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Adoption of Large Action Models

Context:

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.

Relevance:

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
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