[neilv]

The first paragraph of the first section of reasons given is:

> Alexa put a huge emphasis on protecting customer data with guardrails in place to prevent leakage and access. Definitely a crucial practice, but one consequence was that the internal infrastructure for developers was agonizingly painful to work with.

I really don't want this to be a message companies are hearing right now -- that being conscientious about customer data is a lethal barrier to progress, in the "AI" gold rush.

Also, without knowing anything about the organization, I'd expect it to probably have a high level of dysfunction, being at a company known for being excessively metrics-driven from the top, and for ruthless stack-ranking and related HR practices... trying to organize a large coherent cutting-edge R&D effort against that cultural backdrop. Like suggested by this bit elsewhere in the section:

> And most importantly, there was no immediate story for the team’s PM to make a promotion case through fixing this issue other than “it’s scientifically the right thing to do and could lead to better models for some other team.” No incentive meant no action taken.

[wepple]

Whilst there may be some inefficient bureaucracy in large orgs, I’m tempted to offer the following proposition:

Companies that are absolutely at the forefront of AI, must be by definition, doing terrible things wrt privacy & security.

[pessimizer]

> I really don't want this to be a message companies are hearing right now

They won't be hearing it, they'll be (and are) sending it. "AI would be better for you if it had fewer guardrails around your privacy. Trust us."

[johndhi]

You may not want privacy guard rails to be contrary to progress in AI but I'm afraid they may be.