1- Be careful how you present your model
... What is clear is that even if we want to attribute some form of intelligence to LLMs, we must acknowledge that it is fundamentally different and largely incompatible with human intelligence—even if on the surface, it produces very convincing output. ...
2- Benchmarks are often misleading
... while benchmarks are a good tool to compare machine learning models against one another, they are not anthropomorphic measures of cognitive skills in machines.
3- Recognize the limits and powers of LLMs
One of the big challenges of large language models is that they can create output that is convincingly human but not based on human cognition. Models like Galactica can be extremely powerful but also dangerously misleading. ...
See the full story here: https://bdtechtalks.com/2022/11/21/meta-ai-galactica/