Generative artificial intelligence might be likened to several elements of personal computing. Just as personal computers revolutionized how individuals interacted with technology, generative AI is poised to fundamentally change the consumer relationship with machines. Machine learning, in contrast, remains largely an enterprise use of AI.
Both personal computers (more aptly, the applications and software consumers can run on PCs) and generative AI models are accessible to a wide range of users, for “daily life” tasks, regardless of their technical expertise.
User-friendly interfaces (graphical user interfaces, for example; “what you see is what you get” displays); multimedia content; portability and mobility and a focus on content (social media; driving directions; answers; price discovery; product or service availability; entertainment; ordering and learning) made PCs the first consumer-focused computing experiences.
Generative AI, with its focus on content and conversational interface, likewise makes it useful for consumers in applications including entertainment; learning; answers; ordering; price discovery and availability; o business and research.
Similarly, generative AI is being applied to a wide array of consumer tasks, including content creation, customer service, and scientific discovery.
Also, the GenAI adoption context is quite different from that of the first PCs. Unlike PCs, which required something of a paradigm shift in how people interacted with technology, generative AI often enhances tools people are already using. So where PCs were largely disruptive or revolutionary, GenAI is mostly incremental and evolutionary.
Early PCs had no keyboards, monitors or convenient storage. They required extensive hacker skills; investment in new hardware and did not immediately solve any common consumer problems. GenAI is almost the polar opposite, enhancing and improving lots of experiences consumers already are using, using existing hardware and platforms.
Natural language is similar to the graphical user interface in terms of enabling an easy human interaction with the machine and its software.
So writing assistants improve or enhance word processors; enhance photography; improve search and e-commerce or social media personalization. AI assistants extend capabilities of existing voice interfaces and appliances.
Where personal computing originally had high barriers to entry (which became far lower with graphical user interfaces; point and click), genAI has low barriers to entry, using conversational language interactions on existing software and applications and existing hardware and platforms.
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