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By: Daniel W. Rasmus for Serious Insights
AI PCs are coming. AI PCs will include a key that invokes a Microsoft Copilot. Copilot, as it does on Microsoft Edge and Windows 11, will pop up, informing the person pushing the key that it is ready to be asked anything. But that isn’t really an AI PC. It is a PC that integrates a generative AI chatbot at the most rudimentary level.
Previous versions of PC-based AI did live up to their promise. Cortana was too primitive. Like Apple’s Siri, it performed only rudimentary tasks. Microsoft deprecated Cortana as a Windows 11 feature. It now exists only as a download from the Microsoft store. I will return to Siri later, as it is likely Apple interface to AI.
AI will likely transform the way personal computers work. They will likely start with advanced information retrieval powered by voice-to-text (more likely direct voice, but the interface will mimic text in the background until the chatbot modalities evolve).
In my work with Microsoft, I suggested that one aspect of the future of computing would include “finding information for you.” This idea suggests that local devices build a model of the owner, as well as their information assets, including files and communications. When attending a meeting, for instance, the system will compile a view of information required by that person at that moment. Rather than asking, “Where is that PowerPoint?” the latest version will be at the top of the list of content required to support the meeting.
But this idea wasn’t new. At Forrester/Giga, I crafted planning assumptions that talked about two AI-influenced ideas. The first, I called Learning Architectures. It consisted of a block diagram with sections for “query generation” and “categorization engines.” These services sat upon metadata that enhanced context stored in what I called a “universal repository.” The universal repository was an abstraction of all types of content, from e-mail and structured data to the enterprise directory, collaboration platforms, videos, images, text, and sound. You get it. Everything. 24 years later, software makers still don’t sell a universal repository. Not IBM. Not Oracle. Not Dell. Not OpenText.
However, generative AI cheats by abstracting away the repository in its working memory, its vectors and weights. While it does not provide direct access to source documents via foundation engines, it starts to offer some of the features I described in my writing about Learning Architectures. To be clear, Learning, in this case, was about computers learning, not about supporting human learning, although the entire rationale for a Learning Architecture was to support people effectively finding, applying, repurposing, and collaborating on the content the system surfaced.
A year later, I started writing about Adaptive Workspaces. Adaptive Workspaces built atop the Learning Architecture with another layer of intelligence that looks at the end user computing experience as a set of indexable objects, from data to applications. It pointed to a fundamental flaw in the computing experience that still exists today: the lack of synergy between the computer’s owner, the data, and the work being done.
As with information finding you, Adaptive Workspaces suggest that the entirety of the computing experience be informed by the owner and the work. My computers, be they Microsoft Windows or Apple macOS-based, conform to my will because I have manually created environments that suit my needs. I have moved items to favorites or the taskbar because I wanted them there, not because the OS sensed a pattern in my work that would benefit from easier access to tools. That is a simple pattern recognition chore.
Slightly more complex would be the repeated process of compacting a PowerPoint-generated PDF with Adobe Acrobat and changing its name by amending an “email” to the smaller file. And while the Mac will remember my last configuration and start me off where I left off, it is not capable of reconfiguring itself on demand, to say, a start-up configuration. For me: Load TheBrain. Load Mail. Load the browser with the last open instances and sites. Load the Calendar. If the next calendar entry includes a conference call, load the appropriate meeting platform…
To find out if privacy will kill the AI PC, what an AI PC should do, and more, read the rest of the article: Thinking Out Loud: What Should an AI PC Do?
About the author:
Daniel W. Rasmus, the author of Listening to the Future, is a strategist and industry analyst who has helped clients put their future in context. Rasmus uses scenarios to analyze trends in society, technology, economics, the environment, and politics in order to discover implications used to develop and refine products, services, and experiences. He leverages this work and methodology for content development, workshops, and for professional development.
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