That is what I have been told. It is however clearly messed up.
Surprising good.
It is hard to sell technology to companies when they have their own teams (often using free libraries). Embedded teams are always experts and will often discredit better technology. Often the only method of testing is…
This is what working in a big company is like sometimes. Imagine a person like MaxLeiter working in Netflix. You would think that all staff would be happy that their work became easier. But a minority seem to have a…
I don't keep track of time. That system is old technology. I did confirm from a Netflix employee that they still use it a few months ago. Deep learning, LDA (even one of Xavier's pet projects - k-means), did not do…
I wrote the recommendation system at Netflix (still in use after 5 years). Primary problem was company politics. Many groups were not happy that one person could write a system that was better in A/B test, had more…
The future is a long time. Eventually faster computation, larger memory would allow taking smaller and smaller steps during training (coupled with avoiding "bad optima" with stochastic training). All of this would…
https://research.google.com/pubs/pub45530.html is the most complete recent paper I've seen.
I wrote the recommender at Netflix about 5 years ago (every line of code). Netflix has been degrading it since then. The problem is that many companies are hotbeds of politics over expertise. Recommender, UI, A/B tests,…
There are many intelligent replies here. 5 years ago I wrote the recommendation system that Netflix uses (and has degraded since then). One major problem is in the past certain senior Netflix managers are only…
Netflix is no different to any other company. Your happiness depends on your boss. And even single teams go through bad patches. Some background. I wrote Netflix's recommendation system. Netflix later went on to take…
That is what I have been told. It is however clearly messed up.
Surprising good.
It is hard to sell technology to companies when they have their own teams (often using free libraries). Embedded teams are always experts and will often discredit better technology. Often the only method of testing is…
This is what working in a big company is like sometimes. Imagine a person like MaxLeiter working in Netflix. You would think that all staff would be happy that their work became easier. But a minority seem to have a…
I don't keep track of time. That system is old technology. I did confirm from a Netflix employee that they still use it a few months ago. Deep learning, LDA (even one of Xavier's pet projects - k-means), did not do…
I wrote the recommendation system at Netflix (still in use after 5 years). Primary problem was company politics. Many groups were not happy that one person could write a system that was better in A/B test, had more…
The future is a long time. Eventually faster computation, larger memory would allow taking smaller and smaller steps during training (coupled with avoiding "bad optima" with stochastic training). All of this would…
https://research.google.com/pubs/pub45530.html is the most complete recent paper I've seen.
I wrote the recommender at Netflix about 5 years ago (every line of code). Netflix has been degrading it since then. The problem is that many companies are hotbeds of politics over expertise. Recommender, UI, A/B tests,…
There are many intelligent replies here. 5 years ago I wrote the recommendation system that Netflix uses (and has degraded since then). One major problem is in the past certain senior Netflix managers are only…
Netflix is no different to any other company. Your happiness depends on your boss. And even single teams go through bad patches. Some background. I wrote Netflix's recommendation system. Netflix later went on to take…