In short
The AI Daily Brief Podcast Summary
Episode Title
How to Get AutoGPT on Your Phone (And What People Are Actually Finding it Useful For)
Overview In this episode of *The AI Daily Brief*, the host discusses the AutoGPT tool, updates on recent AI news, and what people are finding useful about AutoGPT six weeks after its launch. The episode covers multiple trending topics in the AI space, including developments from major companies like Google and IBM, as well as predictions regarding AI's impact on jobs.
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Key Topics Discussed
Segment 1
Updates on AI Regulations and Investments
- U.S. Copyright Office Update:
- Clarification on AI-generated works and copyright.
- Human-created works using AI can be copyrighted if substantial human input is evident.
- Fully machine-generated works remain uncopyrightable.
- Venture Capital Enthusiasm:
- A Pitchbook survey indicates 36.1% of VCs expect AI to lead tech growth in the next year, surpassing other fields like climate tech.
- 70.7% believe generative AI will create unicorn startups.
- Palantir's Stock Surge:
- Following the announcement of new AI features, Palantir's stock increased by over 20%.
- Google I/O Developer Conference:
- Leaked documents hint at updates to Google's language model, Palm 2, with support for over 100 languages.
- IBM's WatsonX:
- IBM relaunches its AI division focusing on enterprise model training, collaborating with Hugging Face to enhance AI capabilities.
- Job Market Predictions:
- AI expert Ben Goetzel predicts that AI could replace up to 80% of jobs, with implications for societal adaptation and job transition.
Segment 2
AutoGPT and Its Applications
- Introduction to AutoGPT:
- AutoGPT offers a more interactive and autonomous experience than traditional ChatGPT by being connected to the internet and auto-generating task lists.
- Functionality:
- AutoGPT has proven effective for tasks involving up-to-date research and self-prompting.
- Limitations remain in executing tasks autonomously, with users often experiencing loops or inefficiencies.
- Specialized Tools:
- Users have shifted focus from generalized applications to specialized use cases.
- Tools like iBabyAGI have emerged, enhancing the accessibility of AutoGPT-like experiences on mobile devices.
- iBabyAGI Experience:
- Developed by Nate Chan to facilitate AutoGPT-style interactions on iPhones.
- Early testers report successful applications in travel planning, SEO analysis, and sales prospecting.
Segment 3
Practical Use Cases and User Experiences
- User Feedback on iBabyAGI:
- Testers highlight the app's efficiency, ease of use, and ability to execute tasks without getting stuck in loops.
- Examples of successful tasks include generating travel itineraries, SEO suggestions, and automated sales tools.
- Challenges and Innovations:
- Users noted that specificity in task requests leads to better outputs.
- The combination of human oversight and AI task management shows promise in optimizing productivity.
- Emerging Patterns:
- Developers are exploring the balance between human and AI roles in task execution, leading to enhanced collaboration and productivity.
- The potential for brainstorming and ideation assistance appears to be an underappreciated feature of AutoGPT tools.
Future Considerations
- The episode discusses potential developments in AI tools, including OpenAI's enhancements to ChatGPT with browsing capabilities.
- The impact of these advancements on the need for AutoGPT-style tools remains an ongoing area of exploration.
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Conclusion This episode of *The AI Daily Brief* provides a comprehensive look into the evolving landscape of AI tools and their implications for users and industries. The insights shared highlight both the excitement surrounding innovations like AutoGPT and the challenges that come with their implementation, ultimately emphasizing the need for specificity and human-AI collaboration in achieving effective results.
For more updates and discussions on artificial intelligence, listeners are encouraged to subscribe to the podcast for daily insights.
Written by AI. May contain mistakes. Listen to the episode to check what was said.
Transcript
Automatic transcript. May contain errors.0:00On this episode of the AI Breakdown, we are talking all about auto-GPT, a new tool for getting it on your iPhone, plus what people are finding it useful now six weeks after it came on the market. and when some of the hype has died down. Before that, on the AI Breakdown Brief, we cover new updates from Google and IBM on AI strategy, as well as a bold prediction that 80 % of jobs will be replaced by AI. Welcome back to the AI Breakdown Brief, the headline AI news you need in five minutes or less. We start today with updates from the U.S. Copyright Office. Obviously, AI has been a copyright challenge, and the Copyright Office has updated their guidance.
