Meta Announces Planned Launch of Open-Source Llama 3
By Adam Pease
Meta Announces Planned Launch of Open-Source Llama 3
Meta, which has secured its footing in the generative AI space by releasing a variety of leading open-source models, has just announced its plans to release Llama 3, the latest iteration of its core open-source large language model (LLM).
Why Llama 3 Now?
Llama 3’s release announcement comes at a competitive time in the AI space, as large providers like OpenAI and Google compete to release cutting-edge proprietary models. It is also a time of fierce debate about AI’s potential to create misinformation or generate harmful stereotypes. Google recently faced criticism for the images generated by its new model Gemini, and Meta has taken the opportunity to position itself as a provider of more open, unrestricted AI models.
Specifically, Meta has stated that its new model will be more open-ended when answering questions, and less constrained by some of the guardrails that have frustrated some sections of the user base of proprietary LLMs in the past. With this move, Meta appeals to a segment of developers that want more open-box, unrestricted language models to build applications with.
The Future of Meta in Generative AI
Meta’s bet on open source may turn out to be an effective differentiator when it comes to the highly competitive generative AI space. While all the AI giants publish considerable amounts of open-source research, Meta has uniquely situated itself to build a developer community around its open-source research.
Meta is positioning itself differently from core AI providers like Microsoft, OpenAI, and Google. Instead, it aims to incorporate AI into a broad range of its products and services. By advancing open-source models, it may drive adoption on those platforms by enabling developers to build more open-ended applications.
Bottom Line
Llama 3’s release is an indication of Meta’s ongoing focus on open-source AI, and its attempt to cultivate a developer community that seeks more open and configurable LLMs.
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