I think there's a real moment of fear

which is like is this a tool we have

built or a creature we have built what

is what is that going to mean like four

times now in the history of openi the

the most recent time was just in the

last couple of weeks I've gotten to be

in the room um when we sort of like push

the front the sort of the veil of

ignorance back and the frontier of

Discovery forward and getting to do that

is like the professional honor of a

lifetime and as AI continues to make

progress as technology continues to

advance as more and more people see what

AI can do and where it is headed towards

then it will become clear just how

dramatic incredible and almost

Fantastical AGI is going to be and how

much trepidation is appropriate all

right this is going to be a bit weird so

the open Saga is coming to an end Sam

Alman is back it seems that Ilia sover

is happy at how everything worked out

but there's still a question what did

ilas see this is a very rational

straightforward very ordered very smart

individual it seems to have briefly went

nuts what triggered that even Elon Musk

wants to know what is this thing they're

talking about we'll come back to this

thing in just a second first a little

bit of background a number of months

back Sam Altman on Reddit through an

account that he doesn't really use

resurrects his account and says AGI has

been achieved internally everyone loses

their minds what does that mean now he

edits that saying I was just kidding if

we did achieve AGI we would not announce

some random Reddit post but by that time

more and more people are talking about

some discovery that was made inside of

open AI here's a video of Sam Alman

saying talking about AI is this a tool

we've built or a creature months before

this a lot of people have hinted at the

fact that GPT 5 has been already cooked

up at open Ai and it is Agi it is much

more powerful than than we've expected

we've hit that exponential vertical jump

and we're we're there so no one's

confirming anything but a lot of people

that are on the inside they're talking

as if this AGI this next level

artificial intelligence is just around

the corner not 10 20 30 years in the

future like it's here and it's going to

be rolling out soon get ready but for

the longest time we didn't have a name

for it nor do we have any details there

was just some rumors that were spreading

around the campfire I've mentioned it

here and there but there was just

nothing to really talk about other than

idle rumors but now it seems that maybe

potentially a lot of the insanity that

happened with open AI firing off Sam

Alman that talks about safety trying to

dissolve open AI 90 billion company

that's valued of 90 billion all this

Insanity that's going on could it have

been because of this discovery could

this incredible breakthrough could it

have triggered it it looks like because

of the stuff that was happening a lot of

information was leaked many sources were

going to journalists trying to get the

word out there and we finally have a

name and we finally have some details

the name in seams is qar open AI made an

AI breakthrough before Altman firing

stoking cment and concern Mr Elon Musk

asking what does this letter referred to

this is what he's talking about

exclusive open a ey researchers warned

Board of AI breakthrough ahead of CEO

aler sources say so here's siki Chan so

he's kind of an silicon valy Insider so

this is from March 26 A lot of these

rumors have been floating around for

quite a while so he's saying I have been

told that GPT 5 is scheduled to complete

training this December and that opening

I expects it to achieve AGI this is a

suweet from earlier today now that this

Q star stuff is coming out he's saying

what this means is that within 3 years

you'll either be dead or have a God as a

servant by the way subscribing to this

channel increases your chance of being

in the second category by as much as 12

a half% so make sure you do that don't

forget but something that's important to

understand is that what we're seeing

what's available to us it's kind of like

light from distant galaxies what we're

seeing well that's from a long long time

ago so we're playing with gbt 4 and we

just got Vision well that was completed

back in I mean sometime in 2022 probably

we're just seeing it now seems like they

were working on GPT 5 as early as March

and saying it was going to be completed

in well right around now here's Mustafa

seliman so he is the co-founder of De

mine and so he now runs uh inflection Ai

and so they're training a model that

they're saying it'll be 100 times larger

than GPT 4 so thinking about GPT 4

they're beginning to train something

that's 100 times larger so that's

important to kind of get your mind

around is that the stuff that people are

working on the stuff that people are

going towards it's not you know they're

not try they're not shooting for like

50% better or 100% better they're

shooting for 100 times bigger more

capable and openi has been working on

something for for a very long time

that's beyond gp4 one of the quick

points you understand is this is this is

a Microsoft paper that just came out

recently 18th of November I have a video

that's done about this it's not up yet

as soon as I get a chance I will publish

it but really fast here's what it's

saying and it's important number one AI

models like gbt 4 can produce synthetic

data meaning they can produce text that

then can be used to train other AI

models now before there was this

question are we going to run out of high

quality human generated data and the

potential solution to that would be to

have these AI models provide synthetic

data so provide data so kind of make up

dream up data to train the next version

of models a lot of people said that

would be impossible there would be these

mistakes that kind of cumulatively would

corrupt the whole process everything

would fall apart that would never work

but here they're saying that GPT 4 for

