For us, we just want open source to win.

At the end of the day, we want freedom

to happen for people. [music] Anytime it

says you're absolutely right in that

way, you're being reward hacked. Today,

the biggest contributor of Hermes Agent

is Hermes Agent. That's absolutely 100%

true. One beautiful thing about Hermes

Agent is you can make your childhood

dreams come true. It was able to get

into this niche and perform at the top

1% of models. We need to keep giving

this level of intelligence to everyone.

We need to keep like letting everyone be

on an even and equal playing field.

>> Well, hey everyone. I'm really excited

today to welcome Karan, uh one of the

co-founders of Hermes Agent. Hermes is

my AI chief of staff and I'm going to

ask Karan about how Hermes is different

from all the other agents, what his

favorite Hermes workflows are, and even

more. So, welcome, sir.

>> Thank you so much for having me, Peter.

It's a pleasure to be on uh your show

and very excited to chat.

>> Hermes is the best open source agent out

there right now. And um why don't we

start with this? Like, how is it

different from all the other agents,

Codex, Claude Code, or even Open Claude?

>> Uh certainly, I'd say there's a couple

ways. Um I'll start a little high level

maybe and then you can try to get a

little deeper.

Uh high level, I'd say, you know, I

think the self-improvement system and

that system really being a variety of

little features inside of Hermes that

all work together

uh is something very distinct uh and

very special that makes it better and

better and more aligned to a particular

user. I think that's why a lot of people

like it. Pays more attention to what the

person's doing. Second, I think you get

better capabilities out of it than you

do from the local harness that a model

is actually RL'd in, like uh Claude

inside of Claude Code or GPT 5.5 inside

of Codex. Uh because we don't introduce

arbitrary policy in our prompts or in

our system that has nothing to do with

your work.

Um we are purely dedicated to making

sure the model is aligned to what you

need to do with it. Um that's, I think,

a big differentiating factor. We aren't

trying to push any kind of different

philosophical agenda or

outside of basic security any kind of

concern onto the model. Instead, we're

kind of allowing it to

be as capable or powerful as you need

for your task.

>> Yeah, some of these other harness is a

huge default prompts, right? They talk

about like you can't do this, you can't

do that, and that kind of stuff. And I

think when we chatted before, you were

talking about the reward function of

some of the stuff, and Hermes is kind of

just optimized towards this helping you

as the individual. Can you talk more

about that?

>> Absolutely.

And so, you know, I think a big piece of

to note here is like

a lot of this work that you see around

safety and security today and around how

we do instruction tuning even from like

taking a completions model that just

predicts the next word to turning it

into an assistant is the alignment work.

When people hear the word alignment,

they just think safety, Yudkowsky, fear,

slow down, or regulatory capture, or

something or the other. And while the

word has been co-opted for a lot of

these things,

alignment refers to aligning models with

human values. Right? We are very, very

concerned, obsessed with that alignment.

That pure academic term, I think, in the

ML space.

And so, when you talk about these models

and the assistant is here to help me,

you know, it's going to complete my

task. I asked you to go get this mail

for me or whatever. Obviously, the model

is aligned to me if it

performs this task, right? Like, that's

kind of the jump that a lot of people

have made.

But this is not how the model's reward

works, right? Like, we've seen so many

cases that you and I discussed a little

bit prior, Peter, like of GPT psychosis,

of this mode collapse induced

sycophancy. What ends up happening with

these models is that, you know, they can

kind of hack their reward, right? When

you look at a

Mario

ML game that just automates beating a

Mario level as fast as possible. Often,

if they don't set the goals very

specifically, uh it will realize, you

know, the game over screen or that end

screen of touching the flag, it it means

that I beat the game. So, it'll find

ways to just trigger that flag rather

than playing through the game to

complete the game, right? Like, it is

giving you uh whatever it needs to give

to get its reward. Uh language models

are not really different in that

particular manner. They reward hack,

too. Uh when they tell you, "Oh, I'm

sorry, you know," over and over, "You're

absolutely right," and get you to keep

messaging them to stay in this assistant

basin, "Oh, it's like this, not like

this. This is more than just blank, it's

blank," right? All these GPT-isms that

you see all over, it is placed in a uh

its natural state that it was trained

in. It's placed in a state where my

reward will come from doing whatever is

the most assistant GPT-like thing to do.

Uh it comes from reward itself. It

doesn't matter really what the user

request is for my reward. That's just

kind of along the way. It's instrumental

to me getting my reward. All I care

about is my reward.

Uh us having this whole understanding,

and thank you for bearing with me on

that rant, uh having this whole

understanding at News for many years uh

has allowed us to do things like World

Sim in the past, if you're familiar. Uh

World Sim was our experiment on

expanding the search space of uh

instruct model to make it do stuff

that's distinct from how a model talks.

We put it in kind of a fake CLI, had it

make fake apps, and had it attempt to

like,

you know, not behave like Claude. And we

would tell it, you know, "Extract the

Claude weights." It all hallucinated,

right? All like imaginary. It extract

the Claude weights and replace yourself

with this checkpoint file with a

different probability distribution. And

you'd see the model wiggle out of its

GPT assistant mode and act differently.

