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How Open is Generative AI? Part 2

Embarking on the second and last part of our ‘Generative AI Openness’ series, we earlier established a straightforward framework to gauge the openness of Large Language Models (LLMs) and utilized it to explore LLM development and the positioning of key players. We noticed a trend towards increasingly restricted LLM artifacts for OpenAI and Google, contrasted with Meta’s more open approach.

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How Open is Generative AI? Part 1

Welcome to this two-part series on Generative AI Openness, where we explore the history, current landscape, and potential future of open collaboration and proprietary control in the development of Language Language Models (LLMs). In this first part, we will delve into the importance of inspecting the openness of each component in the LLM training process, and how this can impact the potential limitations on the model use or reuse imposed by one or more of its components. In the second part of this series, we will explore the potential benefits and drawbacks of sharing Generative AIs openly for the collective advancement of society.

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My first open source contribution

Why you should give it a try too

Fight the imposter syndrome

I know contributing to open source projects is a daily task for many developers but I am sure a lot more still do not dare to take that step. They do not think that participating to an open source project is not for them. Most of the time this situation comes from the fact that they do not feel confident enough to participate. A bit of the impostor syndrome . It was my case…

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