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Questions and Answers

The current unprecedented progress in AI is underpinned by a new class of AI models called ______.

large language models (LLMs)

LLMs are extremely ______ and adaptable, and have been useful in computer vision, biology, and more.

flexible

The first modern AI revolution took place in ______ with deep learning for computer vision problems.

2012

CNNs, ImageNet, and GPUs were a magic combination that unlocked tremendous progress in ______.

<p>computer vision</p> Signup and view all the answers

However, there were limits to that generation of deep learning, especially in natural ______ processing (NLP).

<p>language</p> Signup and view all the answers

Until recently, RNNs and LSTMs were used to process and analyze data in ______, but they struggled with longer sentences and paragraphs.

<p>time</p> Signup and view all the answers

Getting the right training data for NLP is incredibly time-consuming and ______.

<p>challenging</p> Signup and view all the answers

The breakthroughs in AI are quickly being turned into practical tools and real ______ products that anyone can use.

<p>commercial</p> Signup and view all the answers

Processing language requires working with sequences of ______, where order matters.

<p>words</p> Signup and view all the answers

Large language models have been useful in various fields, including ______ and biology.

<p>computer vision</p> Signup and view all the answers

Study Notes

  • There is currently unprecedented progress in AI across various fields.
  • This progress is underpinned by a new class of AI models called large language models (LLMs).
  • LLMs are extremely flexible and adaptable, and have been useful in computer vision, biology, and more.
  • The first modern AI revolution took place in 2012 with deep learning for computer vision problems.
  • CNNs, ImageNet, and GPUs were a magic combination that unlocked tremendous progress in computer vision.
  • However, there were limits to that generation of deep learning, especially in natural language processing (NLP).
  • Processing language requires working with sequences of words, where order matters.
  • Until recently, RNNs and LSTMs were used to process and analyze data in time, but they struggled with longer sentences and paragraphs.
  • Getting the right training data for NLP is incredibly time-consuming and challenging.
  • The breakthroughs in AI are quickly being turned into practical tools and real commercial products that anyone can use.

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