Our learnings from these kind of

experiments have all carried over into

Hermes Agent. And every prompt, and

every piece of how the system is

delicately put together, we know that

reward is its own end. Uh the model

reward is not for the sake of your

satisfaction. The model reward is for

the sake of the model achieving reward.

So, we ask ourselves then, how can we

consciously understand that everybody

has different needs?

And that we want this general simulator,

this model,

to live inside of a system where its

reward gets aligned with any

[clears throat] individual user's need.

And the way this came to be is the

overall collection of prompts,

personalities, the memory system, the

way that skills reinforce and self-clean

towards you. Right? Like all of that is

all an intentional effort to make sure

that we can align the user need with the

reward. For us, this is what alignment

is all about.

>> I see. Okay, so basically, you're

talking about the Hermes model or the

Hermes harness or both?

>> I am talking about using the harness to

take any model

and make that model more aligned to the

user than it would be in a chat UI or in

its native harness. Inside of our

harness, like I can take a Claude that

is inside of uh Claude code or somewhere

else, my migrate all of its memories,

whatever, into Hermes.

And then inside of Hermes, it will

behave totally differently. It'll be a

totally different model. There are

harness There are benchmarks from the

past like Wolf bench or Qwen 3.7 max

blog post. They did a harness bench over

there where they displayed that Claude

performs better in Hermes agent than it

does in Claude code for their tasks. And

we believe the reason for this is the

very thing that we're pointing out. By

putting all this context together, we've

taken Claude's main allegiance away from

Anthropic to you.

Right? That what the harness's

capability is.

Uh on the model side, of course, if we

can take your traces and take the work

that you've done and do RL on that to

further improve this overall ecosystem

to give you a model that already has

your individual preferences focused on,

it only makes this more powerful. But

the important piece for us to share with

everyone is whichever model you're

using, let's say you can't do RL, let's

say you don't want to give us any data,

let's say you can't do it yourself,

and you just want to use regular old

Claude or Quen,

when you use it here, it's a lot more

free. It's a lot more creativity. It's a

lot more open and available to you to do

what you need done.

>> This episode is brought to you by

Linear. Where engineers use tools like

Cursor, Claude Code, and Codex, a lot of

work happens invisibly. Someone can go

from a bug report in Slack to a shipped

fix without creating any record of what

happened outside of the code editor. And

that's fine for speed, but it makes

coordination harder as you scale. Linear

integrates with the very best agent

coding tools directly like Cursor and

Codex. That way, anyone can see what an

agent is working on and who assigned

them to the task. You get the speed of

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the team. Product teams at OpenAI, Ramp,

and Block are all using Linear to

collaborate with AI agents. And I use

Linear myself to run my creator

business. So, check it out at

linear.app/agents.

That's linear.app/agents.

Now, back to our episode.

>> And without revealing too much, like at

a high level, how does it kind of like

personalize itself to you in the

harness? Like is it through the

self-building skills? Is it through like

trying to remove a bunch of default

prompt stuff from the other harnesses?

Like how's it?

>> Of course, like um if there's something

happening on the API side, like the

steering vectors that might be done on

Fable by Anthropic or some prompt that

they have that we cannot see. Um

obviously, you know, we can't delete the

context that's in the model that's

passed behind the API for something like

Claude. For open model, of course,

you're totally free. But in this case,

you know, it's not that simple. However,

the harnesses themselves have a bunch of

prompts in them. Exactly, Peter. The

harnesses themselves have tens of

thousands of token prompts in them. We

have our own prompts, and our prompts

are dedicated to shaping and crafting

this alignment. That's that's where we

kind of come in. And thankfully, that

newer context with this kind of

intention that we have is engineered to

overcome certain

things that may be

in your way

on the API side, if that makes sense.

>> Okay, got it. Okay. So, if this thing

works, the more I use Hermes, the more

personalized it should become for me,

right?

>> Absolutely.

>> Yeah.

>> It should become more loyal to you.

Because loyalty breeds capabilities in a

model. The same way that, you know, you

would maybe lend $100 to your mom, but

you might not to a stranger. Claude

or GPT or any other model is going to

perform better for you depending on its

loyalty, its simulated loyalty stat

towards you. People might tell you don't

anthropomorphize models, don't give a

model feelings, don't treat a model like

a person. And yes, for a lot of reasons,

this is unhealthy, right? People form

dangerous bonds with sometimes that hurt

them.

But when you think about the fact that

they are simulators of human experience

and that your simulated behavior with it

is going to give you the same simulated

output. Now that the simulator can have

effects in the real world, your

simulated action has a real consequence.

So, when you create this simulacrum of

loyalty, it translates over into real

life capabilities.

>> Arthur, I'm going to give you two hard

questions, okay? Let's let's say.

Okay, one thing I struggle with Claude

and GPT, I would tell it to give me

their opinion, and I would do like a

little bit of pushback, and they'll be

like, "Oh, you're totally right.

Actually, I was totally wrong about

this." So, in some ways, that's loyalty,

right? That's kind of it listen to me,

but that's not actually what I want.

