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Cake day: June 19th, 2026

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  • I had a discussion with my boss today about potential ways to write code with AI and have confidence in the results without reviewing every line. You’d also have to automate the reviews in some way, and therefore also a way to confirm that the reviewer AIs are working properly, etc. The conversation discouraged me because it made me feel like I’ll end up being a manager of AIs who write the code and test cases, and I’ll just be an ape who manually tests some of the behavior before approving it for release. This is essentially what managers have been doing with human development and QA engineers in the past, but even so, I have a really hard time letting go and not reviewing every line of code myself.




  • Sometimes I wonder what would happen if we created a dolphin with a human brain, or an octopus with a human brain, etc. Are brains plastic enough to adapt? What if after learning how to use one body, the brain was somehow transferred to / plugged into a different body? Would it be possible to learn 2 different bodies and even swap between them at will?






  • nanometer1625@thelemmy.clubtoFunny@sh.itjust.worksBasically this
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    1 month ago

    Its all going to become more efficient enough you can run it all locally. Why are we trying to piss away zillions of dollars on data centers

    The idea that the hardware we currently have is good enough for future applications hasn’t been true of software in general. As better hardware becomes available, software has improved to take advantage of it. Also, the improvements in software have allowed the development of even better hardware, in a virtuous cycle.

    Also, regarding local vs cloud computing in general, datacenters provide an economy of scale that can’t be matched by local compute. Shared datacenters are also more efficient than everyone having expensive hardware that they only use a fraction of the time. This is why datacenters were expanding rapidly even before the recent advances in large language models.