Personalizing AI Models with Kelvin Guu, Senior Staff Research Scientist, Google Brain
How do you personalize AI models? A popular school of thought in AI is to just dump all the data you need into pre-training or fine tuning. But that may be less efficient and less controllable than alternatives — using AI models as a reasoning engine against external data sources.
Kelvin Guu, Senio…
Finetuned Language Models Are Zero-Shot Learners
This paper explores a simple method for improving the zero-shot learning abilities of language models. We show that instruction tuning—finetuning language models on a collection of datasets described via instructions—substantially boosts zeroshot performance on unseen tasks.
2021: Jason Wei, Maar…
Finetuned Language Models Are Zero-Shot Learners
This paper explores a simple method for improving the zero-shot learning abilities of language models. We show that instruction tuning—fine tuning language models on a collection of tasks described via instructions—substantially boosts zero-shot performance on unseen tasks. We take a 137B parameter…
Kelvin Guu, Google AI: Language models & overlooked research problems
We interview Kelvin Guu, a researcher at Google AI and the creator of REALM.
The conversation is a wide-ranging tour of language models, how computers interact with world knowledge, and much more.
Alignment Newsletter #165: When large models are more likely to lie
Recorded by Robert Miles: http://robertskmiles.com
More information about the newsletter here: https://rohinshah.com/alignment-newsletter/
YouTube Channel: https://www.youtube.com/channel/UCfGGFXwKpr-TJ5HfxEFaFCg HIGHLIGHTS
TruthfulQA: Measuring How Models Mimic Human Falsehoods (Stephanie Lin …
42 - Generating Sentences by Editing Prototypes, with Kelvin Guu
Paper is by Kelvin Guu, Tatsunori B. Hashimoto, Yonatan Oren, and Percy Liang
In this episode, Kelvin tells us how to build a language model that starts from a prototype sentence instead of starting from scratch, enabling much more grammatical and diverse language modeling results. In the process…
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