackers continues to expand. To this end, the information security industry has begun to increase the degree of automation and integration to respond. In addition, the industry's main axis has shifted from automated detection to prevention and response, focusing on the use of AI and machine learning technologies to speed up the remediation process. This is best evidenced by industry-driven initiatives such as SOAR (Security Orchestration, Automation and Response), CSPM (Cloud Security Posture Management), and XDR (Extended Detection and Response). Most importantly, we are seeing open security software organizations affiliated with the Linux Foundation start to promote collaboration, and the IT, telecommunications, and semiconductor industries are also actively participating.

 

 

Managing an ecosystem requires a margin.

 

In all four areas—including edge, dedicated mobility, data management, and security—public cloud and traditional infrastructure need to be integrated into a broad ecosystem. We are now in a multi-cloud and decentralized world with huge challenges that can no longer be solved by a single data center, cloud, system, or technology.

Outlook beyond 2022

Quantum computing: Hybrid quantum/traditional computing will be the focus, providing more ways to use quantum computing. In 2022, we expect two industry consensuses to emerge. First, the industry will see that quantum systems will inevitably evolve into hybrid quantum computer topologies, in which quantum hardware or quantum processors (CPUs), specialized computing systems in the form of accelerators,

are used to perform quantum computing. Aspects of mathematical operations and functions. A traditional computing system will be configured around the QPU to perform data preprocessing, run the overall program, and even interrupt the output of the QPU.

Early quantum systems followed this hybrid quantum model, and we see a collaborative model of conventional and quantum computing as the future. The second consensus is that quantum simulations using conventional computing would be the most cost-effective and feasible way to make quantum systems accessible to universities, data science teams, and research institutes. Dell and IBM have announced a joint effort to bring quantum simulation to the world.

Automotive: The focus of the automotive ecosystem will rapidly shift from the mechanical ecosystem to the data and computing industry. The automotive industry is transforming on several levels. We are seeing a shift in the industry from internal combustion engines to electric vehicles, leading to rapid simplification of the physical supply chain. In addition, with the R&D investment in advanced driver assistance systems (ADAS) and self-driving cars, the software and computing content for vehicles has increased significantly. The automotive industry is increasingly becoming a data-driven industry, ranging from entertainment and safety to disruptive business models such as Car-as-a-Service and automated delivery.

These all reflect the rapid transformation of the automotive and transportation industries through software, computing, and data. We have seen this situation in other industries such as telecommunications and retail, and ultimately the use of IT technology has improved. Dell Technologies actively participates in the initial R&D plans of most first-tier automakers in the world. It is estimated that in 2022, these manufacturers will continue to promote their digital transformation and have a deeper interaction with the IT ecosystem.

Digital Twins: Use proprietary tools to more clearly define its related technologies, making it easier for all walks of life to create and use digital twins. Although digital twins are gaining traction, they are still an emerging technology with only a few examples to date. In the coming years, digital twins will be easier to create and use as the industry defines standardized frameworks, solutions, and platforms. By improving the accessibility of digital twins, companies can strengthen their analytical and predictive models to accelerate digital transformation. By accelerating standardization and improving the availability of solutions and architectures, digital twins will gradually become mainstream, while reducing deployment and investment costs. Digital twins will be the core driver of Digital Transformation 3.0, bringing together measurement and model/simulation technologies to realize business value across industries.

As a tech optimist, I have come to observe that people and technology are collaborating with unprecedented speed to produce impactful results. The above near-term and long-term forecasts are based on our current development results. If we continue to progress in the future, we will have a considerable opportunity to make positive changes that will disrupt the way we work, live, and learn. 2022 will be another acceleration technology. A year of innovation and popularity.