What are Large Action Models?
Large Action Models (LAMs) are the latest development in the world of Artificial Intelligence. LAMs use agents to perform actions. The agents are software entities capable of independently executing tasks, moving beyond merely responding to human queries and actively contributing to the achievement of specific goals. LAMs integrate the linguistic proficiency of LLMs with the ability to autonomously perform tasks and make decisions, marking a significant shift.
The architecture of Large Action Models is structured based on the simulation of applications and human actions they are intended to replicate. Unlike a mere textual representation, LAMs can effectively simulate the composition of diverse applications and the corresponding human actions performed on them without the need for a temporary demonstration. This capability is facilitated by advancements in neuro-symbolic programming and pattern recognition.
An AI model can provide you with a detailed process of how you can order food online, but it can’t place an order for you. Even our smartphones with existing conversational models like Alexa, Siri, and Cortana are not capable of doing all sorts of tasks. We also have something called AI agents that can be trained to perform a specific task, but they could be more feasible. And these things open up a whole new area of possibilities where Large Action Models (LAMs) come into action. LAMs are a super advanced version of LLMs operating at approximately 10x the speed of general LLMs. They are advanced computational models designed to handle complex and sophisticated actions in various domains.
Rabbit AI: Large Action Models (LAMs)
The Large Action Models (LAMs) are advanced artificial intelligence systems that are capable of understanding the human intention and predicting actions. In this article, we will be covering the fundamentals, working and architecture of the Large Action Models.
We have all heard about Generative AI & LLMs, used them, and seen their tremendous impact across various industries, especially in tasks like conversation bots, image generation, and customer service. They provide great information regarding asked queries. They mainly work by predicting the next word that should be there using natural language processing techniques. You must have used tools like ChatGPT, MidJourney, and Bard, which are the most common examples of Generative AIs and Large Language Models. These tools are fostering innovation in different kinds of tasks like content creation, website designing, and text-to-image / video generation, and the list keeps on growing.
However, there is one area where all these LLM models lack, and that is taking “ACTIONS” based on the commands given by the user. These models can provide detailed steps to perform a task but cannot perform the task on your behalf. The aim of the article is to cover the fundamentals of this cutting-edge technology and its applications.
Table of Content
- What is Action Model Learning?
- What is Pattern Recognition?
- What is Neuro-symbolic programming?
- What are Large Action Models?
- Applications of LAMs
- Working of LAMs
- Technical Aspects of Large Action Models