llms don't need healthcare or stock grants
500 karma · joined March 8, 2011
300MW is peanuts compared to their multiple 50GW+ deals to the point you start to wonder why just 300MW is making the difference in their capacity that they can increase limits this much... also, why couldn't their many existing multi billion dollar deals not allow them to expand capacity?
when you take this into account, then you read their statement about orbital compute it starts to smell quite fishy
that isn't to say an llm can't be useful but your post implies it's inevitable that llms will replace humans entirely from writing code, which i think is incredibly optimistic at best.
that said we will see!
i see on a weekly basis where if an llm was left to do what its initial direction was without human oversight it would have broken otherwise working programs
i find it as a good backstop to catch dumb mistakes or suggest alternatives but is not a replacement for human review (we require human review but llm suggestions are always optional and you're free to ignore)
what models have you been using that are the least helpful?
i especially find suggestions distracting in markdown where i feel is the key place i really dont want an llm trying to interfere in my ability to communicate to other developers on my team
that said, we will see over the next few years who is right!
i don't see llm code review as any kind of code review replacement; more as a backstop to catch things a human might miss (like today an llm caught an unimplemented feature in a POC that would have otherwise been easy for a human to miss)
- intelligent autocomplete: the "OG" llm use for most developers where the generated code is just an extension of your active thought process. where you maintain the context of the code being worked on, rather than outsourcing your thinking to the llm
- brainstorming: llms can be excellent at taking a nebulous concept/idea/direction and expand on it in novel ways that can spark creativity
- troubleshooting: llms are quite good at debugging an issue like a package conflict, random exception, bug report, etc and help guide the developer to the root cause. llms can be very useful when you're stuck and you don't have a teammate one chair over to reach out to
- code review: our team has gotten a lot of value out of AI code review which tends to find at least a few things human reviewers miss. they're not a replacement for human code review but they're more akin to a smarter linting step
- POCs: llms can be good at generating a variety of approaches to a problem that can then be used as inspiration for a more thoughtfully built solution
these uses accelerate development while still putting the onus on the developers to know what they're building and why.
related, i feel it's likely teams that go "all in" on agentic coding are going to inadvertently sabotage their product and their teams in the long run.
it will be seen how the actual requirements will be validated, likely in a way that favors the "best case" scenario for apple.
for example my iphone 15 pro is at 83% with 654 cycles. clearly it will drop below 80% in less than 1000 cycles