Perhaps. The data here is not 100% conclusive. There are some critical assumptions holding up our conclusion and [...] has never confirmed (or denied) our findings.
Perhaps the horse lives to tweet another day...
Ironically this highlights one of the main problems with how machine learning is used.
On a very high level, I think you can sum up machine learning algorithms as finding pattern in enormous heaps of noisy data ("training") then trying to apply the discovered pattern to novel data and using the result to guess the answer to a question you posed ("predicting").
The keyword being guess here. Unlike algorithms not based on learning, there is no guarantee that the answer is correct, because you usually don't know if the training data you supplied was sufficient or if the learned patterns were the ones you need. If you knew, you could just hard code the patterns directly and get rid of the whole learning overhead altogether.
Researchers know and communicate this. However, in the press, "AI" seems to be seen as almost the exact opposite: Not only can those fantasy AI systems answer questions about fuzzy human concepts with the precision of a computer, their answers are even better than the human ones - which is why the things we need to worry about are ethics discussions and humanity becoming obsolete...
This could be funny if it were just restricted to science fiction and public discussion, but it becomes problematic when "AI" systems are used to make life-changing descisions like setting insurance premiums or declaring persons suspicious to law enforcement.