HomeVideos

Hermes Agent powered by local models on the DGX Spark is basically magic

Now Playing

Hermes Agent powered by local models on the DGX Spark is basically magic

Transcript

688 segments

0:00

Okay, so this is really sick. I just set

0:02

up a Hermes agent on this Nvidia DGX

0:05

Spark completely powered by a local

0:08

model that's running on it. I now have

0:11

an AI agent, a 24/7 AI employee working

0:15

for me completely on this local model on

0:17

this device, completely private, secure,

0:21

and best of all, free. Just the power of

0:23

the energy going into this device. And

0:26

look how cool this is. Isn't this the

0:27

coolest looking computer ever? In this

0:29

video, I'm going to show you how to do

0:31

the exact same thing. I'm going to show

0:32

you how to set up Hermes agent, have it

0:34

set up on a local model that will be

0:37

running on this DGX Spark. You can put

0:39

it on any device you want. For this, I'm

0:41

using the DGX Spark. I'll show you how

0:42

easy that is. And I'll show you how you

0:44

can have your full-time 24/7 AI employee

0:48

that's doing work for you at all times.

0:50

I'll even show you some really awesome

0:51

use cases that can be really helpful.

0:53

Whether you've never loaded up a local

0:54

model in your life, you're an expert, or

0:56

you're just curious in how all of this

0:57

stuff works, you're going to learn a ton

0:59

in this video. Now, let's lock in and

1:01

get into it. So, this is going to be

1:03

really fun. I'm going to show you like

1:04

the most cutting-edge technology ever.

1:06

Quick shout-out. Shout-out Nvidia.

1:08

Thanks so much for sponsoring this

1:10

video. If you watch this channel, you

1:11

know I don't take a lot of sponsorships.

1:13

99.9% of my videos are not sponsored. I

1:16

try to only work with companies that are

1:18

really amazing that I use daily. When

1:20

Nvidia reached out, I was super pumped.

1:22

One of the greatest companies of all

1:23

time. Shout-out Nvidia. Thanks for

1:25

sponsoring this. Let's go into the

1:26

strengths of local models and why a

1:29

local model with Hermes agent is so

1:30

sick. even send me a computer. I bought

1:32

this one myself months ago. So, that's

1:34

why this is really easy for me to do.

1:36

But, let's get into this. Let's talk

1:37

about local models, what makes them so

1:39

amazing, and why it's so powerful with

1:41

Hermes agent. Then, we'll quickly jump

1:43

into setting it up and having a lot of

1:44

fun in setting up experiments and doing

1:46

a lot of cool things. If you need to,

1:48

chapters down below, jump around if you

1:49

need to. Local models, I believe are the

1:52

future. I believe very soon everyone

1:55

will have their own super intelligence

1:57

on their desk. Why is that? Well, local

1:59

models are free. You can download them

2:01

online, load them onto your computer,

2:03

and they're basically free. Just you're

2:04

paying the cost of electricity, right?

2:06

So, the power powering the computer,

2:08

running local models does use up more

2:10

electricity. So, you're paying for the

2:12

power, you pay for the computer itself,

2:14

but unlike AI models running on the

2:16

cloud, you're not paying for every token

2:19

you use. You're not paying for

2:21

subscription plans, nothing like that.

2:23

Just the power going into the computer

2:25

and the computer itself. So, that's one,

2:27

unlimited usage of super intelligence,

2:29

pretty incredible. Next up, and this is

2:31

a big one, it's completely private. When

2:33

you use cloud models, right? So, when

2:35

you go to any of the AI websites and you

2:36

start chatting with their models, your

2:38

prompts and all your chat logs are

2:40

stored in the cloud. They're stored on

2:42

servers somewhere else. And well, I

2:44

don't think any of the employees are

2:45

going and reading your chat logs or

2:48

anything like that. Having your most

2:49

important conversations being private is

2:52

really important. So, you get the

2:54

privacy. If I unplug the internet from

2:56

this DGX Spark right now, I can still

2:58

keep using it. I can still chat with the

3:00

model and use my Hermes agent cuz it's

3:03

all local and private and secure. So,

3:05

everything stays local, everything stays

3:07

in your computer, no one can snoop on

3:09

your chat messages. That's big. It's

3:11

customizable. So, the models themselves

3:13

are customizable. You can install these

3:15

things called LoRAs, which are basically

3:17

plugins for the model, which allow you

3:20

to customize them really any way you

3:22

want. If you want them to really learn

3:23

your voice, if you want them to learn of

3:25

how to make specific types of images,

3:28

you can customize these models any way

3:30

you want. I can literally customize

3:31

right now so it sounds like me. So, all

3:34

of its output sounds like me, which is

3:36

amazing.

