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Related Concept Videos

Machines01:19

Machines

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Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. One example of a machine is the cutting plier, which is used to cut wires by applying forces to its handles. When equal and opposite forces are exerted on the handles of the cutting plier, they cause the cutting edges to come together and apply equal and opposite reaction forces on the wire, which are greater than the applied forces.
A free-body diagram of the...
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Introduction to Learning01:18

Introduction to Learning

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Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...
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Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
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Machines: Problem Solving I01:22

Machines: Problem Solving I

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A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
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Machines: Problem Solving II01:30

Machines: Problem Solving II

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Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
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Neural Circuits

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Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
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Deep Neural Networks for Image-Based Dietary Assessment
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Roadmap on emerging hardware and technology for machine learning.

Karl Berggren1, Qiangfei Xia2, Konstantin K Likharev3

  • 1Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139, United States of America.

Nanotechnology
|July 18, 2020
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Summary
This summary is machine-generated.

Machine learning

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Area of Science:

  • Nanotechnology
  • Computer Science
  • Artificial Intelligence

Background:

  • Machine learning (ML) advancements are driven by algorithms and neural networks.
  • Hardware energy efficiency fundamentally limits ML capabilities.
  • Traditional computer architectures are ill-suited for data-centric and neuromorphic computing.

Purpose of the Study:

  • To survey emerging hardware technologies for ML.
  • To highlight challenges and opportunities in neuromorphic computing hardware.
  • To provide a perspective for nanotechnology researchers.

Main Methods:

  • Review of current and emerging hardware platforms.
  • Analysis of device and system-level challenges.
  • Discussion of potential solutions and future directions.

Main Results:

  • Emerging devices and novel architectures are crucial for future computing.
  • Significant challenges exist in materials, fabrication, and integration.
  • Improved throughput and energy efficiency are achievable with new hardware.

Conclusions:

  • A paradigm shift in hardware is necessary for advanced ML.
  • Neuromorphic computing requires specialized hardware solutions.
  • This roadmap outlines key areas for future research and development.