GPT 4 Level Open Source in 2024..(Llama 3 Leaks and Mistral 2.0)

The transcript discusses the rapid progress of open-source AI and the potential for a GPT 4 level model to be released in 2024. It highlights the achievements of Mistral AI, a European startup specializing in efficient AI models, which plans to release an open-source model that could compete with GPT 4. The company's focus on ethical AI practices and community engagement positions it as an alternative to larger entities like Open AI. The script also touches on the benchmarks where Mistral's models excel, the cost-effectiveness of their models, and the potential for smaller, more efficient models to disrupt the industry. Additionally, it mentions the development of Llama 3 by Meta, which aims to match GPT 4's performance while remaining open-source, and the challenges faced by open-source models in competing with well-funded, proprietary models.

Takeaways

• 🚀 Open-source AI is advancing rapidly and may reach the level of GPT-4 by 2024, with various companies making significant announcements and contributions.
• 🔍 Sam Altman, CEO of OpenAI, has stated that catching up to GPT-4 is challenging, but developers are tasked with trying, indicating the ongoing push for progress.
• 📚 Open-source models like Llama, released by Meta's AI, are gaining popularity, with Mistral being a standout model that is set to release an open-source GPT-4 level model in 2024.
• 🤖 Mistral AI is a European AI startup focusing on compute-efficient, powerful, and trustworthy AI models, positioning itself as an alternative to larger AI companies with a focus on ethical practices.
• 📈 Mistral's model Mixr is reported to be significantly faster than comparable models, achieving results on par with Llama's 27 billion parameters, showcasing the company's efficiency.
• 🏆 Mistral's models have been performing well on benchmarks like the Arena ELO, indicating their competitiveness with larger models from established companies.
• 💰 Mistral AI recently raised €385 million, which will be used for training models, acquiring more GPUs, and covering server costs, highlighting its potential to disrupt the industry.
• 📉 The cost-effectiveness of Mistral's models, such as their medium model nearly matching GPT-4's performance at a fraction of the cost, could disrupt the market if GPT-4's costs do not decrease.
• 🧠 Mistral's team, despite being small at 22 employees, consists of experienced AI engineers and researchers capable of significant industry disruption.
• ⚖️ The debate on whether open-source models can surpass GPT-4 is ongoing, with some arguing that factors like talent, data, team structure, and infrastructure give companies like OpenAI an advantage.
• 🌐 The potential for open-source models like Llama 3 to compete with or surpass GPT-4's capabilities is a significant development that could reshape the AI landscape.

Q & A

What is the significance of open-source AI reaching the level of GPT 4 in 2024?

The significance is that it could democratize access to advanced AI technology, promote ethical practices, and challenge the dominance of larger AI companies by offering transparent, efficient, and powerful models and services.

Who is Sam Altman, and why is his statement about catching up to GPT 4 relevant?

Sam Altman is the CEO of OpenAI. His statement is relevant because it reflects the sentiment that while it may be challenging to match GPT 4's capabilities, it is the developers' job to continuously strive to do so, indicating the ongoing competition in the AI field.

What is Mistral AI, and what has its CEO, Arthur Mench, announced?

Mistral AI is a European AI startup specializing in compute-efficient, powerful, and useful AI models. Arthur Mench announced that Mistral will release an open-source GPT 4 level model in 2024.

How does Mistral AI's business model differ from traditional open-source models?

Mistral AI provides a highly permissive license for their models while maintaining private development and funding. Their models are available for free download and use, but the datasets and weights are private, offering transparent access to model weights for customization.

What is the significance of Mistral AI's team size and their achievements in the AI space?

Mistral AI's team consists of only 22 employees, which is small compared to other AI companies. Despite their size, they have made significant contributions to the AI space, indicating a high level of efficiency and expertise within the team.

How does the Arena ELO benchmark work, and what does it signify for AI models?

The Arena ELO benchmark involves users receiving two responses to a query and rating which one is better. The AI system with the better-rated response increases its ELO score. It signifies the real-world performance and user preference for AI models.

What is the role of Mistral's Mixr model in the company's success?

