Readit News>Still, language-learning app Duolingo and fintech app Klarna have recently walked back aggressive stances on replacing humans with AI.
>Some studies have also shown AI isn’t panning out as much as hoped, so far. An IBM survey found that 3 in 4 AI initiatives fail to deliver their promised ROI. And a National Bureau of Economic Research study of workers in AI-exposed industries found that the technology had next to no impact on earnings or hours worked.
The data in favour of the articles conclusion is "some linkedin influencer said so" and
>But Indeed’s findings show that “for about two-thirds of all jobs, 50% or more of those skills are things that today’s generative AI can do reasonably well, or very well.”
And if you read THAT article that's linking it's some MBAs speculating again at a conference. Which isn't inherently a bad thing not everything in the world can or should be quantified in a clear statistical conclusion. But appropriating the language and implying it and then the source is "some ceo dudebro said so" should be treated with at least some dubiousness at this point when a lot more of job market trends can be explained far less nebulously by a generalised slowdown in hiring and economic shocks. If I'm being less generous I can say this is yet another example of the linkedin media complex trying to rewrite reality again.
S3 is an engineering marvel, but it's an insanely complicated backend architecture just to store some files.
Much like twitter it's conceptually simple but it's a hard problem to solve at any scale beyond a toy.
Wouldn’t it make sense to provide these to the user? Even if they might not be perfectly reliable.
This stuff must be documented internally, why not just release it?
Security by obscurity does not work: Your competitor reverse engineer everything you do anyways.
SQL or rather just some schema based database has a ton of advantages. Besides speed, there is a huge benefit for developers to be able to look at a schema and see how the relationships in the data work. Mongodb usually involves looking at a de facto schema, but with fewer guarantees on types relations or existence, then trawling code for how its used.
So, what you're saying is one or more of the following:
1) The work of most programmers should not be considered R&D, and shouldn't be covered by tax schemes intended for R&D.
2) Most "software IP" in the industry is not the result of R&D.
3) You've rarely been involved in the sale of non-R&D "software IP". (Do recall that your original statement was "As anyone that has ever sold software IP knows, most of the value is vested in the person that wrote the code, not the code itself.")
I think the third statement is a bit personal so will leave that alone.