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  • Two Forces Behind Recent Deep Learning Gains

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Digital Activity Expands the Data Pool for Deep Learning

Widespread use of connected devices and internet-scale applications generates digital records that can be collected into large training datasets. The resulting increase in available training data has contributed to recent deep learning gains.

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Updated 2026-08-30

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Google
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Machine Learning

Deep Learning

Supervised Learning

Dive into Deep Learning @ D2L

Data Science

Machine Learning Strategy

Machine Learning Yearning @ DeepLearning.AI

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  • Which pair best explains the main forces behind recent deep learning gains?

  • True or False: Most neural-network ideas were invented only in the last ten years.

  • Recent progress has been driven by more data and more _____.

  • Match the main forces behind progress in deep learning to their descriptions.

  • Arrange the explanation for why deep learning has accelerated recently.

  • Why long-standing deep learning ideas became effective recently

  • Explain why two models improve differently as a dataset expands.

  • Why can expert-crafted features help when labeled data is limited?

  • Which statement best describes why older deep learning ideas became influential later?

  • Two major forces behind recent deep learning gains

Learn After
  • What most directly explains the growth in data available for deep learning?

  • Large labeled datasets are identified as one of the major reasons for recent deep learning progress.

  • Data created through everyday _____ activity can be valuable for training learning systems.

  • Match each element of the data-growth explanation to its role in advancing deep learning.

  • Order the data-flow steps from everyday device use to better deep learning models.

  • Which statement best describes how widespread use of connected devices can accelerate deep learning progress?

  • Recent deep learning progress has been driven only by more training data.

  • When digital services produce user interactions at scale, they often generate _____ quantities of data that can be used to train learning systems.

  • Match each statement in the data-growth argument to the role it plays in the explanation.

  • Put the argument about data growth in order

  • Describe how connected-device data has accelerated deep learning.

  • Why a smartphone app can produce so much training data

  • How does routine use of connected apps affect training data availability?

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