Also, how are you going to attract scientists who want to make a career (which, perhaps unfortunately for them, involves publishing stuff).
They should probably take an example from research.microsoft.com.
They should probably take an example from research.microsoft.com.
Here's an oldie but a goodie: http://people.mbi.ohio-state.edu/datta.53/philtalk.pdf note the talk refers readers to the patent. At the time, reading Google's patents was the best strategy to learn what it was doing.
It's my understanding these efforts continue, you just don't hear a whole lot (if anything) about it publicly.
Check it out, you'll see Apple quietly listed on several university websites, CMU for example: http://www.cmu.edu/corporate/partnerships/cic/tenants.html
I would agree that publishing results is better for several reasons (ethics, pragmatism, probably more thorough evaluation, etc.), but the definition doesn't really deal with the public at all.
TLDR; Reproducibility != public reproducibility.
There are tons of secret research behind any company (and governments), and it's still "science".
(And conversely, lots of published scientific papers are actually not reproducible, but for most of them nobody bothers -- even if other scientists cite them as accurate).
For example, say I measure gravitational acceleration on Earth by dropping a feather repeatedly. I get a number and I publish it. If other scientists just repeat my exact experiment, they will get a similar number and my result will be confirmed. Yay science!
But if scientists decide to check my number by dropping a wide variety of other objects, they will illustrate the flaws in my original experiment and everyone will get a clearer picture of gravity.
So it's not about just reproducing an experiment; scientists seek to test and expand upon each others' results.
That's because a machine learning system has been built up from known principles and hardware; whereas the human brain is not fully understood, so researchers must work their way down from observed evidence to induce theories.
When physicists were struggling to explain radiation, they didn't call it a bug in the atom. It was their understanding, not the system they studied, that needed fixing.