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Large Action Models (LAMs) | Rabbit R1
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- 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.