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関連する概念動画

Neural Circuits01:25

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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Light Acquisition02:16

Light Acquisition

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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

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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,...
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Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

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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...
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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...
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Photoelectric Effect02:26

Photoelectric Effect

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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...
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関連する実験動画

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

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インターネットのエッジに移動したフォトニック・ディープラーニング

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
まとめ

エッジデバイスで効率的な光学推論を可能にする 新しい機械学習手法であるNetcastを開発しました この技術は高度なコンピューティングの エネルギー消費を劇的に削減し 強力なAIを 小さなデバイスでも利用できます

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Lensless Fluorescent Microscopy on a Chip
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Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

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関連する実験動画

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

Published on: September 8, 2023

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Lensless Fluorescent Microscopy on a Chip
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科学分野:

  • 光学について
  • 機械学習
  • エッジコンピューティング

背景:

  • 先進的な機械学習モデルは,かなりの電力,処理,メモリを必要とし,リソースの制限のあるエッジデバイスでの展開を制限します.
  • 現在のエッジデバイスは ハードウェアの制限により 複雑なAIモデルを実行できません

研究 の 目的:

  • ネットワーク上のデロカライズされたアナログ処理を用いた機械学習の推論のための新しいアプローチであるNetcastを導入します.
  • クラウドベースのスマートトランシーバーから重量データをストリーミングすることにより,エッジデバイスに超効率的な光学推論を可能にします.

主な方法:

  • クラウドベースのスマートトランシーバーを使用して,エッジデバイスに重量データをストリーミングするシステムであるNetcastを開発しました.
  • 機械学習の推論のためのデロカライズされたアナログ処理を実装した.
  • フォトニック推論を用いた 画像認識実験を行いました

主要な成果:

  • 超低光学エネルギーで画像認識 (40アトジョル/倍,<1フォトン/倍) を達成した.
  • 高い分類精度が実証された: 実験室およびフィールド試験で98.8% (93%)
  • 3THzの帯域幅で86kmの光ファイバーで再現的にテストされた性能.

結論:

  • Netcastは,ミリワット級のエッジデバイスで,以前は高性能のクラウドシステムに限定されていたテラFLOPSのコンピューティング速度を達成できます.
  • このアプローチは,エッジAIのパワー,処理,メモリ制約を克服します.
  • Netcastは小型でエネルギー効率の良い機器に 強力なAIアプリケーションの道を開きます