Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Neural Circuits01:25

Neural Circuits

1.4K
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...
1.4K
Light Acquisition02:16

Light Acquisition

8.6K
In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
8.6K
Photoreceptors and Visual Pathways01:22

Photoreceptors and Visual Pathways

6.3K
At the molecular level, visual signals trigger transformations in photopigment molecules, resulting in changes in the photoreceptor cell's membrane potential. The photon's energy level is denoted by its wavelength, with each specific wavelength of visible light associated with a distinct color. The spectral range of visible light, classified as electromagnetic radiation, spans from 380 to 720 nm. Electromagnetic radiation wavelengths exceeding 720 nm fall under the infrared category,...
6.3K
Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

728
A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of...
728
Imaging Biological Samples with Optical Microscopy01:18

Imaging Biological Samples with Optical Microscopy

5.0K
Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...
5.0K
Photoelectric Effect02:26

Photoelectric Effect

30.0K
When light of a particular wavelength strikes a metal surface, electrons are emitted. This is called the photoelectric effect. The minimum frequency of light that can cause such emission of electrons is called the threshold frequency, which is specific to the metal. Light with a frequency lower than the threshold frequency, even if it is of high intensity, cannot initiate the emission of electrons. However, when the frequency is higher than the threshold value, the number of electrons ejected...
30.0K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Foundry-Enabled Patterning of Diamond Quantum Microchiplets for Scalable Quantum Photonics.

Nano letters·2026
Same author

Thermal detection of single photons using Dirac fermions.

Nature communications·2026
Same author

Nanophotonic waveguide chip-to-world beam scanning.

Nature·2026
Same author

Single-shot matrix-matrix photonic processor based on spatial-spectral hypermultiplexed parallel diffraction.

Nature communications·2026
Same author

Disaggregated machine learning via in-physics computing at radio frequency.

Science advances·2026
Same author

Piezoelectrically actuated silicon-nitride-based high-speed spatial light modulator.

Nature communications·2025

Related Experiment Video

Updated: Aug 24, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

637

Delocalized photonic deep learning on the internet's edge.

Alexander Sludds1, Saumil Bandyopadhyay1, Zaijun Chen1

  • 1Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

Science (New York, N.Y.)
|October 20, 2022
PubMed
Summary
This summary is machine-generated.

We developed Netcast, a novel machine learning approach enabling efficient photonic inference on edge devices. This technology drastically reduces power consumption for advanced computations, making powerful AI accessible on small devices.

More Related Videos

Lensless Fluorescent Microscopy on a Chip
11:23

Lensless Fluorescent Microscopy on a Chip

Published on: August 17, 2011

17.7K
Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

2.9K

Related Experiment Videos

Last Updated: Aug 24, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

637
Lensless Fluorescent Microscopy on a Chip
11:23

Lensless Fluorescent Microscopy on a Chip

Published on: August 17, 2011

17.7K
Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

2.9K

Area of Science:

  • Photonics
  • Machine Learning
  • Edge Computing

Background:

  • Advanced machine learning models require significant power, processing, and memory, limiting their deployment on resource-constrained edge devices.
  • Current edge devices cannot run complex AI models due to hardware limitations.

Purpose of the Study:

  • Introduce Netcast, a new approach for machine learning inference using delocalized analog processing across networks.
  • Enable ultra-efficient photonic inference on edge devices by streaming weight data from cloud-based smart transceivers.

Main Methods:

  • Developed Netcast, a system utilizing cloud-based smart transceivers to stream weight data to edge devices.
  • Implemented delocalized analog processing for machine learning inference.
  • Conducted image recognition experiments using photonic inference.

Main Results:

  • Achieved image recognition with ultralow optical energy (40 attojoules per multiply, <1 photon per multiply).
  • Demonstrated high classification accuracy: 98.8% (93%) in lab and field trials.
  • Reproducibly tested performance over 86 km of optical fiber with 3 THz bandwidth.

Conclusions:

  • Netcast enables milliwatt-class edge devices to achieve teraFLOPS computing rates, previously exclusive to high-power cloud systems.
  • This approach overcomes power, processing, and memory constraints for edge AI.
  • Netcast paves the way for powerful AI applications on small, energy-efficient devices.