AI Geeks are Hyped About Agents

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👀 Today’s Thing: AI Geeks are Hyped About Agents

🤖 Chatbots built on LLMs are cool. They’re probably world-changingly amazing, even. But what if you could task a powerful AI not just with a single prompt, but with autonomously completing a multistep task? Some see software that can break a task into subtasks, and carry them out as part of achieving a larger objective, as the next step towards artificial general intelligence (AGI). We call these systems AI Agents, or Intelligent Agents, and they’re one of the more interesting applications being built atop GPT-4 right now.

🎧 Want to go deeper? Geoffrey Hinton, the subject of Monday’s newsletter, mentioned agents as one of the reasons he’s scared about the future or AI. In the same article, however, another industry heavyweight — Meta’s Yann LeCun — says, intelligent machines will usher in a new renaissance for humanity.”

📖 Backstory

☞ Right now, agents can have pizza delivered to your house, and not much else (at least not consumer-facing agents). Meta chief Mark Zuckerberg is excited about other business-y applications, saying, “I expect that a lot of interest in AI agents for business messaging and customer support will come once we nail that experience.” But throw in some self-learning capabilities, and maybe - maybe - we’re talking about a step towards AGI. Artificial General Intelligence, or AGI for short, is human-level intelligence.

☞ Auto-GPT, created by Toran Bruce Richards, and BabyAGI, built by Yohei Nakajima, are two experiments that have attracted a lot of attention. Both are built atop GPT-4, and both are very early stage, requiring a lot of human intervention and not yet reliable when it comes to achieving their goals. That said, I tried Auto-GPT on my laptop, and it was wild to watch it create new agents and write code on its own.

☞ Reddit’s r/ChatGPT subreddit is blowing up with links to experimental agents of all sorts:

🔑 Keys to Understanding

🥇 OpenAI’s ChatGPT is hugely powerful, but it only responds to one prompt at a time, like a conversation. Agents carry out the full conversation for you, until a solution or objective is reached.

🥈 Agents can also access tools to execute sub-tasks. For instance, if you tasked an agent with making money for you, and GPT suggested gambling on the stock market using a bespoke trading algorithm, the agent could build a trading app. Provided you gave a sophisticated enough agent full access to your computer, Internet connection, and bank accounts, the agent could then use the app to buy and trade stocks until either the objective was met or it ran out of resources (in this case, computing and/or monetary).

🥉 One of the fears about AI is that sufficiently advanced agents will hoard resources (like computing power and energy to run the computers) in the name of completing their objectives, even if it means harming humans (locking them out of the computers and energy grids) in the process. Balancing autonomous AI capabilities with human oversight will be key to making agents useful and safe.

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Until the next thing,

- Noah

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