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Adoption of Large Action Models


Enterprises globally are adopting Large Action Models (LAMs) that understand complex goals communicated with natural language, and they follow up with autonomous actions to achieve them.


GS III: Science and Technology

Dimensions of the Article:

  1. About Large Action Models (LAMs)
  2. What are Large Language Models (LLMs)?

About Large Action Models (LAMs):

  • Advanced AI Models:
    • LAMs represent sophisticated Artificial Intelligence models.
  • Complex Task Execution:
    • These models are crafted to understand and execute intricate tasks based on user requirements.
  • Combination of Language and Logic:
    • Unlike Large Language Models (LLMs), LAMs integrate language comprehension with logical reasoning to carry out various tasks.
  • Learning from Data:
    • LAMs utilize extensive datasets of user action information, leveraging this data for strategic planning and proactive real-time actions.
  • Advanced Machine Learning Techniques:
    • These models employ cutting-edge machine learning methods, including deep learning and reinforcement learning, enabling them to learn from vast datasets and enhance their decision-making abilities over time.
  • Predictive Analysis:
    • By examining past and present actions, LAMs can make informed predictions about future outcomes, aiding in planning, strategy, and real-time decision-making in complex environments.
  • Wide Application:
    • LAMs have applications across diverse fields such as personal assistants, autonomous vehicles, robotics, healthcare, and financial modeling.

What are Large Language Models (LLMs)?

  • AI Programs:
    • LLMs are a type of AI program that can recognize and generate text, among other functions.
  • Extensive Training:
    • They are trained on enormous datasets, which is why they are termed “large.”
  • Deep Learning:
    • LLMs utilize deep learning, a machine learning technique, to understand how characters, words, and sentences work together.
  • Contextual Understanding:
    • These models can infer context, generate coherent and relevant responses, translate into multiple languages, summarize text, answer questions, and assist in creative writing or code generation tasks.

-Source: Indian Express

June 2024