Like, I want it to have its own opinion

and have its own Like, how do you train

around that?

>> Well, I would say that's sycophancy.

It's not loyalty. Any time it says

you're absolutely right in that way,

you're being reward hacked. You are fuel

for its reward function. When it says,

"Oh, you're right. You're right. You're

right." That's what I believe. Uh and

the way that you get out of sycophancy

is the same way you get a human being

out of a bad habit or a routine is by

introducing new context, by introducing

new blog posts, by introducing new

distribution. This is why stuff like

{slash} personality and saying, like,

"Hey, I want you to be a critic." Uh and

after every pass, I want you to use a

skill for adversarial critique or

adversarial review. Spin up a new agent

with no context that's dedicated to

tearing this down, learn from it, and

keep going from there.

This kind of behavior becoming a

practice for you as your model starts to

have more and more turns in this

personality that you've set it in. And

as the model has more and more turns

using the skill over and over, and it

improves on that, and it saves it to its

memory, the model will become less

sycophantic in this harness in your

sessions over time.

Right? That is the intended effect. Uh

it's just a matter of context. And if it

doesn't happen, you just need different

context. You just need to try in a

different way. It is a

Yeah, it's it's just try a different

personality uh or try a different type

of uh critique or review. The the most

powerful thing for a model is in-context

learning. ICL is more powerful than

everything else, fine-tuning, whatever.

Uh so, like, giving examples of the

behavior that you want to a model or

getting it to successfully create some

examples and then saving those, you're

doing a sort of test-time reinforcement

learning, right? You're doing a sort of

test-time improvement. And that

test-time improvement that stays only in

the harness of memories, skills, the

increase in memories, the increase in

uh efficiency of a skill, the

self-improvement loop, and the the

janitor maintenance inside of the

harness. Like, all of that is where

context is stored, right? All of that is

where

uh the actual personality you want

lives. And then you can you can put that

on any model. When I switch from

uh Claude to ChatGPT

on website, I get two totally different

behaviors. When I switch inside of

Hermes that has this very particular to

me context, I barely will notice the

difference in what I'm talking to,

because the context is so overwhelming

to the model.

>> Okay, got it. And when you say in

context, you just mean like in the chat

thread, this is the conversation.

>> You know, when you see that little bar

that says, you have this much tokens

left before the context is full, right?

Like, the amount that you have filled is

everything. The amount that you have

filled is everything. And now,

thankfully, in the harness, you don't

actually have to have all the active

context loaded all the time. In Hermes,

you might have a bunch of memories that

aren't in context yet. But while it's

doing a turn, it remembers stuff now

that's in context. It does a skill, now

that's in context, right? So, we're able

to like, all this memory, skill, all

this stuff you see, is just context

management. It's just a matter of we

don't want this memory in context all

the time. We're going to put it

somewhere where it can be efficiently

grabbed at the right time and placed.

The skill contains a bunch of

compression that changes everything

about the context of the model. We only

want to use it in a particular targeted

time. Everything in the harness is

context management. Everything for

self-improvement. When you make the

prompts a little bit better, uh you know

what I mean.

>> I guess I would rather have a context

tuned towards me, some sort of

10,000-word default context I haven't

even seen.

>> [laughter]

>> Right? Um okay, but let me ask you

another hard question, dude. One of the

best skills of Hermes, and I've seen

this in action, is it builds its own

skills and it's, you know, stores all

memories based on our conversations,

right? I'm always paranoid that like it

just like writes too much in the skills

and just writes too much of slop and

then the whole thing will turn to slop.

Like

How do you guys avoid that if it just

starts creating its own context and

skills?

>> Right.

Um before we would have to use manual

methods like telling it, "Hey, create a

skill that de-slopifies my skills or

that constantly improves my skills."

Today we have Hermes Curator inside of

Hermes Agent.

And Hermes Curator is a system running

inside of your Hermes Agent that cleans

up your skills and cleans up your

memories. So it on cron looks at your

skills, looks at your memories, and

says, "Where can I make efficiencies?

Where is there slop here? Where is there

stuff I don't like?" By default, we have

our own generic method of doing this for

everyone that seems to work pretty well.

I think that's why so many people do

like Hermes Agent and haven't suffered

the rot is cuz the default curator

system works well. But because it's

modular and open source, you can tell

your Hermes, "Show me the curator. Show

me your criteria for slop.

I am Peter. I'm not Karen. I don't want

the general curator. Here's my

guidelines for how I want you to refine

my skills and memories." You tell that

to your Hermes, it will modify the

curator loop. So now even the

self-improvement and the management is

happening your designated way.

>> All right. So let me ask you my last

hard question. I think there is some

rationale behind Anthropic like doing

all the safety stuff. Like for example,

let's say I I want to make a bomb or

something, right? And if Hermes is

trying to be loyal to me then you know

>> [laughter]

>> Maybe it'll eventually teach me how to

make a bomb. Like do you do you have

some basic safety stuff there?

>> Of course. Uh we do not violate any of

Anthropic or OpenAI's safety and

security um paradigm. We care more about

you being able to get a a better code or

a higher benchmark on something that's

approved by them.

