Context (TH): Global firms are adopting Large Action Models (LAMs) to cut costs.
LAM has been integrated into a phone-sized standalone AI device called “Rabbit R1”.
Credits: Peacemonger
But “Rabbit R1” is not limited to performing simpler tasks only. It can be taught to perform any task.
LAMs are super advanced versions of LLMs, operating at approx. 10x the speed of general LLMs.
They are advanced computational models designed to handle complex and sophisticated actions.
These help in understanding complex goals communicated with natural language, and they follow up with autonomous actions to achieve them.
LAMs use agents to perform actions. The agents are software entities capable of independently executing tasks and actively contributing to the achievement of specific goals.
LAMs integrate the linguistic proficiency of LLMs with the ability to perform tasks and make decisions.
Its applications include tackling simpler tasks like ordering a cab, sending emails, etc., and complex tasks like robot motion planning, human-robot interaction, and game development.
Key Features and Capabilities of LAM
Advanced Data Processing: LAM can handle and analyse vast datasets, making it ideal for applications requiring extensive data interpretation.
Enhanced Decision-Making: With its sophisticated algorithms, LAM offers improved decision-making capabilities, enabling AI systems to execute more complex tasks effectively.
Scalability and Flexibility: The model’s scalable nature allows it to adapt to various applications, ranging from simple automation to complex problem-solving scenarios.
How it works?
It breaks down complex actions into smaller sub-actions, allowing for efficient planning and execution.
It uses pattern recognition algorithms to analyse and understand complex data.
After this, Neuro-Symbolic AI comes into play, which combines the pattern recognition capabilities of neural networks with logical reasoning.
Then, the Action Model understands human intentions and executes tasks accordingly.
Potential applications
Healthcare: LAM is revolutionising patient care through advanced diagnostics & personalised treatment.
Finance: In the financial sector, LAM aids in risk assessment, fraud detection, and algorithmic trading.
Automotive: Developing autonomous driving technologies and enhancing vehicle safety systems.
Will LAMs cut jobs?
US insurance firms and a European airline are already using LAm to cut down costs. LAMs would likely automate many knowledge work tasks currently done by humans.
However, supporters argue that they are likely to create more jobs than they replace by enabling new capabilities and allowing humans to focus on higher-level, creative tasks.