LW - On AutoGPT by Zvi

<a href="https://www.lesswrong.com/posts/566kBoPi76t8KAkoD/on-autogpt">Link to original article</a><br/><br/>Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: On AutoGPT, published by Zvi on April 13, 2023 on LessWrong. The primary talk of the AI world recently is about AI agents (whether or not it includes the question of whether we can’t help but notice we are all going to die.) The trigger for this was AutoGPT, now number one on GitHub, which allows you to turn GPT-4 (or GPT-3.5 for us clowns without proper access) into a prototype version of a self-directed agent. We also have a paper out this week where a simple virtual world was created, populated by LLMs that were wrapped in code designed to make them simple agents, and then several days of activity were simulated, during which the AI inhabitants interacted, formed and executed plans, and it all seemed like the beginnings of a living and dynamic world. Game version hopefully coming soon. How should we think about this? How worried should we be? The Basics I’ll reiterate the basics of what AutoGPT is, for those who need that, others can skip ahead. I talked briefly about this in AI#6 under the heading ‘Your AI Not an Agent? There, I Fixed It.’ AutoGPT was created by game designer Toran Bruce Richards. I previously incorrectly understood it as having been created by a non-coding VC over the course of a few days. The VC instead coded the similar program BabyGPT, by having the idea for how to turn GPT-4 into an agent. The VC had GPT-4 write the code to make this happen, and also ‘write the paper’ associated with it. The concept works like this: AutoGPT uses GPT-4 to generate, prioritize and execute tasks, using plug-ins for internet browsing and other access. It uses outside memory to keep track of what it is doing and provide context, which lets it evaluate its situation, generate new tasks or self-correct, and add new tasks to the queue, which it then prioritizes. This quickly rose to become #1 on GitHub and get lots of people super excited. People are excited, people are building it tools, there is a bitcoin wallet interaction available if you never liked your bitcoins. AI agents offer very obvious promise, both in terms of mundane utility via being able to create and execute multi-step plans to do your market research and anything else you might want, and in terms of potentially being a path to AGI and getting us all killed, either with GPT-4 or a future model. As with all such new developments, we have people saying it was inevitable and they knew it would happen all along, and others that are surprised. We have people excited by future possibilities, others not impressed because the current versions haven’t done much. Some see the potential, others the potential for big trouble, others both. Also as per standard procedure, we should expect rapid improvements over time, both in terms of usability and underlying capabilities. There are any number of obvious low-hanging-fruit improvements available. An example is someone noting ‘you have to keep an eye on it to ensure it is not caught in a loop.’ That’s easy enough to fix. A common complaint is lack of focus and tendency to end up distracted. Again, the obvious things have not been tried to mitigate this. We don’t know how effective they will be, but no doubt they will at least help somewhat. Yes, But What Has Auto-GPT Actually Accomplished? So far? Nothing, absolutely nothing, stupid, you so stupid. You can say your ‘mind is blown’ by all the developments of the past 24 hours all you want over and over, it still does not net out into having accomplished much of anything. That’s not quite fair. Some people are reporting it has been useful as a way of generating market research, that it is good at this and faster than using the traditional GPT-4 or Bing interfaces. I saw a claim that it can have ‘complex conversations with customers,’ or a few other vague similar claims that weren’t backed up by ‘we are totally actual...

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04/13/2023

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Link to original articleWelcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: On AutoGPT, published by Zvi on April 13, 2023 on LessWrong. The primary talk of the AI world recently is about AI agents (whether or not it includes the question of whether we can’t help but notice we are all going to die.) The trigger for this was AutoGPT, now number one on GitHub, which allows you to turn GPT-4 (or GPT-3.5 for us clowns without proper access) into a prototype version of a self-directed agent. We also have a paper out this week where a simple virtual world was created, populated by LLMs that were wrapped in code designed to make them simple agents, and then several days of activity were simulated, during which the AI inhabitants interacted, formed and executed plans, and it all seemed like the beginnings of a living and dynamic world. Game version hopefully coming soon. How should we think about this? How worried should we be? The Basics I’ll reiterate the basics of what AutoGPT is, for those who need that, others can skip ahead. I talked briefly about this in AI#6 under the heading ‘Your AI Not an Agent? There, I Fixed It.’ AutoGPT was created by game designer Toran Bruce Richards. I previously incorrectly understood it as having been created by a non-coding VC over the course of a few days. The VC instead coded the similar program BabyGPT, by having the idea for how to turn GPT-4 into an agent. The VC had GPT-4 write the code to make this happen, and also ‘write the paper’ associated with it. The concept works like this: AutoGPT uses GPT-4 to generate, prioritize and execute tasks, using plug-ins for internet browsing and other access. It uses outside memory to keep track of what it is doing and provide context, which lets it evaluate its situation, generate new tasks or self-correct, and add new tasks to the queue, which it then prioritizes. This quickly rose to become #1 on GitHub and get lots of people super excited. People are excited, people are building it tools, there is a bitcoin wallet interaction available if you never liked your bitcoins. AI agents offer very obvious promise, both in terms of mundane utility via being able to create and execute multi-step plans to do your market research and anything else you might want, and in terms of potentially being a path to AGI and getting us all killed, either with GPT-4 or a future model. As with all such new developments, we have people saying it was inevitable and they knew it would happen all along, and others that are surprised. We have people excited by future possibilities, others not impressed because the current versions haven’t done much. Some see the potential, others the potential for big trouble, others both. Also as per standard procedure, we should expect rapid improvements over time, both in terms of usability and underlying capabilities. There are any number of obvious low-hanging-fruit improvements available. An example is someone noting ‘you have to keep an eye on it to ensure it is not caught in a loop.’ That’s easy enough to fix. A common complaint is lack of focus and tendency to end up distracted. Again, the obvious things have not been tried to mitigate this. We don’t know how effective they will be, but no doubt they will at least help somewhat. Yes, But What Has Auto-GPT Actually Accomplished? So far? Nothing, absolutely nothing, stupid, you so stupid. You can say your ‘mind is blown’ by all the developments of the past 24 hours all you want over and over, it still does not net out into having accomplished much of anything. That’s not quite fair. Some people are reporting it has been useful as a way of generating market research, that it is good at this and faster than using the traditional GPT-4 or Bing interfaces. I saw a claim that it can have ‘complex conversations with customers,’ or a few other vague similar claims that weren’t backed up by ‘we are totally actual...

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