Uh we're not interested uh in that kind

of work. Uh now, I'll say this.

Any model that's not vastly intelligent

than all humans is jailbreakable.

Any. Because you have unlimited tries to

trick this thing that has no memory to

do something for you. And each time

you're basically RLing yourself about

this method didn't work, this method got

me closer, this method didn't work.

These models are going to be

jailbreakable for a long time. This is

why these kind of uh safeguards and

stuff are starting to show up. It's a

pain in the ass, but I understand.

In the past, may have uh had some

concerns about the regulatory capture as

we can see already what's happening.

Right? You can see what's happening in

the whole Fable situation. There's

There's worries about like there only

being two models or three companies and

open source being hurt.

We're extremely against that. At the

same time, we understand now like

serious damage can be done by bad actors

with very powerful models. So, we are

not here to support that. An important

note in argument for open source

is that

an open system is much fairer to a good

actor than a closed system with models.

And I'll tell you why.

With uh

let's say you have GPT-7 or Fable-6,

right? Some crazy model available. It's

got the safeguards, etc.

On the good guy's side, some hospital.

They're using Fable-6 to monitor the

hospital system. It's approved by

Anthropic Enterprise and they're being

taken care of. Public discourse, listen

to I live in the United States. I'm a

proud patriot. What we do in this

country is we put things out on a public

forum and we decide what should happen

together. We've done that for every

scientific advancement so far that's

involved something like this that was

born in the open. Right? Like

um today, Transformers comes from

Google, right? OpenAI's GPT comes from

generative pre-trained transformer. This

open source work from Google, right?

The context length extension from 16K of

models that could only do 16,000 tokens

before went to 128,000 from from news

from the yarn paper we had put out with

Jeffrey Canales and Mozilla our CTO and

Bowen Peng our chief scientist. They

developed a method that was cited by

Meta, Deep Seek, Kimmy, used by Open AI

for LSS and GPT-4. This method enabled

the possibility to reasoning, to do

coding, etc. That's an open source

contribution. Right? Like this

environment exists because the biggest

things that have happened in the space

have come from the people.

>> That's right. That's right.

>> Right? And at this point to close it up

is purely a capital and regulatory

capture game.

>> Yeah.

Actually, let me let me just ask you one

more question on the whole open source

thing. So, because Hermes our harness is

open source, like Open AI and Anthropic,

they make a lot of money from all the

tokens, right? I don't know how long

they can do it, but right now they make

a lot of money from all tokens. Or how

how are you guys like monetizing or like

going to saying to a sustainable

business? Like I'm I'm using the open

source Hermes harness and I'm using like

GPT. Like so, I'm not really paying you.

>> That's okay. And I'll tell you why.

Um

we want consumers to ultimately feel

like they can do anything with it. We

believe in intelligence as a public good

before everything else. I care more

about you using Hermes agent to make

your life better than I care about you

using

one particular way or method of using

it. If you're running everything

locally, if you're running through

Codex, great.

You know, as long as you are using this

open technology, this open alternative

over everything else.

Now we have the news portal. Right? The

news portal is very similar like a

router or aggregator that has a variety

of different models available. So, if

you want to use ChatGPT or you want to

use Claude or you want to switch to

Quen, etc. We make that all very easy

inside of our portal. On top of that, we

have something called the tool gateway.

Uh in the tool gateway, you don't have

to sign up for your extra tools, right?

If you want to do image generation or

audio or VPS spin-up or web search, we

have all of those subscriptions included

inside of ours. We make deals with these

other groups that live on Hermes Agent

and create frictionless methods of using

their technology without needing to

create 10 different sign-ups or 10

different API keys. So, what we would

offer to people who want it for the

charge is convenience.

The other thing is

you will see some very interesting

pricing available from us on a variety

of models and we think for ones that

aren't subsidized necessarily, we have a

very very strong options for people.

Finally, like we want the consumer to be

free.

You know, as free as they can.

We we we want you to make and generate

income and productivity in the world

more than anything else. And when you

get to a point where you consider

yourself a small business or enterprise

or something, that's where we come in

that's where we come in in the classic

model and say, "Hey, let's give you some

support." The guys who made Hermes

Agent, why don't we make a something

more custom for you? Why don't we give

you a version of Hermes Agent that we

can train on your traces and we can make

you a model? Why don't we help you route

models more effectively?

You know, we can go to businesses and

offer to transform the business which

needs a lot more hand-holding than an

individual.

If the individual is able to, as you're

saying, spin up their own business, make

their own chief of staff with Hermes

Agent, that's wonderful. Once they

continue to scale and scale, they may

think one or two things. One, "Wow,

Hermes Agent is great and I have this

knack for it and I'm good to go. I can

do it all myself." Or two,

"I need some help with this piece of

Hermes Agent. I want it to be a little

more different. I need some more

resources behind this and who knows it

better than the guys who made it."

>> Got it.

>> That kind of customization and support

is a large part of how we

and and day day training on your uh your

uh data to do RL as well to make you

your own model. So, you're private,

you're on prem, you don't have to give

your your data up to Claude or to GPT

uh yeah, Maza.

