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Artificial intelligence (AI) devices have been a trend so far this year. With its growing popularity, electronics manufacturers are now marketing what they have historically referred to as computer chips as ‘AI Chips’ and their devices’ AI capabilities, creating unique selling points and differentiators in their products.

Microsoft (NASDAQ: MSFT) was one of the first companies to announce its first generation of AI PCs, and then they took it a step further by adding a new button to their keyboards dedicated to its AI assistant ‘copilot.’

But Microsoft is not alone in its quest to bring AI PCs to market, with Nvidia (NASDAQ: NVDA) announcing a new line of ‘Super’ graphics cards that are better able to handle AI tasks. Nvidia says these graphics cards significantly speed up language and image model processing, generating video and images 1.7 times faster and 1.5 times faster, respectively.

Additionally, Nvidia says it is collaborating with several leading PC manufacturers like Acer (NASDAQ: ACEYY), ASUS (NASDAQ: ASUUY), Dell (NASDAQ: DELL), HP (NASDAQ: HPQ), Lenovo (NASDAQ: LNVGF), MSI (NASDAQ: MSI), Razer (NASDAQ: RAZFF), and Samsung to introduce laptops that are “AI-ready” and featuring these new cards. These notebook computers are expected to start shipping this month.

This latest development supports the overall trend of manufacturers trying to bring more AI capabilities to the mainstream consumer market.

The core of AI computing

The strength and capabilities of the chip that powers the computer are what determine whether a computer is an AI PC or not. While industry leaders like Nvidia are still opting to use GPUs that are powerful enough to run AI tasks locally rather than outsourcing them to the cloud, other semi-conductor manufacturers are increasingly beginning to introduce Neural Processing Units (NPUs) into their chip lineups so that computer manufacturers can use them in parallel to CPUs and GPUs.

NPUs are computer chips that are specifically designed for processing AI operations. NPUs enable advanced features like facial recognition, real-time language translation, and augmented reality (AR). In data centers, they accelerate AI-based tasks like image and speech recognition, natural language processing, and data analytics. Earlier this year, we saw Intel (NASDAQ: INTC) announce a new chip with an NPU. We also saw Intel CEO Pat Gelsinger say that “the AI PC will be the star of the show for the upcoming year.”

AI integration vs. hardware

Although AI chips in new laptops and computers are making headlines, will an AI chip be enough to persuade consumers to switch from their current devices to these AI devices? Currently, most existing laptops and computers aren’t specifically designed with AI optimization in mind, yet they manage to perform AI tasks, thanks to cloud computing.

For the average user, cloud-based AI processing seems sufficient; the typical consumer is probably not creating, running, or training AI models locally, and those who usually possess the technical know-how to find or outsource the necessary hardware for their projects, which means that the current selling point of these AI-chips will only appeal to a small population.

That being said, I do believe Microsoft’s introduction of the Copilot button on its keyboards would be a compelling reason for consumers to consider upgrading their devices. When activated, the Copilot, powered by OpenAI, emerges on a split screen, offering real-time AI assistance with the task at hand. This feature goes beyond the simple selling point of enhanced AI capabilities and directly addresses the convenience and integration of AI that the average computer user is looking for.

Rather than selling consumers the ability to run AI locally, I think what consumers really want is the ability to integrate AI into their workflows seamlessly.

For example, consider the current workflow when using AI to assist in drafting an email. At the moment, users need to toggle between an email client and a separate AI chatbot or model, but with a feature like Microsoft’s Copilot, the AI assistant is brought directly into the user’s current screen, eliminating the need to switch between multiple tabs and reducing workflow friction. This kind of integration, where AI assistance is woven into everyday computing tasks, is more likely to draw consumers than the raw power of AI-specific hardware.

Consumer-centric AI integration vs. AI as a buzzword

Microsoft’s introduction of the Copilot key is a prime example of how AI can be thoughtfully integrated into everyday technology to align with consumer needs.

Unlike the mere inclusion of an AI chip, Copilot offers a practical, user-friendly approach, providing real-time assistance directly within the user’s workflow. This reflects a deeper understanding of how consumers actually want to use AI as an integrated tool that enhances their computing experience.

At the same time, these two very different approaches that we see manufacturers take to deliver an AI PC underscores a more significant, more concerning trend in the AI space—AI is becoming a buzzword.

The newly announced AI devices at CES 2024 show a growing trend of companies incorporating ChatGPT or similar AI models into products, regardless of their necessity or practicality. This approach not only dilutes the true potential of AI but also leads to market saturation with products that offer little real value to the consumer.

Consumers have shown a demand for AI solutions that genuinely make their lives easier and more efficient. It is becoming clear that people are interested in AI that seamlessly integrates into their existing processes, reducing friction rather than making a task more complex.

Companies must pay close attention to where this demand lies and create solutions that meaningfully improve existing workflows. Once they achieve this, the transition to AI-powered products will become a natural choice for consumers. They will no longer be torn between sticking with their current devices or opting for new AI-equipped ones, and the increase in efficiency provided by thoughtfully designed AI solutions will make the decision a no-brainer.

In order for artificial intelligence (AI) to work right within the law and thrive in the face of growing challenges, it needs to integrate an enterprise blockchain system that ensures data input quality and ownership—allowing it to keep data safe while also guaranteeing the immutability of data. Check out CoinGeek’s coverage on this emerging tech to learn more why Enterprise blockchain will be the backbone of AI.

Watch: What does blockchain and AI have in common? It’s data

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