| Last year, researchers from Google and Stanford University populated a virtual village with about two-dozen ChatGPT-powered characters. The Sims-like personas could remember their roles, go on dates, challenge each other to competitions; they even coordinated to throw a Valentine's Day party. Believe it or not, this sleepy little AI town held some clues about a new stage in the generative AI hype cycle. Tech giants and startups alike are increasingly thinking about how large language models (LLMs) can move beyond chatbots and into autonomous "agents" that can perform tasks on their own accord. More than just answering questions and proffering information, this new crop of systems tap LLMs to actually complete multi-step actions, from developing software to booking flights. While the tech is still relatively nascent, it's progressed in the past year. Google DeepMind recently unveiled an AI agent called SIMA that was trained on 3D video games, including something called Goat Simulator 3, to handle around 600 skills, from navigating the games to opening menus, demonstrating what the research arm called "the potential to develop a new wave of generalist, language-driven AI agents." Mike Gozzo, chief product officer at customer service AI company Ada, said he's seen a shift from a nearly singular industry focus on retrieval-augmented generation—LLMs that can navigate and interact with big databases of information—to autonomous agents in recent months. He said Ada has been working with agents since around the time the tech first began to pique developer interest last year, when OpenAI rolled out Auto-GPT. "I've got this meeting with [OpenAI CEO] Sam [Altman] coming up later today. I was in DC with [Microsoft CEO] Satya [Nadella] a few weeks ago. And like, that's all anyone is talking about is how do we get to autonomy in these systems?" Gozzo said. "And the reason why it's even relevant at all is that, far beyond customer service, I think there's going to be a trend in all software to move through this autonomous agent-style workflow." Keep reading here.—PK | 
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