Stone ages. That’s not 5 years from now. That’s today.
I do and ChatGPT code is rarely useful for me. I can prompt it well enough to do language related stuff for me, but the code it can write for me is more like a highly custom boilerplate that I still need to refactor.
Even for green field private projects, at first it looks fine, bit the bugs are more likely to be traced back to these snippets than not.
I can't trust GPT, and neither can you. But if it really can do all your coding for you, what stops your employer from replacing you with a secretary from a temp agency?
It's so stupid for engineers to say that ChatGPT codes for them. They are shooting themselves in the face. They are devaluing the entire profession. Why? My reaction to all those breathless online demos was to point out the difference between what they were showing and what an engineer really does. Your reaction is to act like being a prompt jockey is the new way of engineering. How does that give you pride in yourself?
All I did was hold it's hand, it wrote every line of code. You are living in fantasy land if you think we will be writing lines of code in 10 years.
I was with you until that sentence. No, LLMs will not write all our code and the reason is very simple: coding is easier than reviewing code. Not to mention the additional complexities and weirdness that we've always dealt with without even thinking about it.
We can see in Photoshop what's coming for developers: context-sensitive AI autocompletion and gap filling. Copilot but more mature and integrated, perhaps with additional checks that prevent some bugs being inserted. And troubleshooting, the area where I think we can profit the most.
but will ChatGPT help you debug and fix a production issue that came about due to a Kafka misconfiguration? will it be able to find the deadlock in your code that is causing requests to be dropped? will it suggest a path forward when you need to replace an obscure library that hasn't been updated in 5 years? will it be able to make sense of seemingly contradictory business requirements?
Wake me up when ChatGPT is able to write and maintain a POS system, or an online store with attached fulfillment management. Anything that goes beyond a fancy 100-line script. Anything that people actually hire teams of senior devs, business analysts and software architects for.
Pontificating their nonsense around the hype about LLMs to the point where they don't even trust it. The same thing they did with ConvNets and they still don't trust that either since they both hallucinate, frequently.
I can guarantee you that people will not trust an AI to fly a plane without any human pilots on board end-to-end (auto-pilot does not count) and it is simply due to the fundamental black-box nature of these so-called 'AI' models being untrustworthy in high risk situations.
I like to think of capable LLMs as pf gifted interns. I can expect decent results if I explain well enough, but I need processes around them to make sure they are doing what they are told. In my industry thats enough to produce a noticeable productivity gain, and likely some reduction of employment as its a low margin cut throat business relying on low grade knowledge workers. I see the hype and honestly cant stand it, but its measureably impacting my industry and the world around me.
Except humans can transparently explain themselves and someone can be held to account when something goes wrong. Humans have the ability to have differing opinions and approaches to solve unseen problems.
An AI however cannot explain itself transparently and just resorts to regurgitating whatever output it has been trained on and black-box AI models have no clear method of any transparent reasoning meaning that it cannot be held to account.
Any unseen problem it encounters, it falls back to fixed guardrails and just repeats a variation or re-wording on what it already has said. Especially LLMs.
Except humans are excellent at finding excuses to avoid explaining themselves and being held to account, or to justify some misguided belief based on whatever output they have been "trained on" in their past.
People often seem to apply standards to AI in terms of rationality and reliability which even many humans cannot achieve, using terms like "hallucination" when we've seen humans do the exact same by confidently talking about things they know nothing about. Everyone laughed at Bing insisting on a wrong date to avoid admitting it's wrong about the Avatar 2 release, when that's very typical behaviour of humans in certain situations.
I'm not trying to make LLMs seem better than they are, but parts of its weaknesses are not surprising given the training data.
Personally, I think LLMs are a step forward, but I suspect that GTP-4 is close to the limit of what’s possible with LLMs. I don’t think we’re going to see AGI from the same approach.
For so many, discussion and debate has been redefined to complain about how much the world sucks.
Capitalism sucks
AI sucks
The US sucks
Crypto sucks
Javascript sucks
Python sucks
Software itself sucks
Take out those thoughts and 90% of the comments on this board would vanish.
That’s a fact.
I also know that voice-interfaces to date have been incredibly stiff and there is ample room for improvement. I know, for a fact, that having AI enable better voice interfaces will make computing better and more accessible. I have a hard time understanding how those are hype-driven comments and/or opinions.
We do know these things for a fact. Not being able to articulate exactly which breakthroughs will be most important doesn’t make it hype.
You’re treating it as a fact that LLM are going to replace existing products, at some unknown future date.
“In 5 years, all code will be written by AI”
“In 5 years, LLM will replace Siri and Alexa”
“In 5 years, AI will replace [sector of jobs]”
The thing that frustrates me about these statements is that you don’t know what AI technology is going to look like in 5 years, so stop treating it like a fact. It’s possible LLM are useful in all of these places, but we don’t know that yet.