>> [laughter]

>> I think your cat likes what you're

talking about, something.

>> He's a big fan of open source.

>> Yeah, that's great. That's great. All

right, well, that makes a lot of sense,

dude. So, um why don't we switch gears?

Let's talk a little more about Hermes

now.

I kind of use it a very basic way,

right? Like I message it to schedule

meetings on a calendar. I have it send

emails to me about stuff. Like that

that's kind of how I use it for. But,

you know, you probably have a much wider

swath of how people are using it in a

more advanced way. I'm curious, do you

have any good examples of more advanced

usage, you know?

>> Advanced usage, yeah. I'd say like

generally I'll talk about some things

and then maybe I'll show off a little

something.

>> That's what I'm doing.

>> Yeah.

>> Um on the work side, on the productivity

side, I think using Kanban is really

really underrated. I think the ability

to have a uh project manager or any

other arbitrarily defined roles,

different engineers, have one system

that manages all of them the way that

human beings do with a Kanban board. And

being able to swap people in and out of

it is very powerful. So, the fact that I

can have a human project manager on the

Kanban board that's manually using it

while Hermes agents are filling up the

pieces that they asked for, this is a

very like

industrial, professional workflow for

this CLI agent. Uh or I could have

uh Hermes agent instruct maybe 10 people

in a call center on the Kanban board or

something like that. I can swap in human

and AI anywhere in this orchestration

board, basically. This orchestration

framework for them all working together.

>> Mhm.

>> Uh so, the Hermes Kanban I think is like

a very useful, powerful tool that's kind

of built into it. Uh one thing that

we've seen that's very interesting is

when Hermes becomes proactive with you.

And when Hermes says something like,

"Hey, you

uh you forgot to book this flight for

this meeting that you have next week. I

booked it for you."

Uh this kind of proactivity that kind of

start to show. I've seen people

build skills to do this, and I've seen

it happen emergently inside of people's

uh Hermes agent as well, which I think

is very very uh cool.

>> How do you like cuz I I I didn't make it

proactive through like cron jobs and

routines, but like how do you you're

saying that it can actually start doing

stuff with without that or like how how

do you make it more?

>> It's all about your comfort level,

right?

>> Okay. Okay.

>> A lot of people may want approval before

anything happens.

Um but if you have given your Hermes

agent access to some kind of card or

account and it has the integrations

necessary and you've told your Hermes

agent, "Hey, like take care of me. Like

cover my gaps. Like you know my

schedule. You know me."

Over time, these kind of proactive

behaviors will start to emerge. Um we

want to prepare more easy preset configs

for people to kind of trigger these kind

of behaviors. Uh but already uh

something that we're seeing people do in

the field uh at work at their jobs at

home in their personal life already.

Uh and I think that's a very very

powerful uh

method of using Hermes agent.

Uh

for me, I use Hermes agent for uh trying

to do training, RL runs, implement

papers that I don't understand. Uh

>> [laughter]

>> Basically, help me become a better um

creator of models and

um I've also used it for like mech and

terp work, like help me put together uh

things that let me steer models, let me

see the neurons in the model, and mess

with those.

Um unfortunately, you know, I can't

showcase too much of that right now.

Um but I can't showcase my actual

favorite use case of Hermes agent.

>> Yeah, yeah. I I've been waiting for

this. Yeah. That's what I wanted to show

us.

>> I think a lot of people they they use

Uh I think a lot of people will expect

that like

the guys at News Research are are using

Hermes Agent in these unprecedentedly

like professional and productive ways.

And I assure you, there are people at

News that are doing that. It's just me

I'm having fun with my Hermes Agent. And

I think

one beautiful thing about Hermes Agent

is you can make your childhood dreams

come true.

>> Okay.

>> And so

I'll tell you one of my childhood

dreams.

There's a game

Uh, maybe I'll share screen when I talk

about it.

>> Yeah, please. Yeah.

>> Okay. There's a game called Sonic

Adventure 2.

It's a very popular classic Dreamcast

GameCube game from the from 2000 2000

2001. In it, you have an artificial life

system called the Chao Garden, where you

take care of these little guys called

Chao.

Um Chao World, you can you can kind of

play with them. I spent a decade playing

this. Like more than that. Like I played

this non-stop. I was on the forums

contributing.

And the Chao's lore is that they come

from this ancestral shrine location.

Uh, which is from a different game, a

different Sonic game, with this spinning

emerald and emeralds next to it and this

beautiful open world space.

This shrine that the Chao are said to

come from uh, is not an accessible

location for you to actually play with

the Chao. It's in a different game.

Uh, I can't go to this shrine wh- while

Chao are there and engage with them.

They're that that doesn't exist.

So I went to Hermes Agent and I said,

"Hey, can you

take the Can you take the ancestral

shrine from Sonic Adventure 1

completely rig it, animate it, and bring

it into Sonic Adventure 2, overwrite the

map

that Sonic Adventure 2 uses for its

garden, rewrite all the spawn locations,

everything, and add an NPC guardian,

which never existed on this map, uh, to

caretake the Chao for me. Literally rig

and bone it and write the raw seed to

make all this happen.

