What is the significance of the Open Source AI Definition released in 2024?

The Open Source Initiative released its first definition for open source AI, clarifying that weights and code must be available under an open-source license, and restrictive clauses are disallowed. However, the definition's stance on data availability is considered soft.

Why are open models becoming harder to train?

Access to training data is diminishing as content owners block web crawling in response to closed models. This trend disproportionately harms newcomers and benefits established players, leading to a scarcity of open training data.

Are open source AI models inherently more dangerous than closed models?

The speaker argues that the risks associated with open models are rooted in existing software and industry dangers, not unique to AI. Attempts to label open AI as an 'unknown alien technology' are seen as disingenuous lobbying tactics rather than genuine risk assessment.

What challenges exist in incentivizing the development of open models?

Building open models is risky and expensive, making it hard to secure investment. While challenges like the FRCHol's Arc Prize are valuable, there's a need for more research funding and long-term support beyond immediate commercial interests.

What are some of Mistral AI's key open-source model releases?

Mistral AI has released several notable models, including Mistral 7B, Mixtral Ax 7B, Mixtral Ax 22B, Codec, Pixol 12B, and Pixol Large. They also offer premium models like Mistral Large and Mixtral AB.

What can Mistral AI's Lashate chat interface do?

Lashate is a free chat interface with capabilities for image understanding and OCR (e.g., processing receipts), executing Python code in the browser, web search, and image generation.

Key Moments

Best of 2024: Open Models [LS LIVE! at NeurIPS 2024]

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Key Moments

TL;DR

Open models in 2024 showed significant progress, with more frontier-level performance and a clearer definition of 'open source' AI.

Key Insights

2024 saw a substantial leap in open model performance, nearing parity with closed models across various benchmarks.

The AI community established the first official Open Source AI definition, clarifying criteria for model openness.

Resource constraints, particularly in compute and data access, pose a significant challenge to the growth of open models.

The concept of 'fully open' models, releasing entire pipelines and checkpoints, is gaining traction and fostering collaboration.

Lobbying efforts and regulations pose potential risks to the open-source AI ecosystem, necessitating community engagement.

Mistral AI has released a wide array of open-source models with varying strengths, from small-scale deployment to multimodal capabilities.

SIGNIFICANT ADVANCEMENTS IN OPEN MODEL PERFORMANCE

The year 2024 marked a paradigm shift in the open-source AI landscape, witnessing the release of numerous models that rivaled the performance of proprietary, closed-source counterparts. Unlike 2023, which saw foundational releases like LLaMA 1 & 2 and Mistral, 2024 presented models from DeepSeek and Mistral that achieved frontier-level performance. This progress is consistently demonstrated across various benchmarks, significantly narrowing the performance gap that existed between open and closed models in the previous year.

THE IMPORTANCE AND EVOLUTION OF OPEN MODELS

The utility of open models extends beyond mere API accessibility. For researchers, they are indispensable, enabling deep dives into model behavior, evaluation, and mechanistic interpretability. For AI builders, local models offer advantages in retrieval tasks, specific application constraints, and overall stability, ensuring models do not change unexpectedly. The surrounding ecosystem, including serving and efficiency technologies, has also matured considerably, reflecting the core tenets of open source like collaboration and building upon existing innovations.

DEFINING OPEN SOURCE AI: THE OSI'S CONTRIBUTION

A landmark development in 2024 was the Open Source Initiative's (OSI) establishment of the first official definition for open-source AI. This definition requires fair availability of model weights, release of code under an open-source license, and prohibits restrictive clauses that block specific use cases. However, the definition's language regarding data accessibility was notably softened, focusing on providing sufficient details to replicate the data pipeline rather than ensuring direct data availability, a point of contention for some in the community.

RESOURCE CONSTRAINTS AND THE 'COMPUTE-RICH CLUB'

Despite advancements, 2024 highlighted increasing resource constraints, particularly concerning compute power. The barrier to entry for cutting-edge research and model development has risen, leading to a concentration of power among entities possessing tens of thousands of GPUs. While pre-training requires substantial resources (10,000+ GPUs), post-training and inference can be more accessible, though advanced research, especially in mechanistic interpretability, still demands significant computational investment.

THE RISE OF 'FULLY OPEN' MODELS AND ECOSYSTEM COLLABORATION

A significant trend in 2024 was the emergence of 'fully open' models. This approach involves releasing not just the model checkpoint but the entire pipeline, including training data, code, logs, and intermediate checkpoints. This comprehensive release strategy fosters deep collaboration, allowing researchers to build upon and adapt existing work. Examples include AI2's OMO, which contributed pre-training data for other projects, and Mistral AI's collaborative releases.

CHALLENGES TO OPEN DATA ACCESS AND REGULATORY RISKS

The open-source AI ecosystem faces significant headwinds. Access to training data is diminishing as websites increasingly block crawling, partly in response to commercial AI development. Furthermore, there is a risk of regulatory overreach and lobbying efforts aiming to portray open-source AI as inherently dangerous. These campaigns often misrepresent risks, drawing parallels to known software and industrial issues rather than highlighting genuinely novel threats, potentially stifling innovation and disproportionately benefiting closed-source entities.