example can produce better data than

humans can for training these other

models our study has demonstrated

improving the reasoning capabilities of

smaller language models is not only

possible but also obtainable through

training on tailored synthe synthetic

data and these smaller models trained on

synthetic data very specific tailored

handcrafted if you will Artisan

synthetic data they beat out models that

are five to 10 times larger especially

on zero shot reasoning tasks meaning on

on solving problems they haven't

encountered before so you don't have to

give them examples about how to solve a

problem you give them the problem and

they just solve it so in other words you

can think of it as like all of the human

data that we've ever produced all the

pictures and text and books and tweets

and whatever that had kind of Spun up

the first AI model the first good AI

model gbt 4 cleared a certain threshold

it seems and now it can produce better

data for training the future models

which clears that sort of block of us

not having enough data because it can

create an infinite amount of data so

that you know potential roadblock of us

running out of data that's gone at least

again this is what this Microsoft

research is showing so here's the CEO of

Abacus AI xaws gooogle as suspect openi

invented a way to overcome training data

limitations with synthetic data when

trained with enough examples models

begin to generalized nicely great news

for open source and decentralized AI we

are no longer beholden to the data Rich

companies and again while what they're

talking about here is that you know

opening eyes was able to overcome it

using synthetic data well this is not

confirmed the fact that Microsoft is

putting out an open-sourced model that

proves that this is possible and that

those models are 5 to 10 10 times or

rather they're as good as models that

are 5 to 10 times larger here are those

charts so basically like the first and

second chart the first and second bar in

every single one of these charts that's

the Orca two one is a 7 billion that was

13 billion and that was train on

synthetic data how they did is actually

very clever and the paper dives into

that again give me a day or two this

will be out but the point is we're kind

of already at a point where we're not

creating the next generation of AI

models AI is kind of creating the next

generation of AI models like we're kind

of Crossing that threshold it seems and

the reason why I'm telling you those

things is just to as as you read this

understand that while a lot of the stuff

that they talk about here is hearsay

like sources said this people said that

we know that there's open source models

out there that are doing it so we know

this is based on something we know that

the the capabilities they're talking

about is very very real and keep in mind

open AI had the smartest people in AI

that were working on this for quite a

while so in other words while some of

the stuff might be not accurate I would

not dismiss it as nonsense very likely

that there's a lot of truth to this all

right so before Sam Alman gets kicked

out and is resurrected on the third day

so before all that crazy stuff happened

several staff researchers wrote a letter

to the board of directors warning of a

powerful artificial intelligence

discovery that they said could threaten

Humanity two people familiar with the

matter told Reuters and so what follows

is them saying all these people declin

to Comet the person that wrote the

letter declined to Comet the staff

declined to comment the board declined

to Comet but we know that in internal

message to staffers they're talking

about this project they're referring to

it as qar some at open ey believe that

qar pronounced qar could be a

breakthrough in the startup search for

what's known as artificial general

intelligence AGI at open AI they kind of

Define AGI because there isn't a one

agreed upon definition but they're

saying once they make an AI that is just

better at humans at most commercial

tasks like if you've seen that show The

Office like once you can fire Michael

and Oscar and Angela and Jim and Dwight

and all of them and just have Shad GPT

takeover well that's AI though only

performing math on a level of grade

school students acing such tests made

researchers very optimistic about Q

star's future success the sources said

that sentence kind of made me stop in my

tracks and here's why most people that

aren't really following up on AI and

what's happening with it they have kind

of this vague idea what what what it's

about but they probably can't really

describe what the difference is between

like the old school logic based

computers and calculators and AI like

how is it different what's the thing

that makes it different most people are

used to this idea that computers can do

incredible stuff right they can do they

can land spaceships and do various

Advanced calculations and all sorts of

stuff when you tell people you know

computer this incredible thing that

humans can't do people kind of go yeah I

get it I believe it so it's hard to

understand for people when you know we

have this a guy that comes out and

they're like well what can it do can it

right can it solve cancer it can create

new technologies like well no it can

like write a poem it can do math on a at

the level of a grade school student so

it doesn't seem like that advanced but

the point is that previously everything

that computers have done it was because

a smart human a smart engineer coded

that functionality letter by letter by

letter right they sat there and they

coded it and if they were smart enough

to create that code then the computer

would do the thing AI these neural Nets

completely different story and this is

what a lot of people just talking to

most people out there smart people but

who aren't in that are not following the

research this is what they don't get

that this AI we're talking about we're

