Game playing is the next frontier. Model economically valuable tasks as games and have the agents play/compete. Alphabench and Vendingbench show the potential of this approach.

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ossa-ma a day ago | parent [-]

A decade of reinforcement and agentic learning was spent playing games (Google Deepmind AlphaGo, AlphaStar, OpenAI Five), including against each other. So what makes it a new frontier?

	▲	CuriouslyC a day ago \| parent [-]
		Its application to LLMs to push capabilities. We're going to tap out expert feedback, and objective/competitive arenas are going to be the only way to progress at a reasonable speed. The difference is going to be instead of starting from pre-existing games and hoping that "generalizes" to intelligence, this time people are going to build gamified simulators of economically valuable stuff. This is feasible now because we can use LLMs to help generate these games much faster than we would have been able to previously.