New podcast episode! 📢

@l2k and @emilymbender dive into the problems with bigger and bigger language models, the difference between form and meaning, the limits of benchmarks, and the #BenderRule.

🎥:

They discuss 4 of Emily's papers ⬇️

1/5
"On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜" (Bender, Gebru et al. 2021)

Possible risks associated with bigger and bigger language models, and ways to mitigate those risks.

dl.acm.org/doi/pdf/10.114…

2/5
"Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data" (Bender & Koller, 2020)

Why systems trained only on form (like language models) have no a priori way to learn meaning.

aclanthology.org/2020.acl-main.…

3/5
"AI and the Everything in the Whole Wide World Benchmark" (Raji et al., 2020)

How benchmarks have been taken out of context and are limited on their own

ml-retrospectives.github.io/neurips2020/ca…

4/5
"The #BenderRule: On Naming the Languages We Study and Why It Matters" (Bender 2019)

Why you should always state the name of the language(s) you're studying, even if it's "just" English.

thegradient.pub/the-benderrule…

5/5

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