not coding it we're not telling them

what to do we're we're creating a brain

a digital brain so when it figures out

how to do something simple but it

figures it out on its own that is

mindblowing so what's interesting to me

about this thing where it says well it's

only performing math on a level of grade

school students this true to me because

if somebody was making it up because

they wanted to convince the vast

majority of the people that something

was something crazy was happening inside

they would say it did something that was

astonishing right it figured out how to

travel faster than light or whatever

this Rings true because the

accomplishment is so simple researchers

consider math to be a frontier of Jar of

AI development currently J of AI is good

at writing and language translation by

statistically predicting next word and

answers to the same question can vary

widely but Conquering the ability to do

math where there's only one right answer

implies AI would have greater reasoning

capabilities resembling human

intelligence unlike a calculator that

can solve a limited number of operations

AI can generalize learn and comprehend

and so that famous clip that recently

has been making the rounds of Sam Alman

saying four times now in the history of

open AI the most recent time was just in

the last couple of weeks I've gotten to

be in the room where we sort of push the

veil of ignorance back and the frontier

of Discovery forward and getting to do

that is the professional honor of a

lifetime a day later the board fired

Alman so when people are asking what did

Ilia C to shake him up so much to get

him to take such drastic actions putting

the entire opening eye at risk the thing

that he's been working so hard on what

did he see that rattled him so much and

that's what Elon Musk is asking what

does this letter refer to the letter

that we just read about the employees

that saying hey we've discovered this

groundbreaking thing what does that

letter what what is it talking about so

here's uh the information and it's

saying a lot of the same thing but a

demo of the model circulated with an

opening eye in recent weeks and the pace

of development alarmed some researchers

focused on AI safety in the month

following the Breakthrough sver appears

to have had reservations about the

technology he formed a team dedicated to

limiting threats from this Ai and on its

web page the team says while

superintelligence seems far off now we

believe it could arrive this decade now

the warning there is important cuz

they're not saying a GI will be here

this decade they're saying super

intelligence so super intelligence in

general we see that as sort of The Next

Step Beyond AGI so we have ai artificial

intelligence AGI artificial general

intelligence so basically reaches the

you know at least as smart as humans

right and the Step Beyond that is ASI

artificial super intelligence and it's

that idea of this Godlike entity vastly

smarter than any single human being that

they're saying I could arrive this

decade are you a little bit scared all

right so that's cool but what is this Q

star is there some hint as to what it is

is just a code name could be related to

something well there's a few potential

theories here's stepen mcleer postto at

CMU researching Foundation models for

decision-making he's saying we invented

qar first glad opening eyes building on

top of our idea later he said guys this

was just a joke I don't know what

opening IQ star is you musk jumps in

says Schmid Huber Ed everything

apparently there's this AI computer

scientist Jurgen Schmid Huber who claims

to have invented basically most of the

stuff related to neural Nets and deep

learning he wrote a scathing 2015

article arguing that Hinton Benjo and

Lon heavily cite each other but failed

to credit the Pioneers in in this field

and then in a statement to New York

Times Yan laon wrote that urgen is

manically obsessed with recognition

keeps claiming credit he doesn't deserve

for many many things as AI improves its

ability to write and especially generate

music I think one thing that that would

really help a lot of us kind of follow

some of the stuff a little bit better is

if these researchers would use AI to

create dis tracks similar to rappers how

they create dist tracks to kind of go

back and forth with each other like

instead of writing articles and talking

and making statements to New York Times

just jot down some ideas give it to J

GPT how it create lyrics put that into

some sort of music generator generate a

diss track publish it I think we can all

agree that would be the better way to go

just a thought but back to what we're

talking about one last thing by siki

chin so basically GP 5 turned out more

powerful than anyone expected IIA gets

spooked R Putin's the board which is

have a like good sir that was excellent

excellent Russ Putin's the that's that's

perfect thank you board fire Sam the

clumsiest way possible every VC plus

Microsoft turns the screws staff revolts

board capitulates like tissue paper Sam

and Greg back by Sunday noon Rasputin's

the board this is excellent thank you

but what is qar so there's a few

different sort of ways that people are

thinking about it what it could

potentially be so it might be something

that is related to Something in machine

learning and AI that we already know

about so there is Q learning in machine

learning we covered it a little bit in

in one of the previous videos about AI

learning to play Pokemon so some people

believe it has something to do with that

so basically when we're training AI we

have certain rewards for it whenever it

does something that we like we give it

an adoy often times there's a lot of

different rewards as in for example you

know if you're playing chess there's a

lot of different things you can do to

win you can get rewards from taking a

piece from an opponent or creating a

better board position or or a million

other things and so if you think of it

