While the concept of an AI PC has been developing for several years, the buzz around AI PCs picked up speed in late 2023 and ushered in a new generation of processors with superior AI processing capabilities, and Microsoft integrated CoPilot into every PC by . However, making a PC intelligent is more than just running a neural network model on the PC, it’s also about making it contextually aware of its environment and the user (or users). This requires the use of sensors, network information, user information, and low-power processing that can be always-on and continuously adaptive. In this regard, this field is one of thousands of opportunities to exploit the capabilities of programmable gate arrays or FPGAs.
Contextual awareness
Context awareness, or the ability to understand and adapt to a specific environment at a given time, is something that is inherent in humans, but is of entirely new and increasing importance to electronic devices.
PC OEMs and technology providers are already developing AI technology that uses information from image sensors to enhance the security of PCs, such as human recognition, facial recognition, attention sensing, and threat monitoring. to allow signing in and locking PCs for In use or when a security threat, such as an unauthorized user or a third party watching over your shoulder, is detected. But the matter should not end there. A mobile PC must be able to determine whether you are at home, in the office or in a restaurant so that it can access the networks and peripherals available to you and adjust the level of security accordingly. can be done An intelligent PC should also be able to use AI agents to adjust the environment (temperature, lighting, music, etc.) to your liking or needs. In the end, building an intelligent PC is more than running AI models to improve productivity applications.
The wide world of sensors
This is where sensors and sensor processing come into the equation. PCs, especially mobile PCs, already have some level of sensing for system temperature, image and audio. There is a surprising amount of information that can only be obtained from external image and audio sensors, including the identification of people and other objects, the identification and verification of the user and others in proximity, the user’s movements, their User health (yes, even heart rate and temperature), spatial dimensions of the environment, objects within the environment, and identification of the environment itself. This points to the continued development of sensor technology, which will continue to improve and, as with most electronic platforms, will likely integrate additional sensors to gather even more environmental information. However, all this raw sensor data requires real-time or near-real-time and on-device processing to ensure data security and minimize latency, even when the rest of the system is asleep. be in a state of This processing should also be adapted to transform AI models and use cases/experiments on PC life. This is where low-power FPGAs come in.
Lattice Semiconductor is working with leading PC OEMs including Dell, Lenovo, LG, and others using its industry-leading low-power CrossLink-NX family for vision processing and even its Avant general-purpose FPGAs. is being used for higher levels of sensor processing in the future. Lattice CrossLink-NX products combine processing, a digital signal processor (DSP) for matrix multiplication, on-chip memory, and a flexible FPGA fabric for flexible I/O configurations given the often heterogeneous nature of sensor interfaces. is important. With smaller package sizes, lattice devices can be located on or near the sensor. Additionally, by taking advantage of parallel processing, Lattice devices can only operate at 150MHz, which allows them to run forever while drawing only milliwatts. This is done not only by offloading sensor processing from the host processor, but also by allowing multi-GHz host processors and most systems to enter a sleep state more frequently, even between key clicks or frame updates. Saves electricity in quantity.
Additional power savings and security come from using sensor information to automatically dim the display when the user is not looking at the screen or when someone else is walking behind the user. And for a better user experience, sensor information is used to automatically increase the brightness of the display if the user is sleeping or has trouble viewing the screen by squinting. These are just a few of the many ways that image sensors with Lattice Crosslink-NX are being used today with AI models and new sensor applications are being developed.
With multiple programmable functions, Lattice products provide adaptability to different product configurations, new AI models, new data standards, and even different interfaces without changing the hardware.
The best part is that the PC is benefiting from the innovation driven by other platforms and vice versa where Lattice FPGAs are used. The sense of user attention is similar to the driver monitoring technology used in vehicles. Security controls are similar to government and healthcare applications. Display brightness control is similar to brightness control in commercial lighting. And security monitoring comes directly from commercial security systems. The applications for sensors are nearly endless as innovative companies devise new ways to use sensors and sensor data. One of the most unique uses is for user interfaces, such as gesture control, a common feature for VR headsets that is likely to become more common on other consumer devices such as TVs and PCs in the future.
Focus on intelligence
While AI is the buzz word of the day, intelligence is the ultimate goal of every consumer and commercial electronic platform. And while a multi-GHz processor can potentially provide all the processing needed to get the job done, it’s not an efficient use of performance, nor is it a great drain on the battery in this type of use. It is likely to provide a positive user experience. Creating intelligent solutions will require a hybrid approach to improve overall system performance, efficiency and security. One of the key technologies to enable the latest advances in AI and intelligence is FPGAs. While in the past, FPGAs were often viewed as a niche technology used in the development process of more advanced technologies or used in specialized applications with very low volumes, these performance enhancement factors So changing with focus on small/low power. and functionality. FPGAs are flexible and adaptable to needs such as different sensors, and can be a cost- and power-efficient solution for more intelligent PCs and other electronic platforms.
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The author and Tirias Research staff members do not hold equity positions in any of the companies mentioned. Tirias Research tracks and consults for companies in the electronics ecosystem, from semiconductors to systems and sensors to the cloud. Tirias Research has consulted for Dell, HP, Lattice, and companies in the semiconductor, PC, and general electronics ecosystem.