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> Researchers say among the reasons Apple has failed to keep pace is its unwillingness to allow its AI engineers to publish scientific papers, stymieing its abi

> Researchers say among the reasons Apple has failed to keep pace is its unwillingness to allow its AI engineers to publish scientific papers, stymieing its ability to feed off wider advances in the field. I don't follow. How would preventing employees from writing papers would stop them from reading papers?

jedberg 10y ago
If the could publish their research other researchers would take their work in a new direction that they didn't think of, which they could then bring back. Basically they can't provide that seed insight that motivates others.
leereeves 10y ago
I think they mean that Apple isn't offering researchers the incentives they desire, and may have trouble recruiting them.
- freyir 10y ago
  Yes. Researchers like to publish their research because their publication record the metric they're evaluated on by the outside world. If you can't publish your research, that will significantly reduce your ability to get hired by another top research group, industrial or academic, in the future.
argonaut 10y ago
Would you rather work for a company that has their engineers actively contribute to open source, or a company where all of your code is private?
sytelus 10y ago
Modern AI research heavily depends on building work of others as well as having others build on your work. It's this virtuous cycle that is bringing all the advances we are seeing. Let's say someone at Apple had invented recurrent networks but they never published it. That would mean they would miss out on literally hundreds of researchers working on this, enhancing techniques in very critical ways and writing thousands of papers over the period of just few years that would feed in to this cycle. Many of these papers would contribute absolutely important enhancements to productionize things. Much of the AI research currently starts with some seed idea like GAN which looks cool in small experiments but have tons of blind spots that needs to iron out. Unlike typical product efforts where you can probably work your way out through brute force engineering, advances in most AI related areas requires massive amount of collaboration, mathematical acrobatics, trial-and-error and cross-pollination across fields consuming multi-person-years before yielding fruits. In theory, Apple can still keep any silver bullets they find in the field secret but in practice such silver bullets are rare and advances are very incremental spanning over many years and many people.
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jedberg 10y ago

If the could publish their research other researchers would take their work in a new direction that they didn't think of, which they could then bring back. Basically they can't provide that seed insight that motivates others.

leereeves 10y ago

I think they mean that Apple isn't offering researchers the incentives they desire, and may have trouble recruiting them.

freyir 10y ago
Yes. Researchers like to publish their research because their publication record the metric they're evaluated on by the outside world. If you can't publish your research, that will significantly reduce your ability to get hired by another top research group, industrial or academic, in the future.

argonaut 10y ago

Would you rather work for a company that has their engineers actively contribute to open source, or a company where all of your code is private?

sytelus 10y ago

Modern AI research heavily depends on building work of others as well as having others build on your work. It's this virtuous cycle that is bringing all the advances we are seeing. Let's say someone at Apple had invented recurrent networks but they never published it. That would mean they would miss out on literally hundreds of researchers working on this, enhancing techniques in very critical ways and writing thousands of papers over the period of just few years that would feed in to this cycle. Many of these papers would contribute absolutely important enhancements to productionize things. Much of the AI research currently starts with some seed idea like GAN which looks cool in small experiments but have tons of blind spots that needs to iron out. Unlike typical product efforts where you can probably work your way out through brute force engineering, advances in most AI related areas requires massive amount of collaboration, mathematical acrobatics, trial-and-error and cross-pollination across fields consuming multi-person-years before yielding fruits. In theory, Apple can still keep any silver bullets they find in the field secret but in practice such silver bullets are rare and advances are very incremental spanning over many years and many people.

deleted 10y ago

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