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Communication Quote by Andrew Ng

“I think the first wave of deep learning progress was mainly big companies with a ton of data training very large neural networks, right? So if you want to build a speech recognition system, train it on 100,000 hours of data.” quote by Andrew Ng
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“I think the first wave of deep learning progress was mainly big companies with a ton of data training very large neural networks, right? So if you want to build a speech recognition system, train it on 100,000 hours of data.”

Andrew Ng

About This Quote

Early deep‑learning breakthroughs relied on massive data and compute, making large‑scale training essential for high‑performing speech models.

In simple terms: Big data and compute drove early AI gains.

Key Takeaway

Scale matters for model performance.

Themes

AI development data economics model scaling industry innovation

Mood

analytical pragmatic

Type

technical insight observation

When to use this quote

  • speech‑recognition startups
  • large tech labs
  • academic research

Key Concepts

neural network architecture training pipelines

Practical Applications

  • building robust ASR systems
  • benchmarking models

Questions to Reflect On

  • Is scale always necessary for progress?
  • What alternatives exist to massive data?
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