What I mean is, why generate the function when only the data needs to be generated? Let's say I need a function that takes the text content of a post and returns an array of recommended flairs for the user to click. Why do this

/**
* This function takes a passage of text, and recommends up to 8
* unique flairs for a user to select. Flairs can be thought of as labels
* that categorize the type of post.
*
* \@param textContent - the text content of a user's post
*
* \@returns an array of flairs represented as strings
*
* \@imaginary
*/

declare function recommendedFlairs(textContent: string) : <string[]>

When you could write out the function and only generate the data?

async function recommendedFlairs(textContent: string) : <string[]> {
const OAIrequest = await someRequest(textContent);
const flairs = formatResponse(OAIrequest);
return flairs
}

In writing all this out I think I figured it out. You're abstracting away a lot of the headaches that come with trying to get the correct outputs out of GPT?

This is really cool! Maybe I'm lacking creativity, but why bother generating imaginary functions and introducing risk that they aren't deterministic when you could just hit OpenAI's API for the data? For example in your docs you present a feature for recommending column names for a given table. Why is the whole function generated? Wouldn't it be more reliable to write out the function and use OAI's API to get the recommended column names?

Probably

Is the demo broken for anyone else? I can't get past their I agree button

Obligatory https://www.youtube.com/watch?v=9fa9lVwHHqg

I agree with all of this but it's already been done. Social media platforms already use engagement driven algorithms that instrumentally arrive at recommending reactive content.

Cambridge analytica also famously preyed on user demographics to feed carefully tailored propaganda to swing states in the 2016 election.

Appreciate it! Articulation isn't a strong suit of mine but I guess a broken clock is right twice a day

?

What freaks me out the most are the social ramifications of AIs that pass as humans to the majority of people. We're still figuring out how to healthily interact with social media and soon we're going to be interacting with entirely artificial content that we're gonna anthropomorphize onto other humans. In the US we're dealing with a crisis of trust and authenticity, I can't imagine generative text models are going to help with that.

Personally my comprehension is still decent and speaking is horrible. If you don't use it you lose it BUT after taking 7 years of Spanish classes I'm confident I could pick up a romance language pretty quickly if I had to.

I think course requirements are probably a bigger factor. In New York you need 2-3 years of foreign language classes in order to graduate high school, and all of the state colleges require foreign language credits.

It would struggle with with questions that span against too much text. Like say you asked it, "how long was I working at McDonalds?" in a daily diary and you worked at McD's for 2 years. They don't have enough context.

Not everything existential threat is political propaganda. Climate change being a good example.

I'm pretty sure GPT-J 6B requires a minimum of 24gigs of VRAM so you would need something like a 3090 to run it locally. That said I think you're better off hosting it on something like collab or paperspace.

Whisper too!! Being able to efficiently train on audio gives us so much more data to work with and we're going to need it. GPT models are already running out of training data.

Yeah of course; but that's 2050, not 2027 as metaculus predicts.

I'm inclined to trust the people actually building AI. 50% or experts agreeing AGI is likely in the next 30 years is still pretty insane. Personally I think a lot of the AI by 2030 folks are delusional.

He's not wrong... In a 2017 survey distributed among AI veterans only 50% think a true AGI will arrive before 2050 https://research.aimultiple.com/artificial-general-intelligence-singularity-timing/

I'd be interested in a more recent poll but this was the most up to date that I could find.

EDIT: Found this from last year https://www.lesswrong.com/posts/H6hMugfY3tDQGfqYL/what-do-ml-researchers-think-about-ai-in-2022

Looks like predictions haven't changed all that much, but there's still a wide range. Nobody really knows that's certain.

Does metaculus only poll people in the field and verify credentials or can anybody submit an estimate? If it's the latter, why take any stock in it? AI seems like one of those things that attracts a lot of fanatics who don't know what they're talking about.

Polls of industry veterans tend to hover around a 40% change of AGI by 2035

LMAO. Fair point but judging by how difficult some of those are compared to the past I'd imagine Googles object detection is getting pretty good.

Real time object classification isn't a fever dream, neural networks that classify objects can be run on very modest hardware today. The tricky part is making the glasses stylish and not having cords connecting them to your phone.

This guy's whole channel is really good https://www.youtube.com/@EdanMeyer/videos

It's less about the singularity and more about Machine Learning in General but unlike a lot of the sensationalized garbage you'll find on youtube, it's very educational.

If you're looking for something that's easier to digest Robert Miles is really good at breaking down AI allignment into funny entertaining videos https://www.youtube.com/@RobertMilesAI

I gotchu. First thing you need to do is learn Python. You don't need to be a master by any means but you should understand variables, expressions, functions, classes, packages/dependencies, file systems, and basic algebra. Run through this amazing book and you'll understand plenty to get into the ML side of things.

Once you know a bit of Python complete this course Practical Machine Learning for Coders. This is an extremely highly regarded modern crash course to machine learning that is bringing a lot new people into the industry. In the very first lesson you'll build an image classifier that didn't even exist 5 years ago.

As you go deeper and deeper Math becomes more important but CS isn't really necessary.

I take it you haven't watched or read altered carbon. It would be like if only billionairs were immortal and the rest of us were slaves under threat of having to pay off our debts by selling our physical bodies to our debtors.

Fix ur prompts