Ask HN: After GPT4 Livestream. Are you inspired or ready to quit dev job?
Just finished watching the GPT4 livestream. It was amazing, but I wonder what this means for future and viability of a simple software developer career.
What do you think?
What do you think?
There's a lot more to a programming job than just code.
Evolving a working programing to do something slightly different is programming.
AI will augment software engineers not replace them.
We’ll do more. If right now it takes a team of seven (3 backend, 2 frontend, plus EM plus PM) 3 months to come up with an MVP that does X, well, with AI tools, the company is not gonna fire those engineers and replace them all with only one “prompt” engineer. No way! The company would instead keep all the engineers but instead of launching 1 MVP in 3 months, it will launch it in 3 day! Or better, it will launch 20 MVPs in 3 months!
Once we start applying AI to software engineering, customer demands will sky rocket. Customers will expect nice human-like UX, and rather than waiting months for products and features to come live, they will demand speed. Companies will hire more engineers to fulfill that demand.
For now, it seems to be limited to writing Python scripts using a specific API, not something I do for my daily tasks. I'm more worried for people who could have been replaced by a simple script 30 years ago. Also I'm skeptical about whether or not companies will tell all their secrets to this kind of tool (but I could be wrong, Office 365 has all the secrets of the world).
Also, there are plenty of examples out there of people using it to ask questions.
https://www.youtube.com/watch?v=OgYQAS9LY3o
Exmaple:
I want you to become my Prompt engineer. Your goal is to help me craft the best possible prompt for my needs. The prompt will be used by you, ChatGPT. You will follow the following process:
1. Your first response will be to ask me what the prompt should be about. I will provide my answer, but we will need to improve it through continual iterations by going through the next steps.
2. Based on my input, you will generate 2 sections.
a) Revised prompt (provide your rewritten prompt. it should be clear, concise, and easily understood by you),
b) Questions (ask any relevant questions pertaining to what additional information is needed from me to improve the prompt).
3. We will continue this iterative process with me providing additional information to you and you updating the prompt in the Revised prompt section until I say we are done.
During this demo, a man demoed a prototype of the modern computer, complete with a mouse, keyboard, and programs that draw drawing and edit text.
The kind of software engineer who just churns existing code for no reason might be replaced. Or exposed. Or perhaps he'll use GPT4 to produce even more churn and get promoted.
Who knows. This industry has horrible practices and rewards some of the worst people.
ML/LLM does not fundamentally understand the code. It has to be trained based upon contextual information as to what the code is doing. There are already researchers experimenting with "poisoning" ML models.
For the industry, it just means that a lot of people who _cannot_ code (IE, they haven't the skill, training, or experience to do it) will "start coding" and launch products. Then, when it breaks they'll have to rely upon someone who actually understands why the edge-case bug happened.
ML/LLM are awesome foot-cannons. They have their place, but like a firearm — their 90% use-case will be to cause harm to other individuals (directly, or indirectly).
It doesn't need to understand it, it needs to have correct output often enough. At some point it gets so good at producing code, and so good at explaining code too, that the behaviour is indistinguishable from understanding and that's good enough.
Which explains the bullshit output it generates often enough. A software engineer would be able to detect this rather than a normal user trying to code. That is the point of the parent comment. It is the same with lawyers, doctors, investment bankers and bankers.
There is no fundamental 'breakthrough' in GPT-4 other than training it on more data and super computers. It is still a black-box neural network 'AI' not able to understand its output and give a transparent explanation about its choice of words.
OpenAI (Microsoft) has just gotten better at marketing stunts like this. What they say publicly about their own products turns out to be a different reality.
If any the demo just showed me the next high level programming language: pseudocode (or just plain English)
Not a dev but I assume there is a hard quality barrier - ie does the code work. I'm in digital marketing/seo, and there is a much lower barrier for 'good enough' content. Couple this with a much higher drive for quantiy of content - across web content, social content, and email content. If you can produce enough cheaply it works - look at spam emails as an example.
I am curious if this will lead to a circular logic style training situation for AI in the future - where it begins to train itself on content previous versions have published. Or copyright craziness where it is filtering AI content from it's training materials.
Image generators seem to be on a downward slope in the hype curve. You see their creations in low-budget blogs or game prototypes. But the ones that were generated quickly stick out, and the ones that were generated with careful repetition are expensive unless you and your GPUs' time is worthless.
LLMs could change civilization for the better or worse in any number of ways. They could also turn out to be the next big flop or just another tool if they persistently hover around the "80-90% good enough" threshold.
Personally, I still wouldn't bet a dollar on the question. Computers are interesting and useful, so I'll keep working with them and let the chips fall where they may.
Mostly due to a) extreme legal uncertainty and b) endless harrassment on social media for speaking positively about AI image generation.
There are a lot of very impactful things happening in that space, but the ChatGPT hype sorta drowned it out a bit, in addition to people now keeping actually-good workflows of Stable Diffusion to themselves due to the aforementioned constraints.
You can see the same sort of thing with OpenAI's reluctance to describe the GPT4 model in as much detail as past ones.
I see fewer complaints on Twitter or other social media and more people actually using it to create beautiful images, of course online galleries are full of AI images, but right now they actually compete with human illustrators, not only for quality but also for composition, style, characters, etc. (thx to LoRAs in particular)
Also progress is extremely fast on this research field.
>the ones that were generated with careful repetition are expensive unless you and your GPUs' time is worthless.
There's actually more to it than pure brute force when generating images with generative models, if you know what you're doing, there's no need for a powerful GPU or wasted time.
>just another tool
What are they supposed to be if not tools?
I'm sure as heck not going to rush into spending $200k on a graduate degree in something AI...
I've just been talking with a friend yesterday that this tech is coming sooner and later, in a few years at most ... didn't think it was coming in less than 24hrs from then.
It is going to change all knowledge work a lot, but this is still a demo. It will take time for best uses and integrations to get built.
Assuming OpenAI and Microsoft don't screw it up (and/or a viable open source/competition emerges).
Exciting times!
From now on, it is going to be less engineers and seniors are a cost center waiting to be reduced from a team of 5 to 1 or 2.
The last wave was smartphones: I’m sure they made some jobs obsolete, but it created a whole new well paid role, the mobile engineer. That’s coming, again.
Quite the opposite - good code generation replaces junior engineers more than seior ones.
> No wonder there is so many layoffs.
The layoffs have been completely unrelated so far.
just hoping my employer didnt watch the livestream
It also makes me feel anxious about where this is all going. I'm having questions about whatever I thought was unique about me, or about humans over computers. And like all of us I have a lot of identity and sense of self-worth tied up in my relationship with computers. All of that feels mixed up and confused now. My confidence in how the future will unfold is very low. (I'm also unemployed, which in some ways feels auspicious at this moment, but also creates a high base-level anxiety.)
So far I feel like GPT rewards expertise. That is, your confidence and both breadth and depth of knowledge are accentuated by GPT, not diminished. But will that stay true? Things I think I understand keep changing every couple months. And what will these changes mean to us collectively? I really don't know, and that's uncomfortable.