#195: Generative AI and the Resurrection of IoT

The Internet of Things (IoT) once promised to transform our homes, cities, and industries through seamless device connectivity. However, time has shown that connectivity alone does not equate to intelligence. Much like how constant engagement with social media floods us with information but doesn't necessarily make us smarter, the IoT's potential for creating a truly intelligent world has remained largely unfulfilled. Now, with the advent of generative AI and large language models, we stand ready to bridge the gap between mere connectivity and genuine intelligence—ushering in the era of the "Intelligence of Things."

GOFAI Could Only Go This Far

When IoT first emerged, it carried the promise of devices that could anticipate our needs, adjust to real-time data, and optimize processes autonomously. Early AI implementations, predominantly based on Good Old-Fashioned AI (GOFAI), were instrumental in achieving initial milestones. GOFAI, characterized by rule-based systems and symbolic reasoning, enabled devices to perform specific tasks efficiently. Whether centralized or decentralized, these systems followed predefined rules and algorithms, executing commands within the boundaries of their programming.

However, GOFAI lacked the capacity for true agency—the ability of devices to make autonomous decisions based on learned experiences and adapt to new situations without human intervention. Even with decentralized computing, GOFAI-powered devices were limited to scenarios anticipated by their programmers. They couldn't learn from their environment, handle unforeseen circumstances, or evolve their decision-making processes over time. This rigidity meant that while devices could execute complex computations locally, they remained passive tools rather than active agents.

Generative AI: Empowering Agentic Behavior in IoT

Generative AI introduces a transformative shift by endowing IoT devices with the ability to learn, adapt, and make autonomous decisions—a level of agency not achievable with GOFAI. Unlike rule-based systems, generative AI models are trained on vast amounts of data, enabling them to recognize patterns, understand context, and generate appropriate responses in dynamic environments. This empowers devices to act independently, making real-time decisions without constant human oversight.

For instance, during an emergency evacuation prompted by a hurricane, smart cars equipped with SLMs can autonomously analyze real-time data on weather conditions, traffic flow, and road closures. They determine the safest and most efficient routes, adapting instantly to new information like sudden floods or blocked roads, and can take occupants to a safe location. This example may seem to conflate two parallel evolutions, but convergence is closer than you think.

Conclusion

We all thought IoT was struck by the same lightning that zapped OpenStack—left smoldering in the annals of overhyped tech. But generative AI is bringing it back to life! By empowering devices to learn, adapt, and make autonomous decisions, generative AI transforms the Internet of Things into the "Intelligence of Things," fulfilling the original promise of a smarter, more responsive world.