uh from that perspective so qar is the

ideal scenario it represents the perfect

knowledge of all the best action to take

in every possible state to achieve the

highest reward so it's kind of like

thinking you know as you go through life

and you have a lot of decisions to make

you automatically you just know you know

qar would be you knowing exactly which

decisions lead to the best outcome if

you've played chess in the last you know

whatever 5 years you know that there are

the suggested moves nowadays made by you

know by AI that shows you like well this

is the best move the best move possible

and then this is what you did this is

not the best move possible right so qar

would be this is the best possible move

to make and then Q learning on the other

hand is the method used to approximate

qar it's a learning process where the

agent interacts with its environment

receives feedback in terms of Rewards or

penalties and updates its CU values

based on that feedback so basically the

agent the AI initially has no clue what

actions lead to the best outcomes over

time as it learns more and more it has a

better idea of which of its actions lead

to the best outcomes so you can think of

it over time its ability to predict the

best action gets closer and closer to

that perfect state of knowing the exact

best move to make in any given scenario

what's interesting to me is that this

often this kind of reminds me of how

humans are when we're kids versus when

we're old when we're kids we have no

idea what actions lead to you know what

we want to happen we make stupid

mistakes we don't know what we're

supposed to do so we do a lot of

different stuff sometimes randomly and

slowly over time start accumulating

knowledge and experience and over time

right over time as we learn more and

more sort of our range of things that we

do sort of Narrows we kind of know the

few potential actions we can take to get

us closer to that goal and when we're

old it's kind of like that Other Extreme

like this is this is the only way to do

it this is the best way there's there's

no other way you know how I mean this is

generalizing but sometimes older people

like they're just like no there's just

one right way to do this thing and

there's zero other ways of doing it so

over time they think that they

understand right that qar the best

possible thing to get the highest

possible reward and they're not willing

to look at any other options whereas a

kid is like I don't know there's a

million things we can do so put another

way Q would be the optimal set of

choices to make and a specific game of

chess and the Q learning so that's like

the method in machine learning that's

what's referred to Q learning that's the

method by which those choices were

discovered so it's kind of like it's

kind of like gaining experience in

figuring out what are good things to do

what are bad things to do but for AI

then there's Greg Brockman talking about

Fro i' I'm not familiar with this so I'm

guessing it's this little fra character

here the frog or is it frogue frog I

don't know emoji on an open AI employees

laptop is an unofficial IAL company

mascot I I did not know this so Jimmy

apples jumps in here saying Q frog so

some people are posting that you know

here's a person whose team put an llm

inside a deep Q learning agent in 2019

started playing with AAR like planning

with llms last year here's a person

saying looks like opening ey cracked

generalized agents as expected I mean

it's not that hard process called qar

where Q is a nod towards Q learning

which is what we just talked about and

the star for generalization makes sense

this would spoop the board if Sam plan

to release this into the wild with GPT

version 2 El mus quips qar aan which I

guess that was I think that was a thing

in 2020 the politically related thing

I'm not going down that rabbit hole but

it's confusing cuz like how many things

how many things can QB I mean here's

another one cute the latest post by Elon

excerpt from a book it just says true

here's the thing that he linked to the

bitter Lesson by Rich suton March 13th

2019 talking about Ai and learning I

think the point is that the bitter

lesson is that AI advance ment often

comes not from Human Centric methods but

from scaling computation search and

learning and certainly I think this

makes sense here a lot of the stuff

that's happening right now seems to

point to the fact that AIS are now

making the data to train future AI if

qar is referring to Q learning then

we're taking what we've built what we've

built what open ey has built what

Humanity has built with something like

GPT 4 and we're letting it now go and

explore on itself to learn out itself

what of the best approaches so instead

of human reinforced learning you know

giving it thumbs up thumbs down we're

saying you know what you figure out we

have the compute we have the Nvidia

chips we have billions of azure credits

you figure out how to do it using Q

learning anyways it's like 2: in the

morning I'm getting tired and loopy but

man this was interesting and I can't

wait to see what comes next I guess

there's always a chance this is oh just

fugazi fugazi is just a head fake but it

doesn't feel like it it feels that it's

aligned with a lot of the other stuff

that we're seeing it feels aligned with

the Microsoft research with Orca 2 it

makes sense in light of all the

craziness that has happened what will

cause ilas s to Rasputin the board I

can't get over that you know he saw

something something spooked him I've

said this before but what are the

chances that we are alive just as all of

this is happening and we have a way to

see it we have a way to interact with it

either we are living through the this

particular time Against All Odds or this

is all assimilation and is just kind of

unfolding according to plan either way

I'm excited my name is <PRESIDIO_ANONYMIZED_PERSON> and

thank you for watching
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