When a great innovation like “Llama 2” is on the horizon, there’s a slim chance that Meta won’t capitalize on it. This time, they came up with their own chatbot.
Llama 2, Meta’s very own open-source large language model (like GPT-3), is set to make waves in the artificial intelligence sphere.
The new AI is in a perfect position to pose a direct threat to ChatGPT, mainly because it’s free to use and makes way for more breakthroughs in artificial intelligence research. But Llama 2 has much more to offer. In this post, I unwrap Llama 2 for you.
Meta: Pioneering the Metaverse Revolution
Let me start by re-introducing the mastermind behind Llama 2, Meta Platforms Inc. Once upon a time, you might’ve known it as Facebook, but not anymore.
With a market capitalization of $772.33 billion, Meta is one of the leading tech companies in the market, specializing in social media and technology products. Most popular social media and messaging apps, including Facebook, Instagram, WhatsApp, Threads, and Messenger, come under its umbrella.
Meta’s prized project is the development of Metaverse, a collective virtual shared space combining physical, augmented, and virtual realities. This vision includes the development of VR and AR technologies, immersive experiences, and digital ecosystems that allow users to interact in new and immersive ways.
When the world got introduced to the Large Language model through OpenAI’s GPT models and Google’s PaLM 2, Meta saw an opportunity to present something of their own – to snatch the cake from their plates.
Llama 2 is an open-source large language model developed by Meta and Microsoft, designed for research and commercial purposes. Yeah, that sounds like an unusual alliance, but both companies have been trying to make their mark in artificial intelligence research, so why not join forces against common foes? The result is a powerful LLM that is free to use.
Since it’s available for free, Meta has become one of the biggest contributors to Open Innovation in AI. Although Llama 2 works similarly to other LLMs, such as GPT-3 and PaLM 2 work, with similar development ideas.
The platform empowers organizations and developers to make generative AI tools and experiences without restrictions.
While the details of how it’s different from its competitors on the technical side are still murky, it’s open and free to use, as opposed to the closed-source codes of others.
How Does Llama 2 Work?
Llama has been trained with 2 trillion “tokens” from publicly accessible sources, such as Wikipedia, Common Crawl, and publicly available books from Project Gutenberg, to create its neural network. Every token denotes a word or a semantic fragment that empowers the model to give meaning to different texts and predict the follow-on text.
The developers implemented several strategies while training the AI model, including reinforcement learning with human feedback (RLHF). This was done to encourage helpful responses from the system and generate more appropriate results.
But the best part is you can train the model to create brand stories through examples in your personal, professional, or brand’s style, voice, and personality. The model is just a base over which you build form, depending upon your needs. The chatbot of the model is also trained and fine-tuned with data, which makes it better at responding to prompts in the most natural manner.
System Requirements to Run Llama 2
To run the program, you would need a minimum of 7B model and at least 10GB VRAM, although 8 GB could work too.
Here are some prerequisites for running Llama 2 locally:
Python: Python 3.8 or higher is needed, while 3.11 is recommended
Git: Grit needs to be installed
To try any of the versions of Llama, your only option is to go to Hugging Face, the prime hub for open-source AI models. Through the platform, you can also try Llama 2 7B Chat. If you have the specifications that support its operation, you can request access to Llama’s next version by giving details about yourself to Meta.
How Does Llama 2 Compare with GPT and Bard?
Llama 2 is in the same league as GPT and Bard’s AI models. The researchers of the Llama published a research paper in which they expounded upon various aspects of the AI model, including how it compares to similar products based on some common benchmarks – TriviaQA reading comprehension dataset and multi-task language understanding.
The comparison was done with several open and closed source models, such as GPT-3.5, GPT-4, PaLM, and PaLM 2.
The conclusion was that the 70B versions of Llama are way better in terms of performance than other open-source LLMs. While it appears to be on par with the performance of GPT-3.5 and PaLM on most parameters, it doesn’t outperform GPT-4 or PaLM 2.
In practice, Llama 2 relies on imagination while producing prompt results. ChatGPT, on the other hand, can be more advanced and creative with its output, especially if you’re using its latest and paid version.
But that is where Llama has the advantage: it’s free to use and open source. Businesses can access and use the official APIs to fine-tune their models so they encourage unique responses.
Llama 2, by far, is not the best LLM out there. But what sets it apart is that it’s open source and available to anyone for free, unlike its closed-source competitors. The introduction of this AI tool has been a giant leap for open innovation; since Llama is so accessible, it makes it easier for companies to experiment and create AI-powered tools and applications they can control.
Anybody can access it, but the only limitation to the license is that companies with over 700 million monthly users would have to request special permission to operate Llama. This means big tech giants and direct competitors to Meta and Microsoft, such as Google, Amazon, and Apple, can forget about getting easy access. More power to smaller companies, then!