Recent comments in /f/MachineLearning

nxqv t1_jdxx53i wrote

Reply to [D] FOMO on the rapid pace of LLMs by 00001746

I don't know a whole lot about LLMs because I'm new to the field but I sure do know about FOMO. I recently felt a lot of FOMO about having missed opportunities to path towards graduate school and AI research years ago.

What you need to do is put a name to the face. Dig deep and understand your feelings better.

What is it you're afraid of missing out on exactly?

Untold riches? Researchers don't really make any more or less money than other computer science jobs. And most billionaires aren't following some predetermined path.

Fame? Clout? We can't all be Sam Altman or Yann LeCun or Eliezer Yudkowsky or whoever. Besides, most of the things you see these types of guys say or do in public is only tangentially related to the day to day experience of actually being them.

Impact? I've recently come to realize that a craving for "impact" is often rooted in a desire for one of these other things, or rooted in some sort of egotistical beliefs or other deep seated psychological matter like seeking someone's approval. In reality, you could be the guy who cures cancer and most regular people would only think about you for half a second, your peers could be jealous freaks, and people could still find some tiny little reason to turn on you if they really wanted to. You could easily die knowing you did something amazing for the world and nobody cared but you. Are you the type of person who would be okay with that?

Edit: the "Impact" part was controversial so I'd like to add:

> don't lose sight of the forest because of a tree. We're talking about impact in the context of FOMO - if you feel that level of anxiety and rush about potentially missing out on the ability to make an impact because others are already making the impact you want to make, it's more likely to be ego-driven than genuine altruism

The ability to work on something cool or trendy? There's SO MANY new technologies out there you can path towards a career in. And there will continue to be something cool to do for as long as humanity exists.

Something else?

For each one of these, you can come up with convincing counterarguments for either why it's not real or why you can just find a similar opportunity doing many other things.

And let's be real for a second, if this technology really is going to take knowledge workers' jobs, researchers are probably on the chopping block too.

97

ypxkap t1_jdxwirl wrote

Reply to comment by yaosio in [D]GPT-4 might be able to tell you if it hallucinated by Cool_Abbreviations_9

the bing chat thing is interesting because it can’t seem to tell when it can’t see the whole page, eg if you ask it “what’s the last line of this webpage” you’ll get some line x words in (usually ~1100 words for me but it’s been awhile since i checked). if you then send text from after the “last sentence”, it will act like it’s been looking at it the whole time, but as far as i can tell it has no capacity to notice the text otherwise. i asked it to summarize a chat log txt file i had loaded into edge and it included in the summary that there was an advertisement for an iphone 14 and also that “user threatened to harm the AI”, neither of which were present in the text file. that gives me the impression that it’s seeing something completely different from what edge is displaying that also includes instructions over how to respond in some scenarios including being threatened?

2

CacheMeUp t1_jdxvq8t wrote

Reply to comment by hadaev in [D] Do we really need 100B+ parameters in a large language model? by Vegetable-Skill-9700

Perhaps the challenge is not the size of the internet (it's indeed big and easy to generate new content), but rather the uniqueness and novelty of the information. Anecdotally, looking at the first page of Google results often shows various low-informativeness webpages, where only a few sentences provide information and the rest is boilerplate, disclaimers, generic advice or plain spam.

1

Rioghasarig t1_jdxs956 wrote

Reply to comment by Cool_Abbreviations_9 in [D]GPT-4 might be able to tell you if it hallucinated by Cool_Abbreviations_9

I really don't think your experiment makes much sense. Even if we could determine the confidence level of GPT there's no reason to believe asking it for its confidence level is an effective way of determining the actual confidence. As other people have asked the obvious question is "what's your confidence on these confidence reports"? The logic is baseless.

2

wind_dude t1_jdxrcpp wrote

Reply to [D] Instruct Datasets for Commercial Use by JohnyWalkerRed

>depend on the Alpaca dataset, which was generated from a GPT3 davinci model, and is subject to non-commercial use

Where do you get that? tatsu-lab/stanford_alpaca is apache 2.0, so you can use it for whatever.

​

for OpenAI

"""

(c) Restrictions. You may not (i) use the Services in a way that infringes, misappropriates or violates any person’s rights; (ii) reverse assemble, reverse compile, decompile, translate or otherwise attempt to discover the source code or underlying components of models, algorithms, and systems of the Services (except to the extent such restrictions are contrary to applicable law); (iii) use output from the Services to develop models that compete with OpenAI; (iv) except as permitted through the API...

"""

​

So as far as I'm concerned you are allowed to use the generated dataset for commercial purposes...

​

Only use might be the licensing on the llama models... but you can train another LLM

2

lhenault OP t1_jdxpuso wrote

Reply to comment by onequark in [P] SimpleAI : A self-hosted alternative to OpenAI API by lhenault

Not for now but that’s indeed a cool feature and something available in OpenAI API. It shouldn’t be too hard to implement, as I’ve already started something for that on the gRPC backend, and as FastAPI has a StreamingResponse. Thanks for suggesting it, will try to prioritise this!

2

OnlyAnalyst9642 t1_jdxlki8 wrote

Reply to [D] Simple Questions Thread by AutoModerator

I have a very specific problem where I am trying to forecast tomorrow's electricity price with an hourly resolution (from tomorrow at midnight to tomorrow at 11pm). I need to forecast prices before 10AM today. Electricity prices have very strong seasonality (24 hours) and I am using the whole day of yesterday and today up to 10AM as an input to the model (an input of 34 hours). In tensorflow terms (https://www.tensorflow.org/tutorials/structured_data/time_series) my input width is 34, the offset is 14 and the label width is 24.

Since I only care about the predictions I get at 10AM for the following day, should I only train my model with the observations available at 10am?

I am pretty sure this has been addressed before. Any documentation/resources that consider similar problems would help

Thanks in advance!

1

__scan__ t1_jdxj30g wrote

Reply to comment by robobub in [D] GPT4 and coding problems by enryu42

This is what will happen if we’ve either a) exhausted demand, or b) made software development much easier such that people who previously couldn’t do it now can.

The first was likely true for accountants, but is less obviously so for software — there’s still vastly more useful software to build than actually gets built, and each piece of new software that gets built generally increases that demand.

Perhaps the second is true though — do you foresee enough non-developers being able to write, deploy, maintain, and operate production systems as a result of LLMs (in a way that high level languages and previous tooling didn’t)? If not, or if not in sufficient numbers, maybe what happens is that software developers become more in demand than ever due to their productivity increases resulting in even demand for more software (because they can write it quicker).

1