Nobody knows yet what we will eventually come to know as an “AI PC.” But it is almost certainly going to be more than new keys that offer shortcuts to one or more generative AI models and services, as currently is the developing practice. Almost everyone expects that AI PCs will include hardware allowing on-board processing or faster processing.
Some point to neural processing units--specialized chips designed for efficient AI tasks--that offload AI workloads from the CPU and GPU, improving overall performance. Others expect significant increases in random access memory and faster storage solutions probably using solid state devices.
Others might point to the use of AI assistants that anticipate user needs and proactively offer suggestions, such as automatically summarizing documents you're reading or translating content on the fly. The assistant would understand your workflow and automate repetitive tasks, providing a “context-aware” experience.
The assistant could pre-fetch relevant data, suggest actions based on your activity, and personalize the user experience.
Most think AI PCs will conduct on-device processing for at least some operations, avoiding full reliance on remote processing. But one has to ask "So what?" as a rhetorical quesiton. What experiences and use cases will benefit from local processing?
Personalization, sure. Image processing or speech-to-text, sure. Still, what improvement might be possible, compared to using remote processing? The issue isn't "using AI," but rather where we do the processing.
To a greater or lesser extent, AI PCs might be able to learn and adapt over time, personalizing their functionalities to a user’s specific needs and preferences.
And some might believe AI PCs will be open enough to allow developers to create new AI applications and extend the capabilities of the PC.
But it remains unclear at this point that the suggested use cases for AI necessarily require on-board processing. Much of the value of AI could still be provided by remote processing.
For example, it is not clear that on-board processing has much value for use of AI assistants to brainstorm ideas, generate creative text formats, or streamline workflows for writers, designers, and students.
And though on-board processing is deemed an advantage for smartphones, AI-PC editing tools might not add much value, as such editing is likely not to require real-time adjustments.
Automation of repetitive tasks such as data entry or file organization likewise might not provide much value over remote processing.
Most personalized learning or education use cases would be using remote data bases in most, if not all, cases, so remote processing might also be adequate to support those activities, and not require on-board processing.
Similarly, it might be questionable whether on-board processing is need to support many entertainment and gaming use cases, as access to remote databases would be required in any case.
Remote AI is likely good enough for personalizing entertainment recommendations based on user preferences and watch history; dynamic, adaptive storylines for gaming or music composition.
AI assistants might arguably be more important for voice commands and speech-to-text or language translation “on the fly.”
But other potential use cases, aside from facial recognition for security purposes, might work just as well using remote computation. Many security monitoring tasks, for example, could be handled that way.
The point is that AI PCs are likely to be a niche product initially, partly because of high cost, and partly because there will not be many consumer applications that actually benefit.
No comments:
Post a Comment