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Hi everyone yes, I left OpenAI yesterday

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Re: Hi everyone yes, I left OpenAI yesterday

#401

Earlier quoted context omitted.

Sometimes I wish as a profession we valued teaching more. I would love to teach, but not do research, and make a living.

Become the next 3blue1brown. He has inspired many. Here's a gem of educator. Check out his other videos. https://www.youtube.com/watch?v=dhYqflvJMXc

He's a great educator, but at the same time we must recognize that his videos are not a replacement for a traditional math course. They amplify the existing paradigm, not replace.

MOCs are great for access, but they are not, and definitely should not be treated as, replacements. That I am certain will have a net negative result. I'm in grad school and there's something I tell students on the first day:

> The main value in you paying (tuition) and attending is not just to hear me lecture, but to be able to stop, interrupt, and ask questions or visit me in office hours. If you are just interested in lectures I've linked several on our website from high quality as well as several books, blogs, and other resources. Everyone should all use these. But you can't talk to a video or book, but you can to me. You should use all of these resources to maximize your learning. I will not be taking attendance.

I'm sure many of you have had lectures with a hundred students if you went to a large school (I luckily did not). You're probably aware how different that is from a smaller course. It's great for access and certainly is monetarily efficient, but its certainly not the most efficient for educating an individual. MOCs are great because they increase the ability of educators to share notes. We pull from one another all the time (with credit of course), because if someone else teaches in a better way than I do, I should update the way I teach. MOCs are more an extension of books. Youtube is the same, but at the end of the day you can't learn math without doing math. Even Grant states this explicitly.

Re: Hi everyone yes, I left OpenAI yesterday

#402

Earlier quoted context omitted.

I never bought into ethical questions. It's trained on publicly available data as far as I understand. What's the most unethical thing it can do? My experience is limited. I got it to berate me with a jailbreak. I asked it to do so, so the onus is on me to be able to handle the response. I'm trying to think of unethical things it can do that are not in the realm of "you asked it for that information, just as you woul…

One recent example in the news was the AI generated p*rn of Taylor Swift. From what I read, the people who made it used Bing, which is based on OpenAI’s tech.

You are talking like it's something bad. Kids are learning AI and computing instead of drugs and guns. And nobody is hurt.

Re: Hi everyone yes, I left OpenAI yesterday

#403

Earlier quoted context omitted.

this is disrupting education. you can get a better undergraduate education in STEM on youtube than my paid education 20 years ago. I think those visualizations can even pull forward a bunch of stuff into high school.

Well, I get the point and find it appealing but I don't agree. When my kiddo was a sophomore in HS he decided that he wanted to be an engineer, and I thought that it would be really good for him to learn calc- my feeling was that if he got out of HS without at least getting through Calculus he'd have a really hard time. So _I_ learned calculus. I started with basic math on Kahn and moved to the end of the Calc AB syl…

I think it's important to separate the motivation pill from the content delivery. You can buy a motivation pill for cheaper than $160k or whatever a degree costs these days. And we get to compare the very best tryhard youtubers to the median lecturer who is grinding it out.

Re: Hi everyone yes, I left OpenAI yesterday

#404

Earlier quoted context omitted.

GPT-3 came out 3 years before 4.

GPT-3.5 is when LLMs start to get "main stream". That's about 4.5 months before the GPT-4 release. Keep in mind GPT-3.5 is not an overnight craze. It takes months before normal people even know what it is.

>GPT-3.5 is when LLMs start to get "main stream".

To the general public sure but not research which is what produces the models.

The idea that diminishing returns has hit because there hasn't been a new SOTA model in 9 months is ridiculous. Models take months just to train. Open AI sat on 4 for over half a year after training was done just red-teaming it.

Re: Hi everyone yes, I left OpenAI yesterday

#405
post #397
post #350

Earlier quoted context omitted.

That’s kind of the point, you won’t be able to due to the algorithm. I can give you something analogous though: I’m a big fan of old school east coast hip-hop. You have the established mainline artists from back then (“Nas”, “Jay-Z”, “Big L”, etc), then you have a the established underground artists (say, “Lord Finesse” or “Kool G Rap”), and then you have the really really underground guys like “Mr. Low Kash ‘n Da Sh…

Somewhat off-topic, but what do you feel like are the best techniques to find the artists in Tier 2 and 3? I face a similar conundrum just in a different genre.

(I realize know I dislike using the descriptor "tier", as it implies some sort of ranking. Perhaps "layer" would have been better, but I'll stick with it for now)

For both tier 2 and tier 3 its basically the same process. This is for Spotify btw, I have no idea how different the workflow would be for something like Apple Music.

Say the genre you want to dig around in is Hip-Hop. You are aware of Eminem and Mac Miller, and vaguely aware of a guy named Nas. By intuition you'd probably already be able to tell that Nas is more at the edge among the mainline artists.

You click on "Nas", and scroll down to Fans also like. Right now, for "Nas", it is showing "Mobb Deep", "Mos Def", "Rakim", "Big L", "Wu-Tang Clan", "Gang Starr", "Ghostface Killah", "Method Man" and "Common".

This is a mix T1 and T2. "Wu-Tang"s in there along with assorted members, but some of the other artists are much lesser known quantities.

Its a bit hard for me to decide what a Hip-Hop layman would consider the most unknown name here, but I'd venture it'd be "Big L". We click on him, do the same thing. Now we're really getting somewhere, with guys like "Inspectah Deck" and "Smif-n-Wessun". Click, dig, we get a bunch of names amongst which "Lord Finesse" stands out. The Show more at the end of Fans Like is also invaluable.

