41–50 of 92 posts
It'd probably be best if we all learned some agriculture and opted for simpler lives, rebuilt our social capital (aka community) and learned to do leisure like sane people. The rat race has never thanked anyone for participating, not even software engineers.
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Yeah. Integrating the 99.9% correct code into already existing systems sounds like the software job of the future.
Frankly it sounds not far off from the software job of the present. The correct code is largely the easy part in my experience, but this could be because I struggle immensely with learning each company/department/projects esoteric CI/CD pipelines
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I wasn't worried until Google showed up with a 1M token context with 99.9% recall...
Some random team at Berkeley beat them to it by a couple days: https://largeworldmodel.github.io/ . It's just a matter of throwing compute at it, nothing fancy. OpenAI could probably do 1M token context too but they haven't yet found a way to make it profitable (neither have Google; the most they actually offer customers is 256k).
https://www.theregister.com/2023/10/11/github_ai_copilot_mic...
"Make it profitable" appears a secondary concern in the AI space.
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GPT4, as smart and impressive as it is, starts forgetting or confusing key instructions with as few as 500 tokens (in my experimentation). Practically speaking the advertised 32k context window could be a few orders of magnitude smaller depending on what you're asking it to do!
Did you see the Gemini 1.5 1M token demo? They upload the three.js library and ask it to make changes, which it does successfully and pretty quickly. I want LLMs to fail at my profession as much as everyone at risk of losing their jobs, but unless Google is lying, things are looking pretty grim. https://youtu.be/SSnsmqIj1MI?si=N0zYY_Zbbfz3KRWK
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I’m not saying they’re not vapour, but the article does mention a series of closed door demos and thousands of GPUs deployed, so it at least appears that someone has seen something .
https://en.wikipedia.org/wiki/Magic_Leap https://hn.algolia.com/?dateRange=all&page=0&prefix=false&qu... Healthy skepticism is pragmatic. Sequoia and FTX comes to mind as well. Don't assume an adult was in the room doing due diligence.
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https://en.wikipedia.org/wiki/Magic_Leap https://hn.algolia.com/?dateRange=all&page=0&prefix=false&qu... Healthy skepticism is pragmatic. Sequoia and FTX comes to mind as well. Don't assume an adult was in the room doing due diligence.
That's not the same Magic...
(have done technical due diligence for M&A, but also realize a greater fool can be found; ask lots of questions, and ensure the people you're trusting to validate the responses to those questions have the necessary domain expertise)
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You're already "inside". The danger with automation is that it can pull up the ladder of developing junior talent on nuts-and-bolts, especially if these platforms aren't accessible to students and small-time developers.
Architecture doesn't matter anymore. I can have the AI do general purpose computing. Who cares if its slow? Integration work between two systems? Why bother writing APIs when my robot can spawn 1000 tabs and do manual data entry. Eventually they can just speak English to each other
That is...exquisitely false. Especially under the tensions of scale, architecture matters a great deal. Yes, computers are ridiculously fast these days, but it is quite easy to architect yourself into a situation that cannot be solved by more hardware, not even theoretically. There are plenty of problems that would require more memory than there are fundamental particles in the universe if you model them wrong.
As for your offered examples, you seem to be thinking in terms of glue code and how well it could be replaced by an intelligent agent with its attention focused on a browser, reading one tab and entering data in another. This approach is going to break at any kind of scale greater than 1, and probably be quite brittle at 1. I'd argue that such an agent, if properly trained, will quickly realize that the cost/benefit ratio of it doing the job manually is not nearly as good as if it wrote a program to perform this mechanistic task. In which case, architecture still matters but the agent doing the architecting has changed.
Maybe I'm naive, but I just don't feel threatened by this at all. As a software engineer, I'd love to have an AI engineer automate the boring stuff so I can work on higher-level architecture concerns.
You shouldn't feel anymore threatened by this than by interchangeable parts. People upskill and society ends up as a massive net beneficiary. Until we have ASI (imho we're not remotely close) then there is plenty of work to be done. It will just involve fewer menial tasks.
Prompt: AI, production is down. Fix it. AI: working...
3 days later.
CEO: Hey, dear contractor, our Production is down for 3 days - can you fix it ? Contactor: Sure, give me $500/hour and within 3 weeks it might work again. You know, you have 10mio SLOC, 1mio npm dependencies so it will take a 'bit' longer...
Yes, its bit oversimplified, but imagine it ;)