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> "Previously, those were kind of off the books, under the table. You know, 'Don't ask don't tell deployments.' "But now suddenly, it's the AI team and they've

by twa927 7y ago

> "Previously, those were kind of off the books, under the table. You know, 'Don't ask don't tell deployments.' "But now suddenly, it's the AI team and they've got to be supported." Are AI devs (Data Scientists?) really regarded that much higher by the management compared to the regular devs? Do you think this is special or is it just the current fad that is large enough to reach the management?

gonyea 7y ago
In my experience, Developers who deviate from the norms are able to support themselves. Data Scientists are generally more dependent on support and infra from the rest of the org.
bluGill 7y ago
Regular devs tend to have to target users. You can love X as much as you like, but if your users are on Y you will find it easier to be on Y as well. Devs that have a business case to not be on Y have been using X for years. The only thing different about AI devs is they are enough to get a critical mass in some areas as opposed to the weird guy.
geodel 7y ago
Yes I think so. At our place all data scientist/big data types are given high end MBPs and >2 good quality 4K monitors. All other typical IT devs are given a low-end 15W HP laptop and 2 HD monitors again from HP. Low quality Windows machines have been mandated right from top IT leadership. So I think data scientists are important enough if they can override or get exception to standard issue hardware/software.
- twa927 7y ago
  That's interesting, I'm wondering if this happens also to e.g. "Cloud Specialists" or happened to "Object Orientation Specialists" 20 years ago...
  - geodel 7y ago
    Maybe. But I think it is mainly due to expensive ass consultants selling management the idea of deriving deep insights out of terabytes of application logs. And since it is about big data so big hardware seems natural to management. Regarding OO Specialists I remember in J2EE heydays stodgy Weblogic/Websphere tools would take 2GB RAM when 256MB was more of standard. So management would approve this configuration for important enterprise projects done in J2EE.

by twa927 7y ago

gonyea 7y ago

In my experience, Developers who deviate from the norms are able to support themselves. Data Scientists are generally more dependent on support and infra from the rest of the org.

bluGill 7y ago

Regular devs tend to have to target users. You can love X as much as you like, but if your users are on Y you will find it easier to be on Y as well. Devs that have a business case to not be on Y have been using X for years. The only thing different about AI devs is they are enough to get a critical mass in some areas as opposed to the weird guy.

geodel 7y ago

Yes I think so. At our place all data scientist/big data types are given high end MBPs and >2 good quality 4K monitors. All other typical IT devs are given a low-end 15W HP laptop and 2 HD monitors again from HP. Low quality Windows machines have been mandated right from top IT leadership. So I think data scientists are important enough if they can override or get exception to standard issue hardware/software.

twa927 7y ago
That's interesting, I'm wondering if this happens also to e.g. "Cloud Specialists" or happened to "Object Orientation Specialists" 20 years ago...
- geodel 7y ago
  Maybe. But I think it is mainly due to expensive ass consultants selling management the idea of deriving deep insights out of terabytes of application logs. And since it is about big data so big hardware seems natural to management. Regarding OO Specialists I remember in J2EE heydays stodgy Weblogic/Websphere tools would take 2GB RAM when 256MB was more of standard. So management would approve this configuration for important enterprise projects done in J2EE.