11–20 of 53 posts
It's not just you in the boat and whatever happens you can follow the crowd when/if it happens.
I personally believe it'll just be a new set of tools to reskill in, much like a calculator to an abacus.
Sure it would help to know how to build that calculator, but just changing the batteries and typing sums will be fine, and you can continue doing the theoretical physics equations the calculator helps with but cannot do itself.
At my workplace they recently enabled Microsoft's Copilot which is basically OpenAI + RAG. It's a joke. It is painful to watch how slow it types. About 30% of the time it doesn't work at all. I asked it how big a particle accelerator would have to be to have 1 PeV protons and it got the right equation for the radius of the ring but it told me the ring would be like 10^34 meters in radius which is about 10^24 times to…
I'm not sure if your Godel Escher Bach reference is real, but Douglass Hofstadter himself has recanted some of his views in light of LLMs.
The things you're complaining about are implementation details.
> People who know better act insulted when I remind them that neural networks don't repeal the laws of computer science (e.g. Godel, Turing and all that.)
There is absolutely no evidence that humans do either. Not that I don't believe they do, because I -- due to religious reasons -- think we do. But from a purely empirical perspective, I don't see how you can make this claim at all.
However, reading this, I do not get the impression that your background gives any kind of unique insight others have missed, more that you’ve just read a lot of opinions online.
Online isn't reality. Online, people don't talk about corporate politics and inertia and the million tiny factors that determine which jobs get "replaced" and which don't. I use quotation marks because most people mid-career or higher can see changes coming and either shift out into another role or go into management or solution architect roles where there is a need for human oversight (and tend to be roles that offer more money).
AI is an existential risk only if you choose to do the same job forever.
I work in an industry already being shaped by LLMs. Today, it's eating away at the bottom of the market, but I assume it will eventually eat away at the top where I am positioned too. I was talking to a friend about the book "psychology of money" and the part he shared was related to paying down your mortgage, even if it makes more financial sense to keep your money invested in the market with a higher expected retur…
> Being disrupted by an LLM has created a ton of anxiety for me, and this conversion led to investing almost my entire NW into Nvidia. It is almost never a good idea to convert your entire NW into anything. Nothing is unprecedented.
Literally everyone was freaking out in the 2000's about their job because of India.
The more connections you make and the more people respect you, the more likely you are to get a job when you need one.
What we have right now is not really AI, its not really intelligence in the sense that the models can't reason. All the models out there are forward pass (and yes, even recurrent ones, which can essentially be unrolled). There is nothing on the horizon that indicates that we are even close to getting something that can reason, or are headed in the right direction.
The biggest benefit of current ML stuff is translation. Everything that ML does now is translation, and it will apply to dev more and more over time.
For example, Python and Node dominate the programming world because its way easier to translate ideas into code through abstraction layers. In the same way, the future is going to still require developers, but these developers are going to be coding in something that looks like python. You will be able to type plain english instructions on command line intermingled with traditional code, which will save you a lot of time because you won't have to learn specific syntax of some framework. The language will then be translated to some IR (most likely JS bytecode), which will then be translated by a specially trained model into efficient machine language instructions for a specific architecture.
There will probably be even a come back for FPGAs, because you there will probably be models that optimize architecture for your code, and there would be some use cases where processing at slower speed but in parallel with specific "virtualized hardware" configuration for optimality is actually faster.
And all that will mean is that dev will move faster. You will be able to write code faster, test the code and simulate production usage easier, and generally make things work in way shorter time with way less people. The thing thats preventing a lot of stuff being made now isn't really lack of ideas, its lack of funding.
Now, as for actual AI, i.e intelligence that can reason, if we somehow manage to build it, the cool thing about it is that you will be able to simply ask it a question "Im a regular guy, what is the best way for me to optimize my life that guarantees my current standard of living?", and it will answer this for you.
Can''t you just replace every mention of AI with outsourcing in your post? Literally everyone was freaking out in the 2000's about their job because of India.
In the short term I’m far more concerned about the quality of info just absolutely crashing. Remember the time before google search that made all knowledge accessible? There is a real risk of a returning to that era. Just be virtue of real drowning in genAI and signal/noise collapsing. Even worse things like political misinformation going viral was not a thing back then. So it’s double bad in that sense