3:37

So, customization, that's big. It's

3:39

educational. You're learning about AI,

3:42

right? When you install it and start

3:43

using it locally, you learn how it

3:45

works. And I think this is the most

3:47

important technology of all time. I

3:48

think it's super important you learn it.

3:50

So, when you download it onto your

3:52

computer, you start using you learn

3:53

about the most important technology I

3:55

think humanity has ever invented. That's

3:57

huge. It's just straight up fun. It's

4:00

fun doing this. It's fun looking at your

4:02

desk, seeing a DGX Spark there, any

4:04

computer you have, and knowing there's

4:06

like superintelligence running on that

4:09

device. It's really, really fun. You're

4:11

allowed to have fun. You're allowed to

4:12

do things for the fun of it. Not

4:14

everything needs to be a hyper-optimized

4:16

dollar spend. You're allowed to just

4:18

have fun. And the last one here before

4:20

we get into actually promise we're about

4:21

to have a little fun here, use cases.

4:23

When you can run a model 24/7 for just

4:26

the cost of power, it unlocks so many

4:29

use cases. And I'll go into those use

4:31

cases in a second, but you really get a

4:33

powerful 24/7 AI employee. So, real

4:36

quick, why the DGX Spark? Everyone knows

4:38

I got a whole bunch of devices. I got

4:39

Macs, got everything under the sun here.

4:41

Why the DGX Spark though? Why do I like

4:44

this device? It is super easy. It makes

4:46

this whole process super easy. You buy

4:49

it, you plug it in, and it just works.

4:51

It turns on and you can immediately

4:53

start putting models on it. It's also It

4:55

also has the full suite of Nvidia

4:57

developer tools on it, so you can do all

5:00

the customization that's really only

5:02

possible on Nvidia chips. So, if you're

5:04

into customization as well, this is like

5:06

the best way to do it. So, the Spark is

5:08

a great way to run these models and run

5:10

Hermes on it. And I'll show you in a

5:12

second how easy it is for the agents you

5:14

have on your computer to actually manage

5:16

this device and install different models

5:19

on it. And by the way, that's not even

5:20

part of the sponsorship. I just threw

5:22

that in cuz I've been using this device

5:23

for a long time, and I use it every day,

5:25

and I love it. So, let's go into setting

5:26

it up. Let's get the device set up. I'll

5:28

speed through actually setting up the

5:30

computer, and we'll spend most of our

5:32

time setting up the agent and the model

5:34

itself. Feel free again jump around the

5:36

different chapters below if you want to

5:38

hear about any specific subject. First

5:40

thing you need to do though is actually

5:42

plug the computer in. Unlike other

5:44

computers out there, you do not need a

5:47

monitor for this computer. You can run

5:50

this in what is called headless mode.

5:52

Headless mode basically means there's no

5:54

monitor, you don't have to control it,

5:56

you don't have to touch it. It's just

5:58

powered on and you're able to use it

6:00

basically as a tool for whatever your

6:03

main computer is. So, once you have it

6:05

plugged into the wall, into the power,

6:08

it just turns on and it starts up a

6:10

local network. If you look at your

6:12

instruction manual with the DGX Spark,

6:14

it has actually like network information

6:16

on it. You just connect to that network

6:19

on your main device. Now your main

6:21

device can control that DGX Spark. So,

6:23

what you're going to want to do for this

6:25

is you're going to want to install

6:26

Hermes Agent on your main computer.

