In November 2022, OpenAI launched an AI chatbot that witnessed some remarkable success. Following the success of OpenAI’s popular AI chatbot, ChatGPT, many tech companies have entered the race to develop their large language models (LLMs).
The primary motive of these companies is clear: they want to overthrow the supremacy of OpenAI’s dominant LLM.
Meta has been lagging behind its rivals. In February 2023, when other competitors like Microsoft and Google released their AI chatbots, this sparked Meta to roll out their first.
Meta initially launched LLaMA (Large Language Model Meta AI) but it was restricted to researchers only. After about five months in July 2023, Meta released the next generation of LLaMA, called LLaMA 2, which shows considerable promise for both research and commercial usage.
TL;DR
- LLaMA 2 is Meta’s new open-source language model that looks to revolutionize the AI landscape.
- It’s useful for both individuals and professionals.
- LLaMA 2 uses two reward models that score the responses based on safety and helpfulness.
- The model creates safe and helpful content while discarding anything that seems harmful to users.
- It is free for everyone to use and build custom chatbots.
- LLaMA 2 has some of the greatest use cases in multilingual translation and customer support.
Introduction to LLaMA 2
Large Language Model Meta AI 2 (aka LLaMA 2) is a new and advanced contender in the LLM space. The model surpasses its predecessor, the LLaMA 1 version.
Having undergone significant improvements and innovations, LLaMA 2 is a much more powerful and valuable AI tool compared to LLaMA 1. The tool employs a language processing technology that’s similar to OpenAI’s GPT 3.5 and Google’s PaLM 2.
Meta designed this tool for individuals and professionals alike.
Major improvements
As a human, you need an AI tool that would generate responses just like you do. Keeping this in mind, you’ll come across just a few tools that come up with human-like results. Thanks to the team at Meta AI, LLaMA 2 is one of them.
LLaMA 2 has this impressive ability to produce helpful and non-toxic content for you. For this, it uses the Reinforcement Learning from Human Feedback (RLHF) model, the biggest improvement of LLaMA 2.
What an RLHF model does is, it scores various outputs generated by LLaMA 2 and chooses the one deemed most relevant, safe, and useful for you.
It’s trained with reward modeling
LLaMA 2 utilizes two separate reward models:
i) Helpfulness reward model – When you give it a prompt, the helpfulness reward model enables the LLaMA 2 to analyze the usefulness and relevance of the output. It has a scoring system for each generated output, showcasing how helpful it is against the user’s query.
ii) Safety reward model – This ensures you don’t get harmful content. It calculates the content safety based on things like hate speech or bias, etc.
To provide you with high-quality responses, the tool only selects outputs having high scores in terms of both helpfulness and safety. That means the tool discards the outputs with lower ratings in either area, helpfulness or safety. As a result, you enjoy an effective interaction with the tool.
LLaMA 2 is free for all
Yes, LLaMA 2 is freely available for everyone. Individuals and organizations can use it without any subscription or licensing fees.
Meta thinks that keeping the model open-source and letting users build customized products on top of it will only help the parent company catch up.
According to Ahmad Al-Dahle, the driving force behind Meta’s generative AI work declares it a game changer for the AI community. He says we’re offering people both closed- and open-source options, allowing them to tailor their approach in a manner that suits their needs and goals.
Let’s talk about its use cases
LLaMA 2 has the potential to be your go-to AI companion for a lot of daily and professional tasks. Let’s have a look at some of its important use cases.
Multilingual translation
Whether you’re an independent linguist or a corporate translation company, you can use LLaMA 2 to translate content between different languages. The tool is available for both of you.
Here’s to sharing my personal experience with you. I’m an AI practitioner who makes use of LLM models to provide software localization services to clients.
As far as my interaction with LLaMA 2 is concerned, I used it to translate some content from Spanish to Chinese. It disappointed me with its results.
Later, I came to know that the model only works best when you’re translating content between English and other languages. This is because a major proportion of the data used to train LLaMA 2 was in English. Is this insightful?
I hope this helps you if you choose to translate any materials with this model.
Customer support applications
Meta has prioritized safety and helpfulness when creating their robust large language model, LLaMA 2. This makes it highly reliable and an excellent choice for use in customer support services.
So you can use LLaMA 2 to provide chatbot services on your web platform or app. Due to being a fine-tuned language model, you can rest assured it won’t generate harmful responses for your users.
Final remarks
LLaMA 2 is undoubtedly a robust language model that has made its presence felt loud and clear. Its open-source design and powerful capabilities position it as a powerful tool to shape the future of the AI landscape.
However, it’s important to acknowledge that LLaMA 2 is a new entrant in a field where ChatGPT has already established its dominance. Therefore, it will be too early to pass a verdict on whether it will surpass ChatGPT and its counterparts.
What are your thoughts on the future trajectory of LLaMA 2?
