31–40 of 54 posts
This is pretty alarming tbh. Anyone already making a pivot out of SWE?
I am a SWE currently making a pivot into business owner. The future I see is that everyone is about to become a CEO with a personal assistant that can run a business. So I'm going to start building something of my own starting now.
This is pretty alarming tbh. Anyone already making a pivot out of SWE?
So today’s hard problems are becoming easy problems, but this produces a new set of harder problems for tomorrow. Ad infinitum.
Earlier quoted context omitted.
I am a SWE currently making a pivot into business owner. The future I see is that everyone is about to become a CEO with a personal assistant that can run a business. So I'm going to start building something of my own starting now.
I find it very hard to imagine a world in which software development is fully automated but business owners still have value to bring to the table.
Earlier quoted context omitted.
I am not convinced we have cracked AGI. I just would no longer make a large bet that we have not. We won’t know until an AGI actually starts to act like one. In other words we won’t know until we know and then we are suddenly there. That doesn’t mean I’m on the doomwagon. I feel kind of weird and contrarian but I am just not that afraid of AGI. For the foreseeable future AGI should be much more afraid of us. Imagine…
Fwiw, a majority at OpenAI believes GPT5 will achieve AGI, depending on how you define it, according to Sam Altman.
Just like that. Prompt engineers are also obsolete
Earlier quoted context omitted.
LLMs are having a moment in 2023 like self driving cars were having in 2015. Some really cool demos following a lot of hard work, too much hyperbolic speculation that mass real-world job-destroying deployments are right around the corner, not enough appreciation of how few commercial applications are ok with 99% (or even 99.9%) accurate solutions. Real value being created, but still requiring lots of human ingenuity…
almost nothing involving NLP requires solutions anywhere near that accuracy rate. I've seen the self driving comparisons a lot but they straight up make little sense. there's a reason microsoft's various copilot suites have already popped up (365, X, Bing). massive value to be gained already in the here and now.
This is pretty alarming tbh. Anyone already making a pivot out of SWE?
Earlier quoted context omitted.
LLMs are having a moment in 2023 like self driving cars were having in 2015. Some really cool demos following a lot of hard work, too much hyperbolic speculation that mass real-world job-destroying deployments are right around the corner, not enough appreciation of how few commercial applications are ok with 99% (or even 99.9%) accurate solutions. Real value being created, but still requiring lots of human ingenuity…
almost nothing involving NLP requires solutions anywhere near that accuracy rate. I've seen the self driving comparisons a lot but they straight up make little sense. there's a reason microsoft's various copilot suites have already popped up (365, X, Bing). massive value to be gained already in the here and now.
I say that as someone who works in the space and loves it tbc. And I fully expect to see some wild stuff make it IRL this decade in both NLP and CV, I just think the rubber hits the road a bit more slowly than pop social media discourse would have one think.
Just like that. Prompt engineers are also obsolete