Mixr is a notable model from Mistral AI that is reported to be six times faster than comparable models while matching or outperforming models like Llama with 27 billion parameters. It supports multiple languages and can handle long sequences, contributing to Mistral's reputation for efficient and powerful AI models.

How does the cost-effectiveness of Mistral's models impact the AI industry?

If Mistral's models can match or exceed the performance of models like GPT 4 at a fraction of the cost, it could disrupt the industry by offering a more affordable and scalable alternative, potentially challenging the dominance of more expensive models.

What is the potential impact of GPT 4 level AI being available on a laptop?

The availability of GPT 4 level AI on a laptop could significantly increase the accessibility and application of advanced AI technology, enabling more users and industries to leverage powerful AI without the need for extensive infrastructure.

What are the challenges that open-source AI models face in competing with proprietary models like GPT 4?

Challenges include recruiting top talent, access to massive proprietary datasets, centralized team structures, the need to develop not just a model but a product with effective distribution, and the ability to iterate and improve at a pace that matches or exceeds proprietary models.

What is the significance of the rumored Llama 3 model and its potential to compete with GPT 4?

If Llama 3 can match GPT 4's performance while remaining freely available, it could offer a powerful open-source alternative, breaking the dominance of proprietary models and providing advanced AI capabilities to a wider audience.

Outlines

00:00

🚀 The Rise of Open Source AI to Rival GPT-4 in 2024

The paragraph discusses the rapid progress of open source AI, with a focus on Mistral AI's announcement to release an open-source model at the level of GPT-4 in 2024. It highlights Mistral's commitment to ethical AI practices and their efficient, powerful models. The company's small team of 22 employees, with experience from Meta and Google's DeepMind, is noted for its significant impact on the AI industry. Mistral's Mixr model is mentioned for its speed and performance, and the paragraph concludes by emphasizing Mistral's potential to disrupt the industry with its transparent and efficient approach.

05:01

📊 Mistral's ELO Leaderboard Success and Cost-Effectiveness

This paragraph details Mistral's success on the ELO leaderboard, where their medium model ranks fourth, surpassing other notable models. The text emphasizes the company's cost-effectiveness, with Mistral's medium model nearly matching GPT-4's performance at a fraction of the cost. It discusses the limitations of GPT-4's usage due to rate limits and the need for cost reduction for scalable applications. The paragraph also mentions a video clip translated with Mistral's technology, showcasing the company's rapid development in the AI space.

10:02

🧠 Mixr's Innovative Architecture and Mistral's Benchmarks

The paragraph explains the innovative architecture of Mistral's Mixr model, which functions like a team of specialists, each handling specific types of problems. It discusses the model's efficiency, multilingual capabilities, and suitability for quick thinking tasks. The text also draws a parallel between Mixr's architecture and the rumored structure of GPT-4, suggesting that other companies may adopt similar strategies. The paragraph concludes by noting the importance of product distribution and user-friendliness in addition to technical performance.

15:02

🤖 Open Source Models vs. GPT-4: A Critical Perspective

This paragraph presents a counterargument to the notion that open source models will surpass GPT-4 in the near future. It outlines several advantages that GPT-4 and companies like Open AI have, including talent, data, team structure, product focus, and infrastructure. The text acknowledges the challenges open source models face in competing with GPT-4, despite potential benchmark victories, and stresses the importance of product distribution and adoption.

20:05

🌟 Llama Models' Potential to Compete with GPT-4

The final paragraph discusses the potential of Meta's Llama models, particularly Llama 3, which is rumored to compete with GPT-4 while remaining freely available. It mentions the challenges of progressing from Llama 2 to Llama 3 and the possibility that open source teams are moving towards a 'mixture of experts' architecture. The paragraph also highlights Meta's goal to establish Llama models as an enabling technology in the LM market, akin to Google's strategy with Android in the mobile market.

Keywords

💡Open Source AI

Open Source AI refers to artificial intelligence systems whose design is publicly accessible, allowing anyone to view, modify, and distribute the design as they see fit. In the context of the video, it discusses the imminent release of AI models that rival the capabilities of GPT-4, which is significant as it could democratize access to advanced AI technology.