In total the dig order for me to get to the very bottom of the undeground is "Nas" > "Big L" > "Smif-n-Wessun" > "Lord Finesse" > "Channel Live" > "Ed OG & Da Bulldogs" > "Trends of Culture" > "Brokin English Klik" (358 monthly listeners).

I wouldn't consider each of those going a tier (layer) deeper. As a guy who knows waaay too much about Hip-Hop, I'd separate them into:

- T1: "Nas", "Big L"

- T2 "Smif-n-Wessun", "Lord Finesse"

- T3 "Channel Live", "Ed OG & Da Bulldogs", "Trends of Culture", "Brokin English Klik"

Perhaps "Brokin English Klik" should be in its own T4 and 3 tiers lacks the fidelity to be necessarily accurate. Not sure.

A little shortcut would be using "The Edge of $Genre" playlists. They're the pair playlists to "The Sound of $Genre" (broad slice) and "The Pulse of $Genre" (most popular) generated via everynoise.com, although as that guy got fired from Spotify its up in the air how long those will keep working.

Edit: oh, and if you run into a playlist that caters to that deep underground (in my case, that was "90's Tapes"*), that's worth its bytes in gold.

*https://open.spotify.com/playlist/2H0rNGEBShvHSGebM2m37c?si=...

Re: Hi everyone yes, I left OpenAI yesterday

#406

Earlier quoted context omitted.

Neural networks were already big 10 years ago, you have to go back 15 years to see before they started being popular. From wikipedia: > Between 2009 and 2012, ANNs began winning prizes in image recognition contests, approaching human level performance on various tasks, initially in pattern recognition and handwriting recognition. That was when Neural networks became a big thing every tech person knew about, 2014 it w…

NN were already a casual topic in my high school computer science class more than 20 years ago. I've always assumed they were already fairly common by that point. (~2000)

They were and they were in use, for instance in character recognition. They just hadn't had their breakout success yet.

Re: Hi everyone yes, I left OpenAI yesterday

#407
post #350

Earlier quoted context omitted.

That’s kind of the point, you won’t be able to due to the algorithm. I can give you something analogous though: I’m a big fan of old school east coast hip-hop. You have the established mainline artists from back then (“Nas”, “Jay-Z”, “Big L”, etc), then you have a the established underground artists (say, “Lord Finesse” or “Kool G Rap”), and then you have the really really underground guys like “Mr. Low Kash ‘n Da Sh…

I hate the fact there is no diversity in recommendation algos. We need to bring back Yahoo style top-down directories recommendations and not just a blackbox. But you can find good channels on youtube using tags like "#some3" and "#some2" and so on.

(I deeply hate TikTok)

TikTok's recommendation algorithm is probably one of the best. It puts content first, giving what seems only a passing weight to follower count.

That doesn't mean that having a big follower count doesn't increase you chance to go viral and gain a lot of views, but it is much more likely for great content from a small creator to go viral, than mediocre content from someone with 500.000 followers.

You can also see this in that successful TikTok profiles often have a much higher view-to-follower ratio than something like YouTube.

Re: Hi everyone yes, I left OpenAI yesterday

#408

It seems like he (re)joined OpenAI almost exactly 1 year ago: https://twitter.com/karpathy/status/1623476659369443328

New theory: Karpathy was short on money, so he waited exactly 1 year to vest 25% of his options.

Short on money after being an exec at tesla during a huge rise in its stocks? More likely he has too much money and maybe doesn't really want or need to work and is doing passion projects instead

Re: Hi everyone yes, I left OpenAI yesterday

#409

Let me say, he's a great teacher! I took a CV class with him. He should teach more, and take it seriously. Being a popular AI influencer is not necessarily correlated with being a good researcher though. And I would argue there is a strong indication that it is negatively correlated with being a good business leader / founder. Here's to hoping he chills out and goes back to the sorely needed lost art of explaining co…

>He should teach more, and take it seriously. if only we compensated that knowledge properly. Youtube seems to come the closest, but Youtube educators also show how much time you have to spend attracting views instead of teaching expertise. > It makes you a target for offers and opportunities because of your name/influence, but not necessarily because of your underlying "best fit" That's unfortunately life in a nutsh…

> Youtube seems to come the closest, but Youtube educators also show how much time you have to spend attracting views instead of teaching expertise.

Actually for all the attention that the top Youtubers get (in terms of revenue), the reality is that it's going to be impossible to replace teaching income with popular Youtube videos alone.

Based on what I've seen, 1 million video views on Youtube gets you something like $5-10K. And that's with a primarily US audience that has the higher CPM / RPM. So your channel(s) would need to get to about 6 million views per year, primarily US driven, in order to get to earning a median US wage.

Re: Hi everyone yes, I left OpenAI yesterday

#410
post #189

Earlier quoted context omitted.

That’s the correct answer. Years ago I worked on inference efficiency on edge hardware at a startup. Time after time I saw that users vastly prefer slower, but more accurate and robust systems. Put succinctly: nobody cares how quick a model is if it doesn’t do a good job. Another thing I discovered is it can be very difficult to convince software engineers of this obvious fact.

Having spent time on edge compute projects. This. Also, all the evidence is in this thread. Clearly people unhappy with wasting time on LLMs, when the time that was wasted was the result of obviously bad output.

People think LLM are all or nothing, like it’s either god-like AGI or it’s useless “hallucinating”.

In reality you have to know the strengths and weaknesses of any tool, and small/fast LLM can do a tremendous amount within a fixed scope. The people at Mistral get this.

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