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2023
5221

Aligning language models to follow instructions

We’ve trained language models that are much better at following user intentions than GPT-3 while also making them more truthful and less toxic, using techniques developed through our alignment research. These InstructGPT models, which are trained with humans in the loop, are now deployed as the default language models…

5228

The Scaling Hypothesis

On GPT-3: meta-learning, scaling, implications, and deep theory. The scaling hypothesis: neural nets absorb data & compute, generalizing and becoming more Bayesian as problems get harder, manifesting new abilities even at trivial-by-global-standards-scale. The deep learning revolution has begun as foretold.

5236

CLIP: Connecting text and images

We’re introducing a neural network called CLIP which efficiently learns visual concepts from natural language supervision. CLIP can be applied to any visual classification benchmark by simply providing the names of the visual categories to be recognized, similar to the “zero-shot” capabilities of GPT-2 and GPT-3.

5242

What I Learned at Stripe

In February 2022, I left my job at Splunk to take some time first to relax then to focus on finding a fantastic next job . I managed to do both during my three months of funemployment, landing a job at Stripe in the Atlas team in May. I was laid off in November 2022, along with most people who were hired during this…

5245

World Building with GPT

I’ve been doing lots of experiments with GPT , though I’ve only written about one until now… the more serious something is the harder it is to call it finished or identify the outcomes. Here I’ll describe something a bit lighter: world building, or specifically city building, with GPT .