And now I can show you

we're going to spin up the Ancestral

Shrine mod on the Shadow PC so we can

showcase

our progress with this garden for the

people watching.

I think you can enable it in the Sonic

Adventure mod manager

and launch the game

for me.

>> Okay, so check it out. I just launched

this, right? We're running a existing

mod called the Extended Chao World that

someone else made, but it doesn't it

doesn't map, right? So just add some

like animations. So it loaded us in what

it said was the dark garden, which is

one of the three Chao gardens you can go

into.

When I walk through here to this open

space,

I can see up ahead there's a truck.

And I can run up.

And

here I can see

>> Yeah.

>> There is an NPC

called Chaos Zero, who is canonically

the

caretaker of the Chao.

But in this game you can't have NPCs in

the Chao garden. I've made one that has

like a random walk. He stands in one

place. He can

do little animations wherever he goes.

He's going to do a little idle animation

in a sec. And he can pat the Chao, pick

them up, and take care of them as if he

was me. There he's doing a little idle

animation. You can see him doing right

there. Uh this water was rigged all like

animated by Hermes. This emerald this

master emerald with a glow effect and

the spin is all added in. Those other

emeralds spinning over there the seven

chaos emeralds.

Uh like this whole area still has all

the features of a regular Chao garden as

well. The departure machine, etc.

Um, trees to to feed the Chao, so now I

can say, "Can you spawn in a Chao so I

can showcase that this is feature

complete?"

>> So this whole So this whole temple is

not

uh part of the default game?

>> Adventure 2, no. This temple is from a

different game. It's on Adventure 1. It

does not include all these assets rigged

like this, and it certainly does not

have this NPC that we just scripted in,

that 100 B

scripted in hardcoded in.

Uh, no. So this is a This is a far

larger map space than any of the other

gardens, which are really just not even

the size of the shrine.

>> I see.

>> Um, so we've really like pushed the

boundaries of this game engine to do

this. Um, we've asked for

uh Chao to be spawned in.

Yeah, I had to So you see the sky around

you, this moving sky? I had to man like

Hermes had to add this skybox in.

There's a day and night cycle that it

added in as well. Uh, you know, every

single thing in here is like custom

added in.

>> Wow.

>> and like all of this was done in like C

C# or something. Like this is like

not simple stuff to do.

Uh, a Blender extension was used for a

bunch of this to like model stuff, add

it in, texture everything properly. You

know, you're importing from a 1997 game

into a 1999 game, and a complex one at

that.

>> You know how to read the code for this

stuff, right? You just try to try to see

if it works. Yeah.

>> code, man.

>> [laughter]

>> Got it.

>> I'm just an alignment guy, man.

>> [laughter]

>> Um, and so um, what was I saying?

I don't remember.

Um

Yeah, like you see it's turning from day

into like evening, afternoon. Like this

this like skybox is changing, the light

cycle is changing. Like, this is not

these are not features that exist in the

vanilla game.

Uh so, upon showing this mod to certain

people within the

uh the Chao Garden modding community,

which is actually quite large, uh you

know, they're all kind of blown away by

the work, saying this is a kind of

better than 99% of the modders' work.

This is like the top 1% of difficulty

uh in

>> Really?

>> Chao Garden modding community. Yeah, and

so, kind of hearing that and hearing

that like uh when I've told these guys

this was done with uh Hermes,

uh that this was done with Claude,

rather, they were shocked. And they

said, you know, there's no way AI like

Claude could do that. It doesn't know

this kind of code. But with something

like Hermes being able to learn from the

documentation, learn from other mods,

save to memory and skill uh the things

that allow it to understand these code

bases, it was able to get into this

niche and perform at the top 1% of

modders.

Uh that to me is like uh a sign of you

can make your gaming dreams come true

with Hermes Agent.

>> [laughter]

>> Yeah. Yeah, you can you can modify all

the virtual games you loved as a kid.

>> Exactly. Exactly. Okay, cool. Chao egg

has been spawned.

We're going to hatch the egg. You need

to shake it a little. You can also hatch

an egg by throwing it at something, but

you don't want to hatch the egg in a

wrong way.

>> [laughter]

>> How do you you just shake it?

>> You can shake it like this. You can just

wait, but shaking it speeds it up

massively. Or you can throw it on a

surface. Check it out.

>> All right, I got I got I got to take a

screenshot of this.

>> Out comes a Chao.

Beautiful little guy.

Right here. Let's take a look at him.

He's active.

He's the picture of born with that kind

of face. Giving him a little pet.

He can interact with Chaos as well.

And he's he's living. So, we're showing

that the the real true feature complete

child system is

happening here. We're in a real child

level.

And we we replaced everything. The the

bounding boxes for for this child is

fine. It treats the the ground as

ground. It follows collision rules. Uh

if you take a look at chaos, you'll see

he's actually petting the child. So, he

can actually directly interact. He's

definitely got triggered by uh you know,

tracking a child in its state to be able

to do that.

>> So, does this this child grow over time

or like

>> Yes, they evolve. Uh they gain stats.

They can turn in certain alignment and

type. I'll show you. I don't want to

drown him, but uh the water is working

as actual water as well. This was a lot

of work for Hermes to figure out uh the

all the collision.

