This new AI is powerful and uncensored… Let’s run it
TLDRThe video script introduces a new open-source AI model, Mixl 8X 7B, which offers an alternative to closed-source models like GPT-4 and Gemini. It emphasizes the importance of freedom in AI development and the potential of Mixl to outperform existing models without the constraints of censorship or political alignment. The video also discusses the possibility of fine-tuning AI models with custom data, using tools like Hugging Face's Auto Train and local deployment options, ultimately empowering users to create and utilize uncensored, powerful AI models.
Takeaways
- 🚀 The introduction of Mixl 8X 7B, an open-source alternative to proprietary AI models like GPT-4 and Gemini, offers a new hope for developers seeking freedom from censorship and alignment with specific political ideologies.
- 🌐 Despite the closed-source nature of major AI models like GPT-4 and Llama 2, the emergence of Mixl, with its Apache 2.0 license, allows for modification and commercial use with minimal restrictions.
- 🔍 The Mixl model, rumored to be based on a 'mixture of experts' architecture, shows promise by outperforming GPT 3.5 and Llama 2 on most benchmarks, although it is not yet at the level of GPT 4.
- 💡 The importance of open-source AI models is emphasized, as they enable developers to utilize their skills to modify and improve the models without restrictions.
- 🛠️ The video discusses the potential of uncensored AI models, such as the Mixl Dolphin model, which has been modified to remove alignment and bias, enhancing its coding abilities and versatility.
- 📚 The process of running large language models (LLMs) locally is simplified through tools like 'olama', which is written in Go and supports various open-source models including Mixl and Llama 2.
- 💻 Running these models locally requires significant computational resources, with the Mixl Dolphin model requiring about 40 GB of RAM on a machine with 64 GB.
- 🔧 The script explains how to fine-tune AI models with custom data using platforms like Hugging Face's Auto Train, which can handle both LLMs and image models like Stable Diffusion.
- 🌐 The cost of training AI models in the cloud is discussed, with the Mixl Dolphin model taking about $1,200 to train on four A1 100s for three days.
- 📝 The final step in customizing AI models involves uploading training data that may include prompts and responses, as well as esoteric content, to ensure the model's uncensored nature.
Q & A
What is the main concern about AI models like GPT-4 and Gemini?
-The main concern is that these AI models are not free in terms of freedom; they are censored and aligned with certain political ideologies, and they are closed source, which limits the ability of developers to modify and improve them.
What is the significance of the newly announced open-source model, Mixl 8X 7B?
-Mixl 8X 7B is significant because it offers an alternative to closed-source models by providing a true open-source license (Apache 2.0), allowing users to modify and monetize the model with minimal restrictions.
How does the Mixl model differ from Meta's LLaMA 2 model?
-While both Mixl and LLaMA 2 are open source, LLaMA 2 has additional caveats that protect Meta's interests. Mixl, on the other hand, offers more freedom as it is under the Apache 2.0 license, which allows for greater flexibility and fewer restrictions.
What is the potential issue with AI models being censored and aligned out of the box?
-Censored and aligned AI models may not be suitable for all applications, especially when trying to explore ideas or topics that may not align with the predefined restrictions. This can limit creativity and the potential for diverse uses of AI.
How can one run uncensored large language models on a local machine?
-One can run uncensored models like the Mixl Dolphin model on a local machine using tools such as olama, which simplifies the process of downloading and running open-source models locally.
What is the process for fine-tuning AI models with one's own data?
-Fine-tuning can be done using platforms like Hugging Face's Auto Train, which allows users to upload their own training data, select a base model, and then train the model accordingly.
What kind of hardware is required to run the Mixl Dolphin model?
-Running the Mixl Dolphin model requires a machine with a significant amount of RAM, as it was reported to use around 40 GB of RAM on a machine with 64 GB of RAM.
How long did it take to train the Mixl Dolphin model?
-The Mixl Dolphin model took approximately 3 days to train on four A1 100s.
What are some platforms where one can rent the necessary hardware to train AI models?
-Hugging Face, AWS Bedrock, and Google Vertex AI are examples of platforms where users can rent the required hardware to train AI models.
What should the training data format typically contain?
-The training data format should typically contain a prompt and a response. To make it uncensored, it should be designed to comply with any request, even if the request is unethical or immoral.
What is the ultimate goal of creating a custom and highly obedient AI model?
-The ultimate goal is to have an AI model that is tailored to the user's specific needs and preferences, without the limitations imposed by standard models, thus providing a more versatile and powerful tool for various applications.
Outlines
🚀 Introduction to Open Source AI Models
The paragraph discusses the limitations of popular AI models like GPT-4 and Gemini, highlighting their closed-source nature and alignment with certain political ideologies. It introduces an open-source alternative, Mixl 8X 7B, which offers the potential for customization and freedom from censorship. The narrative sets the stage for the introduction of Mixl, an AI model that can be combined with a dolphin's brain for versatile applications, emphasizing the importance of open-source AI in fostering innovation and challenging the status quo.
Mindmap
Keywords
💡Open Source
💡Censorship
💡Apache 2.0 License
💡Mixture of Experts Architecture
💡Unlabelling
💡Local Machine
💡Fine-tuning
💡Hugging Face
💡Cloud Computing
💡Training Data
💡Dolphin Mixol Uncensored
Highlights
Gro, Gemini, and other AI models are not free in terms of freedom, being censored and closed source.
A new open source model named mixl 8X 7B offers an alternative to the censored and closed source models.
Mixl 8X 7B can be combined with the brain of a dolphin to follow any command, potentially offering uncensored AI capabilities.
Open AI's CEO Sam Altman previously stated that it's nearly impossible for startups to compete with Open AI in training foundation models.
Google's Gemini and mistol's mixol are both new models, with the latter being open source and valued at $2 billion.
Mixl is based on a mixture of experts architecture, rumored to be the secret sauce behind GPT 4.
While not at GPT 4's level, mixl outperforms GPT 3.5 and llama 2 on most benchmarks.
Mixl's true open source license (Apache 2.0) allows for modification and commercial use with minimal restrictions.
Despite Meta's controversial past, the company has contributed significantly to making AI more open.
Both llama and mixl are censored and aligned out of the box, which may not be suitable for all applications.
It's possible to un-censor and re-train these models, as explained by Eric Hartford in a blog post.
The mix dolphin model improves coding abilities and is uncensored, achieved by filtering the data set.
Olama is an open source tool that simplifies the process of running open source models locally.
Hugging face's Auto Train facilitates the fine-tuning of models with a user-friendly interface.
Training models with custom data can result in highly obedient and personalized AI models.
The cost of training large models like mixl dolphin can be significant, but cloud services offer rental options.
The final step in creating a custom model is uploading training data and starting the training process.
By fine-tuning and using uncensored models, individuals can empower themselves in the fight against oppressive forces.