Was it GPT4 or GPT3.5?
It spews less bullshit with each new iteration. Matter of time really.
It spews less bullshit with each new iteration. Matter of time really.
In other words, the utility of a calculator that is correct only 99% of time is zero, since you can't even tell when it's wrong.
You wouldn't say "a programmer that is 99% correct is worthless, I need 100%". I'm pushing it, but for a more fair comparison I'd say measure it against a programmer. How often are we wrong? 75% of the time? :) being generous here. It's the tools that make us productive.
I don't know about you specifically, but I don't think you'll be very productive with a bare terminal lacking any modern IDE-like or even REPL facilities. I'll ask you to come up with instantly working code every time, all the time. It doesn't work like that. You need iteration and I believe these kinds of AI have the same issues as us. There are wrong sometimes (often) and need feedback.
It's funny how we resort to humanizing the machines when their results are inaccurate. We don't do that with the calculator, because it's expected to be 100% bug free. When there's a bug in the calculator code we expect it to be fixed, not gradually improved.
Speaking of bugs: mistakes in code is one thing, wrong output because of a fundamental flaw in the algorithm is another. The statistical machines we are dealing with work as intended, or at least the wrong output the top comment here brings up is not a bug, it's a feature. That's the difference.
Gpt-3 performance on MultiArith goes from 18% to 92% with all three. This isn't some hackneyed anthropomizing. Countless research papers showing massive improvement with these processes.
Computers are extremely close to 100%, we generally expect a CPU to never make errors even after years of working. If it starts making any errors at all we throw it away and make a new one.
My computer will pretty much add 1+1 correctly forever never making a mistake.
My computer will perform an 'error' every time I put bad code into it, and some of those logic chains and error conditions are not very obvious.
The issue here is you think the LLM is performing a category 1 error, when the problem we are seeing is a much more human like category 2 error.
We must work in extremely different industries!
The good things about reliable tools is you can offload the cognitive burden onto them and know they won’t screw you over.
Almost every single post here about using ChatGPT mentions checking through its output. People don’t check though the output of their calculators.
Figuring out what’s wanted from me takes forever though.
GPT has a lot of hype and hysteria around it, but demanding 100% accuracy from it is a bit over the top imo. It doesn't need to have 100% accuracy on any arbitrary prompt in order to be a useful and valuable tool.
Yet anything less than represents a danger. Never underestimate stupid.
I see this analogy all the time in these comment sections but it's not a very good one. A person is not a tool. One of the great achievements of humanity, and in computing in particular, is that we make tools that are more accurate than we are.
I expect a hammer to deliver a hard forward blow 100% of the time. If one out of one hundred times it delivers a hard backward blow, I cannot use it on a job site due to risk of injury to the user. The same is true of a calculator being used for financial transactions. And the same is true of a LLM that would be used for drug interactions as discussed in this thread. We already have 100% accurate ways of pulling data from a drug database—it's called SQL. A tool that is not as accurate is in at least some ways a step backward, even if it's easier to use due to its natural language interface.
If I try to light a cigarette and accidentally set my beard on fire due to my own clumsyness, did the lighter malfunction? No, the lighter did exactly what it was supposed to do, it was my hand that didn't do what I expected.
Either way, when working with humans we already deal with plenty of misses and mistakes. Programmers create 10 to 20 bugs per 1000 lines of code, 9 out of 10 businesses fail, accountants make detrimental blunders, etc.
The point is that in the end the ML systems need only to replace these already non-perfect systems. I'll refrain from judging the consequences of this as I think it's out of scope.
Do you think a carpenter who hits themselves with a hammer blames the hammer or themselves? Or are you going to unironically tell me they would blame the hammer + human system?
The discussion is about AI partially replacing human colleagues. In practice, people already are not 100% reliable. You make a reasonable request and someone makes a stupid blunder instead. That's the "hammer" hitting your thumb. Maybe you were not specific enough or maybe they didn't listen but the damage is done.
Our work processes already take mistakes and iterative refinement into account. If AI, in some specific niche, is cheaper and makes no more mistakes than humans do, it gets the job.
It doesn't need to be perfect or perfectly reliable. Some guardrails will be built into it, and we'll come to trust over time.
Please explain how?
>Or are you going to unironically tell me they would blame the hammer + human system?
As your tooling gets more complex, yes it is very easy to have a non-zero blame assignment to each party. Look at any human+machine system where complex failure conditions can occur.
One is a hammer. The other is a human wielding a hammer.
The hammer did work 100% as expected. It's the human, who is fallible, that hit their hand with the hammer. My analogy stands. We make mistakes, we want tools that do not. LLMs should not be compared to humans, they should be compared to other tools.
And yet Excel is widely popular, despite several footguns and inaccurate calculations!
(This might be a moot point, because I'm not sure current methods can ever get to this level of accuracy, due to limitations of the training data. Needs an entirely new method or a clever insight to optimize for truthfulness with unclean training data, and InstructGPT hasn't made much progress on this, and it might not even be possible)
That's not me saying it, read the "System Card".