Avalue Technology News Center

2025 is shaping up to be a big year in AI computing. Technological developments like AI quantum computing and AI edge computing are really hitting their stride, but there are other evolutions we can expect too.

While this is not an exhaustive list, our guide outlines six of the most important AI computing trends to expect over the coming year.

Edge computing has been around for a number of years already, but we can expect it to come into its own in 2025. The term 'AI edge computing' will be used to refer to two complementary forms of technology:

1. Edge computing systems that gather and process data for deployment in AI large language models and other structures
2. Edge computing systems that are designed using AI itself

So, the placement and operation of a product like the ACS10-TGU fanless system can be governed and optimized by an AI network, helping teams get more from the technology. At the same time, the component will feed data back to AI systems, providing intermediary processing to give these systems the training data they depend upon.

This idea of AI simultaneously supporting – and being supported by – edge computing hardware is going to be a significant trend across the year.

Much of the public perception of AI is based on one specific subset of smart technology – generalized generative AI solutions like ChatGPT. However, 2025 is going to be the year that AI technology grows more targeted.

A general solution like ChatGPT is not going to provide the right results in specialized fields like healthcare or manufacturing. The data it draws upon is simply not of a high enough standard. This year, we will see more and more targeted solutions, built using specialized datasets that have been prepared and structured to facilitate artificial learning.

Human experts still have a lot of input here. These experts will be required to select and label data for AI training. With this foundation, targeted AI can achieve highly sophisticated results across a wealth of different fields.

As we've seen above, human and AI hybrid operations are important to the development of smart technology. This includes things like robot healthcare assistants that interact directly with patients, and human customer service personnel who are backed up by an AI solution. In retail, 77% of respondents to a recent survey said that a human team member using AI was better positioned to answer their queries than a chatbot operating by itself.

This highlights a common trend in AI technology. AI is not replacing human operatives wholesale and is instead being adopted to make life and work easier. Finetuning human/AI interactions will become a significant part of technological development in the near future.

The emergence of the Chinese AI computing solution DeepSeek at the beginning of the year rocked the foundations of the artificial intelligence world. Compared with more established industry heavyweights like Open AI, DeepSeek is capable of far higher levels of performance while drawing upon comparatively fewer resources.

This new competitor underlined something inherent to AI computing development – it's not enough simply to provide huge amounts of power; this power needs to be delivered in an accessible, affordable, and sustainable manner. As sustainability becomes an increasing concern for AI solution developers, we can expect to see more solutions that promise to do more with less.

With this in mind, developers will look to achieve more power with fewer chips, turning to powerful components like the ESM-APLM COM mini module or the Rockchip-powered RSC-3576 SBC. These components support streamlined pieces of hardware without compromising on processing power.

AI quantum computing promises to be a significant trend in 2025 and beyond. With quantum computing, systems are able to transmit data and perform calculations at unprecedented speeds, essentially revolutionizing digital operations for years to come.

An ongoing question surrounding AI centers on computing power. Just how are we able to develop systems with enough power to support the AI solutions we conceive of? AI quantum computing offers a real answer here. Quantum-based systems can achieve this kind of capability with ease, and as quantum computing develops, we'll be able to provide this capability with an increased focus on sustainability too.

Quite how AI quantum computing will manifest in practice itself remains to be seen. But the development of powerful systems with reduced resource appetites is going to be critical to the growth of AI in the near future.

AI computing technology is both at the forefront of the latest cybersecurity efforts and also one of the biggest potential weak points. With so much data involved in the training and development of AI technology, it needs to be protected from potential cybercriminals. At the same time, the highly powerful nature of this technology means that AI is being used to create cutting-edge cybersecurity tools.

Increasingly, we are seeing AI used to assess huge datasets, looking out for potential anomalies or evidence of cyberattacks. Machine learning functionality, trained using data from historical cyberattacks, is now able to identify possible infringements far more effectively than a human team could. AI edge computing also plays a role here – by removing many of the links in the data processing chain, there are fewer points of vulnerability for cybercriminals to exploit.

At Avalue, we have developed a strong reputation for providing industry-leading components and other solutions for organizations around the globe. Whether you are operating in healthcare, retail, manufacturing, logistics, or another sector, we can help you build the systems you need. Explore our product range today, or reach out to our team directly to discover more.