0:40Basically, they wanted to clarify that when humans create works with AI, it can still be copyrighted as long as there is sufficient human creation involved, such as bringing together lots and lots of AI-created inputs into a larger whole. What can't be copyrighted right now are things that are entirely created by machines. Now, obviously, copyright is going to be one of the big issues as we figure out how to integrate AI with existing societal norms. Grimes continues to be on the front of this. I saw this quote from her yesterday where she said, I'm actually kind of stressed that people are starting to make competitively or maybe better quality Grimes sounding songs than I do, but it's also the most wonderfully poetic way to die and respawn in another career.
1:24If you want to hear one of those AI Grimes songs, go check out the weekly recap from Saturday. It has a track from Angel Baby that uses Grimes AI at the end. Next on the AI breakdown, no surprise here, but VCs are excited about AI. This is from a PitchBook survey, and they asked, in which areas of technology do you expect the most growth and adoption over the next 12 months? 36.1 % said artificial intelligence, more than double the second place contender, which was climate tech at 18.1%. Now, in addition, over two thirds of investors that were surveyed, 70.7 % said that they thought that generative AI would spawn unicorns.
2:01No surprises there. I would only caution that there is going to be a temptation for people to write off much of AI because VCs are giving it such hype. Don't fall prey to it. Just because VCs are overhyped and are going to invest in things that probably don't deserve their investments doesn't mean that the overall trend isn't correct. Part of why VCs are so keen to invest is that public markets are also recognizing the power of AI. Palantir last week showed off some of its new AI features, and its stock has gone up more than 20 % since then. They say that demand for AI tools is unprecedented. Speaking of which, we've been keeping track of Google's plans.
2:40Google feels quite far behind, I think especially from where people would have expected Google to be. And this week is their big IO developer conference. Another set of leaked documents from inside Google gave us some hints about what's coming at IO, including the update of their large language model Palm, which they're calling Palm 2 and includes more than 100 languages. That will be used to power Bard, and they're hoping to reclaim some momentum at this event. Speaking of reclaiming momentum, do you guys remember Watson, that IBM early AI product that was created to beat humans on Jeopardy? Well, that business line had basically gone nowhere.
3:17In fact, 15 months ago, IBM had sold its Watson Health unit, but now they are bringing the Watson brand back. They've created something called Watson X, and effectively it is an AI training studio for enterprises. So when enterprises and big businesses need to train their own versions of models, Watson X is supposed to help them do that more easily. CEO Arvind Krishna said, we allow an enterprise to use their own code to adapt the model to how they want to run their playbooks and their code. Then they can deploy it for themselves without any danger of their code leaking. As quick as we might be to write off a legacy competitor like IBM, I wouldn't do so in this case.
3:55First of all, I think it's very likely that enterprises with highly sensitive and proprietary data are going to want to train their own models. We already see OpenAI starting to talk about a chat GPT offering just for businesses that's private by default, but that next level of privacy and security is just running it on premise with your own uniquely trained models. So I think that there's going to be a market for that. Second, IBM is partnering with Hugging Face, one of the most dynamic players in the space, which is the default home for open source AI models. So there's something interesting there to watch.
4:24Finally, a buzzy little prediction that I'm sure will get lots of headlines. AI expert Ben Goetzel says that AI could replace 80 % of jobs in the next few years. He said this at a Web Summit conference, and he said that this was actually a good thing, that humans shouldn't be spending all their time on work that was irrelevant, when machines could just do it better. But even that optimistic view still has a really strong sticking point, which is what happens in the transition and how society is able to deal with so much disruption all at once. Neither Ben nor basically anyone that I've seen has a really good answer to that, but that's the state of the conversation.
4:59All right, guys, that's the AI Breakdown Brief. If you found this useful, please like this video or subscribe to the channel. And of course, you can also listen to this each day at the AI Breakdown podcast. I'll see you back here in a bit for the main AI breakdown. On today's AI Breakdown, we are talking about how to get auto GPT on your phone and what auto GPT is actually useful for about six weeks after it exploded onto the scene. About six weeks ago, people started talking about baby AGI and auto GPT. These were both tools that took the idea of ChatGPT, but added some really interesting features that seemed like they would create a whole new set of functionality.