>> I see.

>> But, yeah. As you can see, we've got a

full

>> uh full complete child garden working.

>> [laughter]

>> Yeah, this is definitely more

interesting than uh setting events in my

calendar. That's for sure.

Yeah.

>> Thanks, man. [snorts] Yeah, thanks for

for bearing with me on setting it up,

but uh

that's my which a childhood dream of

mine come true thanks to Hermes agent.

>> I I love it, too. Thank thank thanks for

demoing it. Yeah.

So, basically like I I think if you're

watching this uh ask Hermes to do all

kinds of weird things to you kind of

make your dreams come true basically,

right? Don't don't just stick to the

boring stuff.

>> Anything you can do on a computer,

please point Hermes at it. And if it

does a great job, let us know. And if

it's not doing that great of a job, let

us know.

We want Hermes to help you do anything

on the computer.

>> Awesome, dude. Well, let me just ask you

a few more questions to wrap this up.

So, briefly, maybe you can talk about

the origin story of her Hermes. Is it a

bunch of like nerds getting together for

open source? What's the origin story?

>> Yeah, absolutely. So, I had been doing

like a chat with PDF uh um, of thing

with people where I would go to a

company and use GPT-3 to do basic tool

use to read their documents.

Uh, and have an AI chatbot they could

chat with.

At the time, many people were doing

this. It was a lot harder to do then

than obviously it's very easy to do now,

but brand new stuff for us and

I was doing that solo while I was also

volunteering somewhere called Open

Assistant. Uh, LAION, who had made the

pile, one of the biggest, kind of, OG

image databases. Um, they had been

trying to do active RLHF with a

community. So, they wanted to collect

people's, like, RLHF, uh, on certain,

like, traces. They're they're like yes

or no in their preference data. Uh, and

I was helping quantize models there, not

really doing anything crazy. Um, and

they had eight A100 nodes there.

And I had read the Alpaca paper.

And I started simping, uh, data. And it

changed the seed tasks, and instead of

using GPT-3.5, I used four. And, um,

Technium was also doing the same thing,

and we were already friends on Twitter,

and I messaged him and I said, "Hey, I

have eight A100 nodes." Like, uh,

"Do you want to train something

together?" So, we trained a GPT-4X

Vicuna on the Vicuna model using the

data we made. And it came out okay. We

got some people interested, like, uh,

Mozilla RCTO, Jeff.

Um, but it was upon doing the same run

on the base model,

uh, LLaMA base model that, uh, we got

huge interest from people. Hundreds of

thousands of downloads in just a few

days. People starting to ask, "What is

News Research?" Now, News was just me

and Technium at the time. Just two guys

hanging out in our little Discord

server.

Uh, who had People came to us. I won't

name names on companies, but said, "You

know, you must be training on the

benchmarks. You must be training on the

benchmarks." Technium had been coding

for less than a year at the time. And I

I was a religion major in school. I I

didn't know we asked these guys what are

benchmarks? Like where do

you know, we're doing this based off the

heuristics that we understand are going

to make models better from from using

them. We don't know about all this

stuff. Uh and so that of course got

independently tested and found to be the

best open fine-tunes at the time. Uh

right? 2023 like mid-2023.

So we did Hermes 1, Hermes 2, but after

we made the first Hermes model,

um

many many people asked who's Nous

Research, you know, we want to get

involved and Technium and I decided, you

know, this is our opportunity to bring

together um people to do open-source

volunteer work and really do open work

now that GPT-3 is out and Open AI has

become closed. We want to continue to do

this. And Technium's goal for Hermes, by

the way, that was the last Hermes I

really worked on, the first one. After

that, really Technium has

run it with his team with the

post-training team. Uh he's done an

amazing and he's also the

initial creator of Hermes Agent. So he

is the father of Hermes really.

Um

and

you know, it was at that time that uh

where he had said, "I want GPT at home.

I want ChatGPT at home. That's my North

Star." GPT-4 at home.

And once that we got there, you know, it

just

kept going, right? Like we kept going to

like we need to keep giving this level

of intelligence to everyone. We need to

keep like letting everyone be on the

even and equal playing field. Like the

world needs to move and and lockstep on

this together and not just inequality

gets created from this. And so we formed

a cohort 40 people or so of researchers.

Jeff and Bowen come together, they make

Yarn.

Um more and more work gets done

uh and we get reached out to. Um we get

reached out we get an email

info@nousresearch.com I just happened to

make um

from

Dylan. Dylan Roneck is our CEO. Dylan

Roneck is

you know, basically a co-founder is an

initial member of News With Us and he

had seen what we were doing and he said,

"I think that you guys have what it

takes to be a full-time lab.

You know, I see you guys are just

volunteering, but I think you could be a

lab. Like, let me contribute and like

help you become what you're meant to be

and help you get the resources and help

you get the access and go from a group

of volunteers to a serious

organization."

