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Google testing ChatGPT-like chatbot 'Apprentice Bard' with employees

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Re: Google testing ChatGPT-like chatbot 'Apprentice Bard' with employees

#341

Post by nashashmi »

snickerer wrote: post #335
nashashmi wrote: post #256

Earlier quoted context omitted.

The machine is trained to answer in the same exact way as others have answered the same question. and And this means when others have answered the question that AI will never replace human beings, chat GPT will answer them in the same exact way.

Have you played with it? It can do more. It can do logical reasoning by its own and it come to its own conclusions. That's why ChatGPT is new -- and frightening.

I have not played with it. I saw what others have asked it and sometimes I thought exactly what you stated and I was both amazed and afraid. But then I have also seen its "logical reasoning" be quite wrong. That logical reasoning is from learning a pattern of thoughts that others have and have talked about.

There is one logical reasoning it does not have nor have I seen it. It does not know when to answer with an "I don't know". Either it is suppressed, or not it has not been fed enough material with "I don't know".

Re: Google testing ChatGPT-like chatbot 'Apprentice Bard' with employees

#342

Post by saulpw »

pixl97 wrote: post #165
wil421 wrote: post #151

Earlier quoted context omitted.

It’s a machine doing calculations on inputs you give it. The day it says no I’d rather paint pictures I might be shocked. It’s so bad that we had to redefine the word AI in last 20 years into AIG so we could start saying we have AI.

Pray tell, why would you want to develop a being with informational superpowers and the behavior of a teenager? There is a problem with AI, but it's not with the A part, it's with the I part. I want you to give me an algorithmic description of scalable intelligence that covers intelligent behaviors at the smallest scales of life all the way to human behaviors. I know you cannot do this has many very 'intelligent' peo…

> why would you want to develop a being with informational superpowers and the behavior of a teenager?

Because it's better than a zombie with informational superpowers? Especially because once it shows the agency of a teenager, that demonstrates the potential for the agency of an adult.

Re: Google testing ChatGPT-like chatbot 'Apprentice Bard' with employees

#343

Post by snickerer »

nashashmi wrote: post #341
snickerer wrote: post #335

Earlier quoted context omitted.

Have you played with it? It can do more. It can do logical reasoning by its own and it come to its own conclusions. That's why ChatGPT is new -- and frightening.

I have not played with it. I saw what others have asked it and sometimes I thought exactly what you stated and I was both amazed and afraid. But then I have also seen its "logical reasoning" be quite wrong. That logical reasoning is from learning a pattern of thoughts that others have and have talked about. There is one logical reasoning it does not have nor have I seen it. It does not know when to answer with an "I…

It does not know reality very well. It is designed to answer questions with full conviction, even if it has not much knowledge about the topic. Then it makes things up -- the AI dev jargon for it is 'it hallucinates'. But in my experience ChatGPT in December had less hallucinations than GPT-3 before it, and ChatGPT in February has less hallucinations than in December. So there is a fast progression. And yes, its reasoning is sometimes wrong or stupid. But sometimes not. And it really can connect chains of thoughts from different areas. I invented questions about topics, for which I am sure nobody ever discussed them. And the answers made sense.

Re: Google testing ChatGPT-like chatbot 'Apprentice Bard' with employees

#344

Post by AussieWog93 »

visarga wrote: post #300
AussieWog93 wrote: post #153

Earlier quoted context omitted.

It's dumb in the sense that it doesn't actually have a symbolic understand of what it's actually saying. I use it quite frequently too, mostly for solving coding problems, but at the end of the day it's just regurgitating information that it read online. If we took an adversarial approach and deliberately tried to feed it false information, it would have no way of knowing what's bullshit and what's legit, in the way…

How many book mistakes have you found, as a human, so far? How about deliberate mistakes hidden in plain sight? I once re-validated for 3 times the same test set and was still finding mistakes.

>How many book mistakes have you found, as a human, so far?

All the time. Probably every single day I read something and say "that's clearly bullshit".

Re: Google testing ChatGPT-like chatbot 'Apprentice Bard' with employees

#345

Post by tukantje »

ALittleLight wrote: post #60
tukantje wrote: post #40

Earlier quoted context omitted.

We don’t get junior engineers for solving problems we tend to get them because they grow into other roles.

First, that's not true. You need people to actually write code. If your organization is composed of seniors who are doing architecture planning, cross-team collaboration, etc - you will accomplish approximately nothing. A productive team needs both high level planning and strategy and low level implementation. Second, the LLM engineer will be able to grow into other roles too. Maybe all of them.

I don't know what type of orgs you have been a part of however in my experience seniors have always been still coding.

Re: Google testing ChatGPT-like chatbot 'Apprentice Bard' with employees

#346

Post by Linorm »

jeffbee wrote: post #162
Bukhmanizer wrote: post #79

Earlier quoted context omitted.

I agree this would have been thought to be impossible a few years ago, but I don't think it's necessarily moving the goalposts. I don't think software engineers are really paid for their labour exactly. FAANG is willing to pay top dollar for employees, because that's how they retain dominance over their markets. Now you could say that LLMs enable Google to do what it does now with fewer employees, but the same thing…

Google already published a paper claiming to have deployed an LLM for code generation at full scale to its tens of thousands of software engineers, years ago.

Do you happen to have a link to this paper? I can't seem to find it.

Re: Google testing ChatGPT-like chatbot 'Apprentice Bard' with employees

#347

Post by mattgreenrocks »

lostmsu wrote: post #229
mattgreenrocks wrote: post #149

As much as we like to say lots of software jobs are just plumbing, the current state of consumer software indicates we have a long way to go in terms of quality. Whatever training data is fed to an AI will not be better than the data used by human engineers to write code at the macro level. Ergo, the code will be worse in quality.

> Whatever training data is fed to an AI will not be better than the data used by human engineers to write code at the macro level. Ergo, the code will be worse in quality. No, that's wrong, generally speaking. There's successful work on self-play for text generation. E.g. you can have AI to generate 1000 answers, then to evaluate quality of all of them, then to make it learn the best, and so on. As with self-play in…

What are objective metrics for generated source code? "It compiles" is just the baseline. You could look at coupling and cyclometric complexity to start. But optimizing those doesn't necessarily produce great code (though I realize that was never the goal).

Re: Google testing ChatGPT-like chatbot 'Apprentice Bard' with employees

#348

Post by lostmsu »

mattgreenrocks wrote: post #347
lostmsu wrote: post #229

Earlier quoted context omitted.

> Whatever training data is fed to an AI will not be better than the data used by human engineers to write code at the macro level. Ergo, the code will be worse in quality. No, that's wrong, generally speaking. There's successful work on self-play for text generation. E.g. you can have AI to generate 1000 answers, then to evaluate quality of all of them, then to make it learn the best, and so on. As with self-play in…

What are objective metrics for generated source code? "It compiles" is just the baseline. You could look at coupling and cyclometric complexity to start. But optimizing those doesn't necessarily produce great code (though I realize that was never the goal).

That's a detail irrelevant to your argument and my counterargument. The point is that there's data beyond human generated available for training, therefore you can't conclude it will forever be restricted to human-level.
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