5:41Now, you could tell just how interesting they were to developers because within days, basically, they were some of the most interacted with projects on GitHub. You had all the threaders on Twitter talking about all the use cases that had popped up within the first week. You had people like me on YouTube who were doing the same thing. But then within a couple weeks, people started to maybe get a little bit more disillusioned. They started to see what AutoGPT and Baby AGI couldn't really do. So what we're going to do today on this AI breakdown is we're going to talk about, one, a new tool that puts an AutoGPT-style experience on your iPhone, and two, we're going to do a bit of an update on what people are actually finding useful with AutoGPT, including one use case that I haven't seen really anyone else talking about.
6:23In order to get started, I think that there were three things about auto-GPT that people were really excited about relative to chat-GPT. The first was that it was connected to the internet. It didn't have a cutoff on when its information came from, which means it could be used for up-to-date research and other sort of queries that involve searching. Second was the idea that effectively it prompted itself. It didn't just respond to human input, but it actually, when given a task, created an additional subtask list to figure out how to get that thing done. The third thing that people were excited about was the idea that it would actually execute the tasks, including spinning up other AI agents to do so.
6:57Now, I think what we've found so far, in short, is that the first and the second have really come to fruition. Connection to the internet does give AutoGPT an entirely new set of use cases that ChatGPT currently isn't useful for. What's more, the fact that it prompts itself and creates its own task list has really interesting implications as well. Where I think for many, AutoGPT has fallen a little bit short is around the execution of tasks with other AI agents. You'll often see people complain that the tools that they're using are getting caught in loops or thinking that something has been executed when it really hasn't.
7:28Now, I will also note that part of the problem here isn't just with AutoGPT. It's with the implementations of this type of technology that people are using. Specifically, the folks who are using no-code implementations where they're just off the shelf and they're a UI that someone has prepared, obviously have a lot less control in terms of how they shape the experience of an auto GPT to actually do the things that they want it to do. Broadly speaking, and we'll see this throughout the rest of the video, we've seen people move from very generalized use cases to more specialized use cases, and they've been having more success as they've done so.
7:57But let's talk about iBabyAGI. Developer Nate Chan has been watching auto GPT since the very beginning and started tinkering almost immediately. And it didn't take long after baby AGI and auto GPT were released for people to start putting web interfaces on top of it. A few that came out pretty quickly and that we've demoed on this channel include God Mode, Agent GPT, and iOmni, which represented an even newer trend of focusing in on a specific use case, in this case, online research. But back to Baby AGI, what Nate Chan wanted to do was get this type of experience on an iPhone. Sure, it was great to have it in a web browser, but the way that so many of us interact with the internet is through our phones.
8:34One of the testers who had early access to iBaby AGI is Lauren Marie. On May 3rd, she wrote, For the past few days, I've been testing the brand new iBaby AGI app by Nathan Chan. I'm so impressed with what I've been able to do with it. She says the highlights include developed a simple interactive web page with a single prompt, some assembly required, conducted an SEO analysis and received SEO suggestions for my website, created a full travel itinerary for a trip to Italy with a budget of$3 ,000 USD, created a fitness plan based on personal preferences, developed a list of tools to automate sales prospecting, Made a newsletter outline with AI trends related to chat GPT-4 and autonomous agents.
9:10Wrote a Python script to send automated emails. This is using the 3.5 API, and if you look in the bottom right corner, you will see that these didn't cost me more than two cents each to run. So let's look at one of her examples. This is the detailed travel itinerary for a vacation to Italy. On her phone, she's typed objective, create a detailed travel itinerary for my upcoming trip to Italy. I will be on a two and a half week excursion visiting Florence, Verona, and Lake Cuomo. and then she put in some more information about what she wanted and her budget. iBaby AGI first created a task list and then it started executing the tasks one by one.