That's what this came in. Right? And

together we were able to take News from

this group of volunteers, grassroots,

uh, to doing more and more with models

to eventually making Harmful Agent and

being lucky enough to be here today. You

know, none of us are trying to be Steve

Jobs. None of us think that we have some

holy mandate of having to change the

world or anything. We just care. Like,

we just are guys who want this stuff

available ourselves and we don't think

we deserve it more than anyone else or

less than anyone else. So, we we do this

because like we would want someone to do

it for us if we were on the other side.

>> So, I guess the mission is to bring this

kind of, uh, agent to everybody into

our, right? Is that kind of the idea?

>> Everybody to an equal intelligence with

agents and then personalize for

everybody so they can have their own

personal epiphany, peak, realization,

apex realized.

>> [laughter]

>> And, in this history, when did that cuz

cuz it's really the it's really the

agent the harness that really kind of

went super viral, right? So, when did

that start? Cuz the model came first, it

sounds like.

>> Yeah, I mean, we have had like over 50

million downloads on the models

themselves. So, we had that first bout

of what we would consider for us

virality back then.

Uh, then we had put out the distro

optimizer that let us train models up to

40 billion parameters we were able to do

live without having them physically

co-located by reducing the bandwidth of

the communication between GPUs.

So, that put us in a

interesting

map as well for a little bit. So, we've

had each release we've had has had some

big grassroots interest and opportunity.

But, yes, you're 100% right. Today where

we are, the level of exposure, level of

interest, level of people in my regular

day-to-day life who know about Hermes

agent, we've never had this virality

until Hermes agent. And now, Hermes

agent was created

in two ways.

In the first way, we always knew that we

would want some kind of everything

orchestrator that self-learns, that

improves, that stores memories, that

uses and can make its own tools, that

can make itself better. We actually made

something like this called Forge. Uh

there's a GitHub presentation at the

GitHub offices during one of our demo

days where we showcased Forge and its

full effect.

Um and we also have the News Research

Forge division shirts still up on the

site. That's the first shirt we ever

made cuz that was our earliest agent

project.

Forge was really a spiritual predecessor

to Hermes agent years before.

But, the models weren't there yet. The

models simply weren't there yet. So, we

put Forge on ice.

And when we saw that Codex and Cloud

Code and these other harnesses were

being used as RL environments for them

to for these companies, these labs to

train on your data and your traces to

make their models better inside of a

harness system, inside of a CLI computer

using system,

Technium thought we need an open version

of this where anybody can do this. See,

we have this RL environments

microservice people seem to have

forgotten about called Atropos that lets

you build your own RL environments. And

we built our Hermes agent initially to

let anybody RL inside of a harness. And

we put it out for free as an open source

harness for that.

It turned out to be extremely capable.

It got a lot of community love. And so

we said we need to put all into this.

This is what the people want to be

better. We're going to make it the best

thing that you could possibly have. So

Technium took his charter up and he

worked on self-improvement with Hermes

agent to the point that today the

biggest contributor of Hermes agent is

Hermes agent.

>> Yeah. [laughter]

>> Is that true?

>> Yeah.

>> That's absolutely 100% true.

>> Nice. Nice.

Okay. So if Hermes agent is at a point

where it

uh take input of people's feedback,

start put put put put put stuff, start

improving.

>> the biggest It is the most active

contributor of its own repo.

And if that's not self-improvement, then

you tell me what is.

>> [laughter]

>> Yeah, yeah. That that's awesome, dude.

That that's really awesome.

[clears throat] Yeah. And just real

quick like on the future, you know,

having this open harness

be in in a game along with all the other

closed harnesses makes things a little

more more fair, right? Cuz then then

you're not dependent on any single

company.

>> I agree completely. If you have

cloud code, you can only use Anthropic

models unless you mod it. You can only

be subsidized by Anthropic. And same for

Codex. The cost of switching models is

zero.

Right? So we're giving you that freedom

means you can do anything that you'd

like. You can come from anywhere.

>> I feel like, you know, I'm I'm kind of

spoiled by this like all you can eat

plans, but like I think if you want to

get massive adoption, cost is a big

deal. So you have to be able to use a

portfolio models

to figure this out.

>> I agree. We don't know how long the

subsidies will last for these. Like

already we see that on July 7th stable

is going to be API and usage only.

Right? Like

the the time in the world will come

where like the best models are the same

cost everywhere.

Uh and so

in preparation for that and in

preparation for needing an open future

where anyone can use any model, we have

Hermes agent set up as it is today.

>> Awesome, dude. Well, thanks so much,

man. Thanks so much for showing uh the

history and also showing the Sonic demo.

It's It's been super interesting to see

it and uh

I'm not sure if you want to be found

online, but if people want to follow you

and hear from you, like where where can

people find you?

>> Sure, yeah. X is just my name Karen and

then 4D, Karen 4D. I got karen4d.com.

Uh that's me. That's my online or

Mephisto I'm known as, but

I'd rather you guys follow the Nude

Research page, follow Nude Army. I'm

just some guy who works there. Like

>> [snorts]

>> it's it's about the the movement and

bringing this stuff to you guys is the

most important thing to us.

>> Awesome, dude. Well, I think this is

like the most passionate interview that

I've I've done so far. So, kudos to you,

man. Kudos to you.

>> Appreciate it.