This is why about 90% of the papers Google publishes are useless.
They describe deep learning successes, with datasets that aren't public, on hardware that isn't public, with software that isn't public.
They describe technologies, be it spanner, borg, flumejava or others, relying on closed hard- and software.
If an average university professor can't replicate research 1:1 based solely on existing, open technology and the paper, the paper should not be accepted by any journal. In fact, it shouldn't even be accepted on conferences, or be able to get a doi code. That's not worthy of being called science.
And it’s problematic when a large amount of AI research happens at Google, Facebook and co., and none of it can be replicated. Science requires replication, if AI research can’t be replicated, it’s not science.