9:43It looked for affordable restaurants, it looked for affordable hotels, and it gave a set of options for each. Now what about the tools for automated sales prospecting? The objective here was very clear. Give me a list of tools for automated sales prospecting. The task list that iBaby AGI generated for itself included identify and extract relevant data from sales prospecting sources such as LinkedIn, company websites, and industry databases. Two, use natural language processing to analyze and categorize the extracted data based on criteria such as job title, company size, and industry. And three, use machine learning algorithms to predict which prospects are most likely to convert into customers based on historical data and patterns.
10:17The tools that it came back with a few minutes later included LeadIQ, ZoomInfo, Clearbit, Sales Navigator, HubSpot Sales, alongside a quick description of each. Now from there, it did a thing which you see these auto GPTs do quite often, which is kind of overcomplicate the task. So some of the additional tasks it created for itself include use machine learning algorithms to predict which prospects are most likely to convert it to customers based on historical data and patterns. Use a decision tree algorithm to identify the most effective outreach strategy for each potential lead based on their extracted data and score.
10:46Implement a chatbot to automate initial outreach to potential leads and gather additional information to improve their score, etc, etc. At the end of it all, the most valuable information was simply this list of tools that Lauren was then presumably able to follow up with and figure out which one she was most interested in on her own. Now, overall, Lauren says, my favorite things about iBaby AGI, quick and efficient, no looping. It never gets caught in a loop. It may provide the same or similar info repeatedly, though. Finishes objectives cleanly, detailed outputs, intelligently segments tasks into completed and remaining, tracks spend, easy copy and share feature to make outputs more useful.
11:20The tool is super user friendly and a lot of fun to play with. Now, of course, when it comes the AI tools, you have to try them yourselves. And so I downloaded iBaby AGI and my first impression definitely resonated with some of what Lauren said, which that it was an extremely easy user interface. It made it feel very fast to begin this process. All you had to do was input your open AI key and you were off to the races. The first thing I tried was a purposefully broad objective. I said, I want to create a newsletter that can get to 100 ,000 subscribers. I'm interested in lots of different topics.
11:52Ultimately, what iBaby AGI spit out was kind of exactly the sort of generic list that you might expect. You could talk about dad stuff, you could talk about technology, you could talk about finance. No real specification, and obviously that was more my fault than its fault. It shows I think the more abstract the objective is, the harder it is for these tools to do it. But then I narrowed things down, and one of my next inquiries was about whether it could help me come up with a top 10 list of guests to have on the AI breakdown. For this, I even gave it the criteria that I wanted them to be based on popularity and reach.
12:21For this one, it did much better. It said, added a new task, use a machine learning algorithm to rank the potential guests based on their popularity and reach, taking into account factors such as the size of their audience, engagement rates, and the number of media outlets they have been featured in. It then decided how it wanted to present the information to me, saying it will provide a report with the following information for each guest. Name, social media following, website traffic, media appearances, the number of times they have been featured in relevant media outlets. It also said that it was going to develop a scoring system that takes into account the factors identified in step one, as well as any additional relevant data, such as academic credentials or industry awards.
12:55Now, the list it came back with was pretty good. It roughly matched what you would expect if you asked an AI to find you the 10 most popular people in the space to interview. Now, of course, what it didn't take into account for was the difficulty of getting them on a show. For example, it has people like Elon Musk, but it also took the additional step of clustering them based on whether they were academics or whether they were industry leaders. And so overall, it did provide some interesting utility. Now, I also asked it to plan a last-minute date night for me and my wife in New York, and I gave it some specifications to help it out.
13:24I said we wanted to be in the Lower East Side, we wanted a hotel under a certain price, and we wanted restaurants within walking distance of that hotel. It came back with a totally reasonable plan on the basis of that, and so again, I think you're seeing here that specificity matters. Now, this idea of specificity and specialization seems to be something that other people are experiencing as well. When I went back to Agent GPT, which I haven't looked at for a couple weeks, I noticed that instead of just a blank box of do whatever you want, although it still has that, it also has a few different agents that it suggests.
