The technologies that define this year are not limited to spectacular announcements at trade shows. Several fundamental changes are altering the way we use our computers, protect our data, and design digital services. Three main themes emerge: artificial intelligence migrating directly into our machines, a European regulatory framework redefining the rules of the game, and environmental pressure pushing the industry to rethink its infrastructures.
NPU and AI PC: when artificial intelligence settles in your computer
Have you noticed that some photo editing or voice transcription functions now work without an internet connection? This is no coincidence. Since the end of 2024, a new generation of processors has included a dedicated AI computing chip, called NPU (Neural Processing Unit).
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In practical terms, instead of sending your data to a remote server for analysis, your computer processes it itself. A telling example: during a video conference, real-time video editing (background blurring, lighting correction, noise removal) is performed locally. The result is faster, and your images do not pass through the cloud.
Microsoft, Intel, AMD, and Qualcomm are promoting this category of machines. Microsoft launched its Copilot+ PCs in spring 2024, with Windows natively integrating generative AI and assistance functions. To keep up with high-tech news on Info Geeks, this shift towards embedded AI is likely the most significant hardware change since the advent of SSDs.
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This transition affects both the general public and professionals. For office work, content creation, or data management, the NPU transforms the PC into a permanent local assistant. The difference from previous years is that AI is no longer a remote service charged by usage, but a capability integrated into the machine from the moment of purchase.
European AI Act: the regulation that changes tech product design
The other significant event this year concerns the legal framework. The European AI Act, adopted in 2024, began to be gradually implemented in 2025. This regulation classifies artificial intelligence systems by risk level and imposes different obligations based on the category.
For a user, this translates into visible changes. Services using generative AI must now clearly indicate when content (text, image, video) has been produced by a machine. Foundation models, those powering chatbots or creation tools, are subject to transparency obligations regarding their training data.
What the AI Act imposes on manufacturers and publishers
- High-risk AI systems (health, recruitment, credit scoring) must document their operation and prove the management of algorithmic biases before being brought to market.
- Foundation models used in consumer applications are required to provide accessible technical documentation, including information on the datasets used for training.
- Compliance must be integrated from the product design phase, not added later as a fix.
For tech companies, this regulation alters the development timeline. Designing a compliant product from the start is cheaper than correcting it post-launch. European startups that incorporate these constraints early have an advantage: their products are immediately marketable in the European market without adaptation.
Green data centers and AI model efficiency
Training artificial intelligence models consumes considerable amounts of energy. This reality has pushed the industry in two complementary directions: reducing data center consumption and designing lighter models.
Green data centers utilize renewable energy and less energy-intensive cooling systems (liquid cooling, free cooling with outside air). Several projects in Europe prioritize locations where electricity primarily comes from decarbonized sources.
Compact AI models: doing more with less
At the same time, a technical trend is strengthening: the compression and optimization of AI models. Rather than multiplying parameters (the race for the “largest possible model”), some labs are working on more efficient architectures that achieve comparable performance with a fraction of the necessary computing power.
This approach directly aligns with the logic of the AI PCs mentioned earlier. A compact model can run on a local NPU, without relying on a remote server. The benefits are twofold: less latency for the user and reduced load on cloud infrastructures.
Connected devices and health: clarifying uses
The connected health sector exemplifies the convergence of these trends. Next-generation connected devices no longer just measure heart rates or count steps. At CES 2025, innovations like Omnia (a connected mirror capable of analyzing health indicators) demonstrate that health data is increasingly processed locally, in line with the privacy requirements of the AI Act.
Augmented reality applications are also advancing in the professional field. Glasses like Halliday’s, which project a screen into the field of vision, find uses in industrial maintenance, logistics, and training. These devices combine sensors, embedded AI, and real-time display.
- In health: connected mirrors, home air quality sensors, advanced biometric tracking devices with local data processing.
- In industry: augmented reality glasses for field operations, robots trained virtually before physical deployment (Nvidia’s Cosmos platform).
- In daily life: AI assistants integrated into household appliances, smart energy management for homes.
The common thread among all these innovations remains the same: bringing data processing closer to the user, reducing dependence on the cloud, and adhering to a stricter regulatory framework. This year’s high-tech trends are not isolated gadgets. They outline a digital infrastructure where computing power, energy efficiency, and legal compliance advance together.