MISTRAL AI'S EXPANSIVE MODEL PORTFOLIO

Mistral AI has been a prolific contributor to the open-source AI space in 2024. Their releases span a wide range, including the popular Mistral 7B and Mistral Large models, specialized embedding and code models, and multimodal models like Pixol 12B and Pixol Large. They also offer a suite of premium models with research licenses and enterprise options, alongside various Apache 2.0 licensed models. Their chat interface, Le Chat, showcases advanced capabilities like image understanding, OCR, code execution, and web search.

THE FUTURE OF OPEN MODELS: INCENTIVES AND SUSTAINABILITY

Ensuring the long-term sustainability of the open-source AI movement requires addressing the high cost and risk associated with developing these models. Initiatives like prizes and funding for research efforts are crucial. While commercial interests drive some open releases, fostering long-term support requires incentivizing purely open development. The community faces the challenge of moving beyond local optima, where individual entities optimize for market position, towards a global optimum where the open-source ecosystem as a whole thrives.

Mentioned in This Episode

●Software & Apps

●Companies

●Organizations

●Concepts

Common Questions

Open models, unlike closed models accessed via APIs, allow users to set up their own infrastructure and run models locally. This is beneficial for research, transparency, and applications where local control is necessary, such as retrieval tasks.

Topics

Ai-Ethics Ai Safety AI & Machine Learning Technology & Innovation Programming & Software Science & Mathematics Open-source AI Language Models Model Training Multimodal AI Developer Tools Compute Resources

Mentioned in this video

Companies

Mistral AI

Mentioned as a producer of open models in 2023 and a key player in the current open model landscape. The company's history and various model releases are detailed.

DeepSeek

Mentioned as a provider of frontier-level performance models in 2024. Also cited as needing a minimum of 50,000 GPUs for state-of-the-art pre-training.

Snowflake

One of the platforms where Mistral AI models can be accessed.

IBM

One of the major cloud platforms where Mistral AI models are available for use.

OpenAI

Mentioned as a provider of closed models like GPT, influencing content owners to block crawling. The scale of their training budget is implicitly referenced when discussing compute requirements.

NVIDIA

Collaborated with Mistral AI to open-source the Mixtral 8x22B model and is implicitly a major player in the GPU compute landscape.

Concepts

Common Crawl

A publicly available scrape of a subsite of the internet used for training language models. A study analyzing its snapshots revealed diminishing accessibility to web content.

Math

Mistral AI has a model named 'Math' that is designed to work well with mathematical problems.

Software & Apps

Google Cloud

One of the major cloud platforms where Mistral AI models are available for use.

Mixtral 8x22B

A powerful open-source model released by Mistral AI in April/May 2024.

Mixtral 3B

A small model from Mistral AI suitable for edge devices.

chat.mistral.ai

The URL for accessing Mistral AI's free chat interface, Lashate.

MPT

Listed as one of the key open models released in 2023.

ALMO

The speaker's institute (AI2) iterates on ALMO, benefiting from open source data and using outputs from other models for its preference model. ALMO is also mentioned as a predecessor to ALMO 2 and a base for recipes like Tulu.

Mixtral AB

A Mistral AI model that offers stronger performance than Mixtral 7B and is available for research and enterprise use under a special license.

Mixtral 7B

Mistral AI's first popular open-source model, released in September 2023. It is recommended for edge devices or as a replacement for older models.

Codec

A code model from Mistral AI, capable of handling 80+ languages.

Lashate

Mistral AI's new chat interface, free to use, offering capabilities like image understanding, OCR, web search, and image generation. It is also available via API.

AWS

One of the major cloud platforms where Mistral AI models are available for use.

Mixtral

An architecture used for models like Mixtral Ax 7B and discussed in relation to multimodal models.

Pixol Large

A frontier-class multimodal model from Mistral AI, capable of understanding both images and text.

Mamba

Mistral AI has a research model named 'Codec from Mamba' built on the Mamba architecture.

Llama

Mentioned as a significant open model released in 2023, alongside Llama 2. Llama's license is noted as not meeting the open source definition due to specific use case restrictions.

Llama 3

Highlighted as a model released in 2024 that reaches frontier-level performance, indicating a narrowing gap with closed models.

Pixol 12B

A multimodal open-source model from Mistral AI that excels at both image and text understanding.

Products

Falcon

Mentioned as one of the key open models released in 2023.

Organizations

Open Source Initiative

The organization that released the first open source AI definition in 2024. Discussions with OSI about licenses and data language are mentioned.

Legislation & Policy

California Senate Bill 1047

Referred to as a piece of legislation that the open source community narrowly avoided negative impacts from, suggesting it was potentially restrictive towards open AI development.

Locations

France

The country where Mistral AI was founded.