13:54It has platformer GPT, write some code to make a platformer game. Travel GPT, for example, plan a detailed trip to Hawaii. Research GPT, create a comprehensive report of the Nike company. So these are clearly three different use cases for coding, for travel, and for research that agent GPT seems to think are primary use cases for this technology. The emergence of tools like AOMNI, which specifically focuses on online research, also suggests that what people are finding is that the more that you can tune these models to go after specific use cases, the more likely to produce good results they are.
14:26I think this was almost inevitably going to be the pattern here, where we went from very generalized use cases to actually honing in on the specific things that these tools could be most helpful for and designing new tooling around those use cases. What's more, I'm also seeing a lot more people start to figure out what the relationship between the auto and automation part of this should be versus the human part. Developer Nick Dobos, for example, had a long thread on April 28th that says GPT and me. A baby AGI slash auto GPT style agent that creates full human and AI symbiosis. The only AI agent that can actually accomplish things today because the task execution subagent is me.
15:04Become a human and AI agent cyborg. Nick then shows these detailed schematics, and basically what they come down to is that you use the Auto-GPT style tool to create the task list, to prioritize it, and then to say what needs to happen. Then, instead of that third step where the Auto-GPT just creates a new AI agent to do that task, the human becomes the execution agent. They return that result and then use that to enrich the Auto-GPT's information so that it can reprioritize and give the human agent the next task. Now in some ways this is all very simple, but what it is is trying to actually figure out the process by which these sort of auto GPT tools are really productivity enhancing without assuming that they're going to be able to do everything all on their own.
15:50Remember, these experiments are less than two months old, and so it doesn't surprise me that we're seeing both a move to specialization as well as a move to people figuring out just how autonomous auto GPT should really be. Now, the use case that I mentioned that I haven't really seen anyone talking about is really simple. It's brainstorming. One of the things that I've been underwhelmed with these tools around is their ability to go from an objective to a completed task. It involves a ton of abstraction, a ton of steps, and the fact that you're seeing objective specialization, as well as people like Nick experimenting with the human part of this, suggests that that's a difficulty for others as well.
16:24What I found auto GPTs to be amazing for, however, is a partner in how to think about accomplishing different objectives. In other words, one of the most valuable parts of letting an auto GPT like iBabyAGI go off to try to finish an objective is to see how it actually approaches it. It's not just the tasks being completed that's valuable. It's which tasks it thinks are important in the first place. especially as an entrepreneur or a content creator or anyone who's working in a small environment where they have to be dynamic and do a lot of different things and context switch. Having a brainstorming partner that can help think from zero to one when it comes to important tasks is incredibly valuable.
17:01Sure, of course, we want these technologies that can do everything for us at the drop of a hat or the snap of fingers, but helping outsource our process brain and make sure that our process is most efficient is actually really valuable as well. Now, one of my biggest questions coming up with AutoGPTs is to what extent ChatGPT with browsing fundamentally changes the need for them. The two plugins that OpenAI has been working on for ChatGPT are, of course, Code Interpreter, which we talked about in a previous video, and ChatGPT with browsing. As you would imagine, browsing gives ChatGPT access to the internet, which is one of those major use cases of AutoGPT.
17:38Now, it still doesn't mean it's necessarily designed to auto-prompt itself to figure out the tasks around an objective, but it's not impossible to me that what we'll really find is that a big part of what feels so amazing about auto-GPTs, at least right now, is the fact that they were connected and can go out and search the internet on our behalf. With GPT-4 with browsing rolling out more fully, I think we'll have much more of a chance to understand that in the weeks to come. All right, guys, that is it for the AI breakdown today. Go check out iBabyAGI. Nate Chan did a great job with it. If nothing else, you will have a ton of fun just experimenting and learning and seeing what it does.
18:11If this video was valuable, please like and subscribe to the channel. Go follow the podcast on Apple or Spotify, wherever you listen. That's the AI Breakdown. Come back tomorrow for another dose of the AI Breakdown Brief and the AI Breakdown. Until then, peace.
18:36You
From the publisher
A check-in on AutoGPT as well as the headline news:
Updates from the US copyright office
Pitchbook VC enthusiasm for AI
Palantir stock price pops after AI announcement
Google I/O Developer conference AI leaks
IBM relaunches AI division as WatsonX in partnership with HuggingFace
One researcher says 80% of jobs could be replaced by AI

