Meta – the parent company of Facebook and Instagram – is moving ahead in the AI sector and challenging the controversial ChatGPT. The company released LLaMA (Large Language Model Meta AI), which Meta describes as a “state-of-the-art foundational large language model” designed to help researchers advance their work in this subfield of AI.
Smaller, more performant models such as LLaMA, said Meta, enable others in the research community who don’t have access to large amounts of infrastructure to study these models, further democratizing access in this important, fast-changing field.
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ChatGPT (Generative Pre-trained Transformer) is a chatbot that was launched by OpenAI in November 2022. Chatbot.com explains that a chatbot is software that simulates human-like conversations with users via chat. Its key task is to answer user questions with instant messages. OpenAI is an artificial intelligence (AI) research laboratory run by the for-profit corporation OpenAI LP and its parent company, the non-profit OpenAI Inc.
Meta said in a blog post, “We believe that the entire AI community — academic researchers, civil society, policymakers, and industry — must work together to develop clear guidelines around responsible AI in general and responsible large language models in particular. We look forward to seeing what the community can learn — and eventually build — using LLaMA.”
But ChatGPT is already causing a great deal of controversy, as are all forms of SI that offer automated services that can do away with people. Students are using this tech to write their term papers for them. And publications may start to use it to write stories for them. Advertisers could also use this new tech to write their ads.
There are also concerns about how this new tech could make it easier for hackers to gain access to private systems.
Addressing these concerns, in part, Meta said, “There is still more research that needs to be done to address the risks of bias, toxic comments, and hallucinations in large language models.”
Meta also acknowledged that, like other models, “LLaMA shares these challenges.” But went on to state that “As a foundation model, LLaMA is designed to be versatile and can be applied to many different use cases, versus a fine-tuned model that is designed for a specific task.”
So, Meta says that by sharing the code for LLaMA, other researchers can more easily test new approaches to limiting or eliminating these problems in large language models. Meta also pledged to provide in the paper a set of evaluations on benchmarks evaluating model biases and toxicity to show the model’s limitations and to support further research in this crucial area.