OpenAI vs. Open-source: After the Chaos, the New Deal

We discuss the impact of the recent events at OpenAI on the dynamic between closed and open source AI models.

We discuss the impact of the recent events at OpenAI on the dynamic between closed and open source AI models.

Recent Events at OpenAI

A few weeks back, Sam Altman, the CEO of OpenAI, was fired by his board amidst much chaos and confusion. He was reinstated a few days later, but the details and reasons behind the board's decision remain unclear.

Closed vs. Open Source AI Models

Firstly, let's define closed and open source AI models. Closed source, exemplified by OpenAI and Anthropic, involves publishing models and charging for access without disclosing model details, such as training data or techniques. Open source is more varied, ranging from freely downloadable model weights to varying degrees of openness in training code, datasets, and licenses.

Why Choose Closed or Open Source Models?

Closed source models, like GPT-4, are often market leaders in performance. They are user-friendly, requiring just an API key and payment to start. Open source models, however, offer greater transparency, control, and potentially, security and cost-effectiveness.

Impact of OpenAI's Leadership Crisis

The recent leadership turmoil at OpenAI raises concerns about the company's stability. Additionally, the reliability of OpenAI's API has been questionable, with multiple recent outages. These incidents highlight the risks associated with relying solely on closed source models.

Shifting from Closed to Open Source Models

As an engineering leader, you face a choice between a high-quality, easy-to-use, but potentially unreliable closed source product and a more transparent, controllable, but labor-intensive open source option. The ideal approach may involve starting with closed models for prototyping and gradually shifting towards open models for production, optimizing cost, performance, and reliability.

The Importance of Open Source AI

Yann LeCun's recent comments emphasize the need for AI to be open source, likening it to a common platform like the internet. This openness is crucial to prevent corporate or national monopolization of AI and to ensure public control and visibility into AI models.


While closed models are powerful and convenient, it's essential to support open source models for a more economical, transparent, and reliable AI ecosystem. Thank you for watching. Please like this video and subscribe to the channel. Bye-bye.

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