Gaming, Goats & General Intelligence with Frederic Besse
Google DeepMind: The Podcast
Understanding Physical and Virtual Agents in AI
Agents in AI can be categorized into physical and virtual types. Physical agents, such as robots, operate in the real world and are capable of performing tangible actions, making them directly useful in practical applications. Virtual agents, on the other hand, exist in abstract spaces, which can include simulated environments like video games or software programming contexts. These virtual agents may not have a physical presence but can take actions such as writing code or interacting with digital resources. The distinction between these agents and traditional chatbots lies in their operational contexts. While chatbots primarily output natural language and may perform limited functions, they do not act in dynamic environments where their actions have significant consequences. Moreover, chatbots operate based on pre-trained data scraped from the internet, lacking the capacity for interactive learning through trial and error, which is essential for agents operating in real or simulated environments. This fundamental difference highlights the varied capabilities and functional implications of physical versus virtual agents in AI systems.
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