One of the well-known problems is that ChatGPT can't count, but today it suddenly came to light that OpenAI has given a magical solution to the problem, which is AI programming.
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text = """
There has been rapidly growing interest in meta-learning as a method for increasing
the flexibility and sample efficiency of reinforcement learning. One problem in
this area of research, however, has been a scarcity of adequate benchmark tasks.
In general, the structure underlying past benchmarks has either been too simple to
be inherently interesting, or too ill-defined to support principled analysis. In the
present work, we introduce a new benchmark for meta-RL research, emphasizing
transparency and potential for in-depth analysis as well as structural richness.
Alchemy is a 3D video game, implemented in Unity, which involves a latent
causal structure that is resampled procedurally from episode to episode, affording
structure learning, online inference, hypothesis testing and action sequencing based
on abstract domain knowledge. We evaluate a pair of powerful RL agents on
Alchemy and present an in-depth analysis of one of these agents. Results clearly
indicate a frank and specific failure of meta-learning, providing validation for
Alchemy as a challenging benchmark for meta-RL. Concurrent with this report, we
are releasing Alchemy as public resource, together with a suite of analysis tools
and sample agent trajectories
"""
Counting the number of words in the text
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