💡GPT-4

GPT-4 stands for 'Generative Pre-trained Transformer 4', which is a hypothetical next iteration of the language model developed by OpenAI. It represents a high watermark in AI capabilities, and the script discusses the race among various companies to develop models that can match or exceed its performance.

💡Mistral AI

Mistral AI is a startup company mentioned in the script that specializes in creating compute-efficient, powerful, and useful AI models. They are known for their research orientation and commitment to ethical AI practices. The company is highlighted for its plans to release an open-source model that could compete with GPT-4 in 2024.

💡Llama

Llama refers to a family of large language models released by Meta AI that are open source. The script discusses the potential of Llama 3 to compete with GPT-4 while remaining freely available, which would be a significant development in the open-source AI community.

💡Mixture of Experts

A 'Mixture of Experts' is an AI architecture where different parts of a model are specialized in handling specific types of tasks, similar to a team of specialists. The script suggests that GPT-4 may utilize this architecture, and other companies might adopt similar strategies to enhance their models.

💡Arena Elo

Arena Elo is a benchmark used to evaluate AI models based on user interactions and preference. It is mentioned in the script as a place where Mistral's model has been performing well, indicating its high quality in terms of user-rated performance.

💡Apache 2.0 License

The Apache 2.0 License is a permissive free software license that allows users to use the software for any purpose, to distribute it, to modify it, and to distribute modified versions of the software under the terms of the license. Mistral AI provides access to its models under this license, which is significant for the open-source community.

💡Ethical AI Practices

Ethical AI practices involve the development and use of AI systems in a manner that is responsible, transparent, and fair. Mistral AI is highlighted in the script for its focus on ethical AI, which is crucial as AI technology becomes more integrated into society.

💡Cost-effectiveness

Cost-effectiveness in the context of the script refers to the ability of AI models like Mistral's to provide high performance at a fraction of the cost compared to models like GPT-4. This is a critical factor for widespread adoption and use of AI technology.

💡Product Focus

Product focus implies that the development of an AI model is not just about technical superiority but also about creating a user-friendly and accessible product. The script discusses how companies like OpenAI focus on product development, which can contribute to broader adoption and success in the market.

💡Infrastructure

Infrastructure in the AI context refers to the computational resources, such as servers and GPU clusters, that are necessary for training and deploying AI models. The script mentions that public cloud infrastructure may not be as efficient as private setups like those of Google's DeepMind, affecting the speed at which open-source teams can iterate and improve their models.

Highlights

Open source AI is approaching the level of GPT 4, with potential availability in 2024.

Sam Altman stated that catching up to GPT 4 is challenging, but developers should still strive to do so.

Mistral AI, a European alternative to larger AI companies, plans to release an open-source model at the level of GPT 4 in 2024.

Mistral AI is known for compute-efficient, powerful, and useful AI models with a focus on ethical practices.

Mistral's model Mixr is reported to be six times faster than comparable models with 27 billion parameters.

Mistral's business model involves a highly permissive license for their models while maintaining private development and funding.

Mistral's team consists of only 22 employees, including co-founder and CEO Arthur Mench, with experience at Meta and Google's DeepMind.

Mistral's model has been exceeding benchmarks, ranking fourth in the Arena ELO leaderboard.

Mistral's Mixr model is extraordinarily smaller than its competition, indicating high efficiency.

Mistral has raised €385 million in funding, which will be used for training models and covering server costs.

Mistral's cost-effectiveness could disrupt the industry, especially considering the rate limits on GPT 4 usage.

GPT 4's architecture is rumored to be a mixture of experts, similar to what Mistral has been using in its models.

Meta's Llama models aim to break OpenAI's dominance in the LLM market, with Llama 3 expected to compete with GPT 4.

Llama 3 is planned to be freely available under the Llama license, potentially offering an open-source alternative to GPT 4.

The transition from Llama 2 to Llama 3 may be more complex and time-consuming due to architectural changes.

Despite the challenges, open-source AI models like Mistral and Llama are making significant strides in the AI industry.