Meta just released its latest version of Llama, this version is 3.2. It is an extension of 3.1.
We got some valuable insight into LeoAi on the most recent AMA. The use cases are expanding. With LeoAI, people will be able to pull data from the Hive blockchain. Everything that touches the database is fed into LeoAI.
This differs from the LLM, in this case Llama. Meta trains its model on allthe data is accumulates. It is doubtful it is scraping the blockchain. More likely, it pulls what is indexed, i.e. blog posts. This means Threads are not in that database.
With LeoAI, however, this is fed directly into the model. We see it constantly being updated, in real time. This is a big advantage for our purposes here.
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Llama3.2 Released
One of the advantages of using Llama is the fact it is open source, This means that anything that is built around that ecosystem could be incorporated into LeoAI. What we are looking at is the potential for a massively growing platform in terms of the features.
When we start to see AI agents emerge, this could see a flurry of activity. If developers are looking at open source solutions, we could see a great deal of innovation in this sector.
For nOWowwe simply will have to watch the advancements that Meta is making.
From their blog, we get this::
We just released our new Llama 3.2 models. Llama 3.2 is our first major vision model, which means it understands both images and text. To add image support to Llama, we trained a set of adapter weights that integrate with the existing 8B and 70B parameter text-only models to create 11B and 90B parameter models that understand images too. And we continue to improve intelligence—especially on reasoning—making these the most advanced models we’ve released to date.
We’re also releasing super-small 1B and 3B parameter models that are optimized to run on devices, like a smartphone or, eventually, a pair of glasses.
We believe open source AI is the right path forward. It’s more cost-effective, customizable, trustworthy, and arguably performant than the alternative. And we’ll continue to drive Llama forward responsibly with continuous improvements and new capabilities. Learn more about Llama 3.2.
There are two things that stand out here:
The first is the fact that Meta released the smaller parameter model for use on edge devices such as a smartphone. This is important to push the capabilities further out.
Another factor is the ability to train the model on images. This is going to be something that LEO can utilize at some point in the future. We know there are thousands of images on the server that Leo set up.
In the future, anything that is uploaded to Leo like this will be utilized for training.
Growing Features
This is some fast moving stuff.
In the past, I discussed the idea of adding more to LeoAI.
My view is that we require:
- text generation
-i mage generation - video generation
We can now add voice conversation to the list. ChatGPT is moving in this direction as are other models. We can presume Meta will get into this game also.
Regardless of that, there are open source models that can be incorporated. The ultimate goal is to set up personal AI assistants. That means we have the ability to train our own assistant as we see fit.
Expanding Revenue Options
Right now, the plan is to incorporate LeoAI into Premium. That is 10 HBD per month.
By going with advanced features, we can add another layer. This means the potential of have a 15 or 20 HBD plan, where even more AI tools are available.
This is a great way to structure a revenue plan.
AI is going to be a hotbed of activity. We are likely to see even more abilities in 2 years. For this reason, we are looking at a platform that can keep expanding with industry trends.
Keep an eye on what Meta is doing regarding Llama. This feeds directly into LeoAI.