I DUMPED ChatGPT for This AI NEW Model (It’s So MUCH Better)
TLDRThe video presents a comparison between Chad GPT and a new AI model, CL 3.5, which the creator finds superior for coding tasks. The creator highlights CL 3.5's ability to generate executable code snippets and artifacts, enhancing the user experience. The video also showcases a proof-of-concept app built with Flutter Flow, utilizing CL 3.5 as a backend for real-time chat interactions, demonstrating its practical applications in no-code app development.
Takeaways
- 😀 The speaker has transitioned from using Chad GPT to a new LLM for better results in specific use cases.
- 🔧 The new LLM offers improved features for programming tasks compared to Chad GPT.
- 📈 The new model claims to outperform Chad GPT 4 in various metrics as shown in a comparison table.
- 🤖 The model is particularly praised for its effectiveness in writing code and generating snippets.
- 🔗 The speaker demonstrates the model's capabilities by showing a proof of concept app built with Flutter Flow.
- 💻 The model provides a front-end chat interface as well as a back-end API for more technical interactions.
- 🛠️ The front-end experience includes a unique feature called 'artifacts' that show real-time code execution previews.
- 🔑 The back-end interface allows for generating custom code for applications like Flutter Flow through API keys.
- 📝 The model can generate custom widgets, functions, and actions using template variables in the back-end.
- 📲 A chat client example is showcased, demonstrating the model's ability to maintain context in a conversation.
- 🌐 The speaker encourages checking out the new model, joining the Patreon community for access to apps and resources.
Q & A
What issue prompted the user to switch from Chat GPT to another language model?
-The user felt underwhelmed with Chat GPT, particularly with version 4, as it was too verbose and required very specific instructions to provide small code snippets, which was not ideal for the user's specific use cases.
What is the name of the language model the user switched to, and what are its advantages over Chat GPT according to the video?
-The user switched to an LLM called 'entropic', which was released around the time of CLA 3.5 Sonet. It is claimed to be better than Chat GPT 4 in various metrics, such as providing more concise responses and better code generation for programming tasks.
What is the main feature of the new LLM that allows users to see the execution of code snippets?
-The new LLM has a feature called 'artifacts', which allows users to see a preview of what the code looks like when executed, providing immediate visual feedback without needing to run the code on their own machine.
How does the user describe the experience of using the new LLM for Flutter development?
-The user attempted to create a Flutter animation using the new LLM but found that while the code was generated, there was no way to preview or execute it as an artifact, suggesting a potential limitation of the model with Flutter support at the time of the video.
What is the process for generating custom widgets, functions, or actions with the new LLM?
-The user can create a prompt template with variables in the LLM's workbench, set the variables to define the desired custom widget, function, or action, and then execute the prompt to generate the code.
How does the user integrate the new LLM into their Flutter Flow apps?
-The user interfaces with the LLM via its API keys and uses the generated code snippets directly in Flutter Flow, allowing for the creation of custom widgets, functions, and actions within the no-code app builder.
What is the significance of the 'artifact' feature in the context of the new LLM?
-The 'artifact' feature allows the LLM to not only generate code but also to execute it and show the results in real-time, providing a powerful tool for developers to immediately see the output of their code without additional setup.
How does the user demonstrate the new LLM's capabilities in the video?
-The user demonstrates by showing conversations with the LLM where it creates various code snippets and artifacts, such as an 8-bit style SVG image of a crab, an animation of multiple red crabs, and a JavaScript clock animation.
What is the role of the Patreon community in accessing the apps and resources discussed in the video?
-The Patreon community provides members with access to all the apps and resources discussed in the video, including the ability to view, clone, or use them in their projects, as well as additional support and content.
What is the user's final recommendation for those interested in the new LLM and its capabilities?
-The user recommends checking out the new LLM, cloning the provided app, and joining the Patreon community to gain access to the app, additional resources, and support from a community of like-minded individuals.
Outlines
🤖 Transition from Chad GPT to a New LLM
The speaker discusses their experience with Chad GPT since its inception and the issues they've encountered recently, such as verbosity and lack of precision in responses. They transitioned to another language model (LLM) that better fits their needs and promises to introduce its features and demonstrate a proof-of-concept app built with Flutter, leveraging the new LLM. The speaker also mentions their Patreon community as a resource for apps and further information.
🔍 Exploring Features of the New LLM
The speaker highlights the advanced features of the new LLM, such as the ability to create artifacts that allow users to see code execution in real-time. They demonstrate this by showing how the model created an 8-bit style SVG image of a crab and an animation of multiple red crabs, as well as a JavaScript clock animation. The model's capacity to update artifacts with new code on-the-fly is emphasized, showcasing its utility for programming tasks.
🛠️ Backend Experience with the New LLM
The speaker explores the backend capabilities of the new LLM, focusing on its programmatic interface. They discuss the process of obtaining API keys and using the model to generate custom code snippets for Flutter Flow apps. The speaker illustrates how to create custom widgets, functions, and actions by setting variables and running prompts, emphasizing the model's flexibility and ease of use for developers.
📲 Building a Flutter Flow App with the New LLM
The speaker describes the process of creating a custom widget in Flutter Flow using the new LLM's backend capabilities. They demonstrate generating a list of random food items and adding functionality for an action to be executed when a list item is clicked, showing the LLM's ability to integrate seamlessly with no-code platforms. The ease of modifying and compiling the widget into a functioning app is highlighted.
🌐 Creating a Chat Client with the New LLM
The speaker presents a proof-of-concept chat client app built with Flutter Flow that uses the new LLM as its backend. They showcase the app's functionality, including its ability to maintain context in a conversation, answer questions about France, and handle follow-up queries without needing repetitive context. The simplicity of the app's integration with the LLM's API is discussed, along with the potential for customizing the app's UI for different devices.
🎉 Conclusion and Invitation to Patreon
In conclusion, the speaker expresses satisfaction with the new LLM for its coding capabilities and unique features not found in Chad GPT. They invite viewers to join their Patreon community to access the chat client app, other apps, and additional content such as Q&As and masterclasses. The importance of community support for the channel and the speaker's work is emphasized, encouraging viewers to become members for mutual benefit.
Mindmap
Keywords
💡Chat GPT
💡LLM (Large Language Model)
💡Entropic
💡Artifact
💡Flutter
💡Code Snippet
💡API Key
💡Custom Widget
💡Patreon Community
💡No-Code
Highlights
Switched from Chad GPT to a new LLM for better results and specific use cases.
Introduction of features not available in Chad GPT.
Building a proof of concept app using Flutter Flow with the new LLM backend.
Issues with Chad GPT 4's verbosity and lack of concise responses.
Entropic's new model claims superiority over Chad GPT 4 in various metrics.
Positive community reception for the new model in programming tasks.
Features of the new model including an interactive frontend chat interface.
Artifact generation allows users to see code execution in real-time.
Demonstration of creating an 8-bit style SVG craft through the model.
Creating and updating animations with the new model's code execution feature.
Ability to modify and preview code changes instantly within the model's interface.
Backend access for technical interaction and API key generation.
Custom widget generation using the new model for Flutter Flow apps.
Creating custom functions and actions dynamically with the model's prompts.
Incorporating the new model into a Flutter Flow chat client as a backend.
Building a responsive chat interface that retains conversation context.
Community support and Patreon involvement for accessing apps and additional content.
Invitation to join the Patreon community for further app development and support.