The Source Dilemma: Open Source vs. Closed Source AI Models

In this episode of Artificiality's January 2024 update, we dive into the heated debate between open source and closed source AI models, exploring the implications of this choice for businesses, developers, and the future of the AI landscape. 🔓🔐

Discover the key differences between proprietary, closed source models like those offered by OpenAI, Microsoft, and Google, and the growing ecosystem of open source alternatives, such as Meta's LLama and the models hosted on platforms like Hugging Face. Learn about the crucial factors to consider when choosing between these two approaches, including auditability, cost, model quality, security, and the risk of vendor lock-in. 💸🔍

Explore the potential for a "Linux moment" in the AI world, as open source models become increasingly robust and attractive, particularly for task-specific applications that require fine-tuning. Gain insights into how the ability to customize and contribute back to open source models can create valuable AI assets for businesses and drive innovation in the field. 🐧💡

Join Dave as he examines the evolving standards in the open source AI community and highlights the role of major tech players, such as Apple, in shaping the future of this debate. Discover how the adoption of open source tools by these influential companies can have far-reaching implications for enterprises developing AI applications. 🍎🌐

Don't miss this opportunity to stay informed about the critical decisions that will shape the AI landscape for the next two decades. Subscribe now to Artificiality for the latest insights, analysis, and expert opinions on the open source vs. closed source debate and its impact on your business and the wider AI community. 🔔👨‍💻

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