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Control Systems01:10

Control Systems

987
Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...
987
Control Systems: Applications01:25

Control Systems: Applications

539
Electrical engineering plays a pivotal role in our daily lives, with control systems at the heart of many applications, from home appliances to sophisticated space shuttles. Control systems manage and regulate the behavior of devices and processes, ensuring they function safely, correctly, and efficiently.
In modern vehicles, control systems manage various functions to enhance performance and safety. The steering wheel and accelerator are primary inputs in a car's control system. The...
539
Open and closed-loop control systems01:17

Open and closed-loop control systems

594
Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal...
594
Feedback control systems01:26

Feedback control systems

262
Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
262
Language Development01:22

Language Development

292
Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
The critical period for language acquisition suggests that the ability to acquire language is at its peak early in life. As people age, this proficiency decreases. Language development begins very...
292
Language and Cognition01:27

Language and Cognition

302
Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
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Updated: Jun 20, 2026

Free-form Light Actuators — Fabrication and Control of Actuation in Microscopic Scale
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Tiny Language Models for Automation and Control: Overview, Potential Applications, and Future Research Directions.

Ismail Lamaakal1, Yassine Maleh2, Khalid El Makkaoui1

  • 1Multidisciplinary Faculty of Nador, Mohammed Premier University, Oujda 60000, Morocco.

Sensors (Basel, Switzerland)
|March 17, 2025
PubMed
Summary

Tiny Language Models (TLMs) provide efficient alternatives to Large Language Models (LLMs) for resource-constrained devices. This survey explores TLM techniques, applications in edge computing and IoT, and future research directions for optimized performance.

Keywords:
IoTedge computinglarge language modelsmodel compressionoptimizationsmall language modelstiny language models

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Area of Science:

  • Artificial Intelligence
  • Computer Science
  • Natural Language Processing

Background:

  • Large Language Models (LLMs) achieve high performance in Natural Language Processing (NLP) but are computationally intensive.
  • Resource-constrained devices require efficient, low-power models for applications like smartphones and IoT.

Purpose of the Study:

  • To provide a comprehensive survey of Tiny Language Models (TLMs), also known as BabyLMs.
  • To explore TLM architectures, methodologies, and their applications in edge computing, IoT, industrial automation, and healthcare.

Main Methods:

  • Survey of TLM architectures and methodologies.
  • Analysis of compression techniques including knowledge distillation, quantization, and pruning.
  • Exploration of TLM applications and challenges.

Main Results:

  • TLMs offer compact alternatives to LLMs for efficient deployment on edge devices.
  • Key techniques like knowledge distillation, quantization, and pruning enable TLM effectiveness.
  • Emerging applications span automation, control, IoT, and healthcare.

Conclusions:

  • TLMs are crucial for bringing advanced NLP capabilities to resource-limited environments.
  • Addressing challenges like accuracy trade-offs and generalization is key for TLM advancement.
  • Future research should focus on hybrid compression and hardware-specific optimizations.