mayaskIn the world of AI, you’ve surely heard about what OpenAI and Google have been up to. And now, Meta’s Llama LLM (large language model) is emerging as a significant player, especially with its open-source nature. Meta recently made a big splash with the launch of its Llama 3 AI model, and it’s shaking up the field dramatically.
Contents:
– Llama 3 is truly remarkable
– It has a massive existing user base
– It’s completely free
– It’s open source, which is a huge advantage for developers
– It can be run locally, making it accessible to a wider audience
– And there’s more to come
The reasons for Llama 3’s success are numerous. It’s free to use, it has a vast user base, and, yes, it’s open source, to name just a few. Here’s why Llama 3 is taking the AI industry by storm and may shape its future for some time to come.
Llama 3 is Truly Good
We can argue endlessly about the practical usefulness of AIs like ChatGPT and Llama 3 in the real world – they’re not bad at teaching you board game rules, but the few benchmarks we have for their capabilities give Llama 3 a distinct edge. Some of the Llama 3 developers have been sharing tests comparing the latest models to some of the leading alternatives, and in many cases, Llama 3 comes out on top. These benchmarks cover areas such as mathematics, natural language processing, coding abilities, and general knowledge and understanding.
Don’t just take their word for it. You can test Llama 3 against itself and a range of other AI models in the AI Arena.
A Massive Existing User Base
When OpenAI launched ChatGPT, it had some early adopters but had to grow its user base organically. It did so incredibly quickly, registering tens of millions of users following the success of its GPT 3 and GPT 4 models. But Meta’s Llama 3 is already integrated into its Meta AI, which can be used across Facebook, Instagram, WhatsApp, Messenger, and on the web app versions of all these services. That’s not millions of existing users. That’s billions. All Meta has to do to gather more data on how Llama 3 is used or how to improve it for everyday users is to nudge these billions of users to give it a try. That’s a captive audience that few other tech companies can even come close to competing with.
It’s Entirely Free
If Meta CEO Mark Zuckerburg’s failed Horizons VR initiative taught us anything, it’s that Meta has no problem investing billions of dollars into projects that may not yield immediate results. But this lack of a need for immediate profitability is a significant strength for a company investing in such a cutting-edge field. Other AI developers may need to see a return on their investment relatively quickly, but Meta doesn’t have the same pressure. With its massive data center infrastructure and firm revenue streams from its various services, Meta can price Llama 3 at $0 for everyone. It can afford to burn through billions of dollars worth of computing power in the pursuit of further developing Llama 3 and future LLMs. This makes Llama 3 more accessible to its billions of users than any other top-tier AI.
It’s Open Source
When it comes to users, price matters; for developers, code transparency is crucial. Unlike proprietary platform AIs like ChatGPT and its various language models, Llama 3 is open source. This means developers can examine how it operates and make changes. They can build upon it and take the project in their own interesting directions. This encourages wider adoption as more developers will be able to incorporate the Llama 3 model into their own projects, and it leads to better code as more people can influence its development. This has the potential to make Llama 3 a de facto standard, ensuring its prominence in the foreseeable future.
It Can Run Locally
One of the major drawbacks of large language model AIs like Google’s Gemini, ChatGPT, or previous iterations of Meta’s Llama is that they require a significant amount of computing power – not just during training but also in operation. That’s why you have to pay for the privilege of using some more demanding AIs, and why the response can be slow when the service is busy. But Llama 3 can be run locally on consumer laptop hardware. It may require a bit of effort to set it up, and you’ll need a lot of memory to make it work effectively (the laptop used in the example below is the MacBook Pro M1 Max with 64GB of RAM memory), but it’s not a major obstacle.
Run Llama 3 Locally with Open-WebUI
This video is NOT sped up. The model downloaded from @ollama (llama3:instruct), running with @OpenWebUI, on a Macbook Pro M1 Max 64G.
You can run it right now on your own machine (Windows, Linux, Mac) with 1 click. https://t.co/sDpI4TEiwa pic.twitter.com/qe5PIv3hQm
— cocktail peanut (@cocktailpeanut) April 18, 2024
This is not the final version of Llama 3, however. It uses 70 billion parameters in its responses, but there are internal versions of Llama that utilize up to 400 billion parameters. Llama 3 is also not the first LLM to be run locally, but it is the most capable so far, and it suggests that we could see this type of AI running on smartphones, smartglasses, VR headsets, and other devices in the near future.
And It’s Only the Beginning
Llama 3 is amazing, but there’s still a lot it can’t do yet. It is currently entirely text-based, which means it’s not the multimodal AI we’ve seen with ChatGPT and similar services. It can’t process video, audio, or images. It can’t respond to vocal commands or speak back to you. It currently only works with the English language as well.
But it will soon be able to do all those things – and probably more. Llama 3 is a warning shot to many AI developers, signaling that the era of smaller startups stealing the limelight in AI development may be over. Without the kind of major financial, technological, and infrastructure backing of a company like Meta, directly competing may be extremely difficult indeed.