6:29

Powered by a cloud model at first, we're

6:31

going to have the local Hermes Agent

6:33

work side-by-side with our cloud agent

6:35

so we can get this all set up. Once you

6:37

have Hermes Agent set up, you have it

6:38

connected to a cloud model, whether it's

6:41

a ChatGPT account or using the Anthropic

6:43

API, whatever you want, we can now get

6:46

to work in setting up our local models

6:48

and setting up our new DGX Spark. Now

6:50

that we got the Spark plugged in, this

6:53

is the prompt I'm going to give to my

6:54

Hermes Agent. I'll put this down below

6:56

if you're setting this up with me. I

6:58

just purchased a new DGX Spark and want

7:00

to set it up. I want to run it headless

7:02

and I want you to be able to control it.

7:04

I'd like you to walk through setting up

7:06

the Spark then install Tailscale on it

7:08

so you can control it from any device.

7:10

So, a whole bunch of things going on

7:11

here, let me explain. Number one,

7:13

remember as I explained before headless,

7:15

that means no monitor or other devices

7:18

are going to control it. And number two

7:20

is Tailscale. For those not familiar,

7:23

Tailscale is like one of the most

7:24

incredible free pieces of software out

7:26

there. It's basically going to allow all

7:28

your devices to create its own private

7:30

network. So, your Spark and whatever

7:33

other computers you're using will be

7:35

able to be on the same kind of virtual

7:37

network so they can talk to each other

7:39

and control each other. So, what this

7:41

prompt will do is have your Hermes agent

7:44

walk through setting up your Spark.

7:46

It'll have you connect to the network on

7:48

the manual. It'll walk through

7:49

step-by-step. And then it'll go on there

7:51

once you're connected, set up the

7:53

computer itself, and then install

7:55

Tailscale so that moving forward it's a

7:58

lot easier for your Hermes agent to

8:01

actually control that device and use it.

8:04

It's going to allow your Hermes agent to

8:07

go on it, install local models on it,

8:10

set them up, run it, and then talk to

8:11

the local model anywhere you are in the

8:13

world cuz it'll be on that same private

8:15

network. So, you hit that, you're going

8:17

to be all set up. It's super easy.

8:19

That's the beauty of these AI agents.

8:21

That's the beauty of using Hermes agent

8:23

here is that it makes it super easy to

8:25

do whatever you want. Before this, it

8:28

would be super intimidating to do

8:30

something like this. It'd be super

8:32

intimidating to set up a supercomputer

8:34

on your desk. People would go, "Oh."

8:37

They throw their hands and go, "Oh, I'm

8:38

not tech. I'm a non-technical person.

8:40

This isn't for me." If you're watching

8:41

this video right now and you're

8:42

thinking, "Oh, this is not for me. I'm

8:44

super non-technical." Throw the word

8:46

non-technical in the garbage can. Take

8:49

it out of your lexicon. Non-technical

8:52

does not exist anymore. Everyone is a

8:55

technical person. As long as you got an

8:57

AI model, as long as you got a Hermes

8:59

agent, it doesn't matter what it is. You

9:01

go to your agent, you say, "This is what

9:03

I want to accomplish. You accomplish it

9:05

for me." And it will figure it out.

9:07

Everyone is technical now. I don't want

9:10

you to limit yourself by calling

9:11

yourself a non-technical person. Every

9:14

time someone in my life says, "Oh, I'm a

9:15

non-technical person." I I tell them to

9:16

kick rocks. Figure it out. Download an

9:18

AI model and figure it out. You got

9:20

this. I promise you. So, you got the DGX

9:22

Spark set up. Next, we're going to

9:24

download and install a local model. For

9:28

this video, we're going to use Qwen 3.6

9:31

27B. Qwen 3.6 is the latest set of

9:35

models from Qwen. This is, in my opinion

9:38

the strongest local model there is. It

9:41

is super fast, it is super efficient,

9:44

and at the same time, it is super

9:46

intelligent. It is up there with a lot

9:48

of the frontier models from the last few

9:50

months. So, it is very, very good. So,

9:52

here's what we're going to do now that

9:53

you have the Spark set up. Say this, "I

9:55

want to download and install Qwen 3.6

9:57

27B onto the DGX Spark so I can use it

10:01

to power AI agents and chat with it."

10:03

27B just means it's 27 billion

10:05

parameters, which is kind of on the

10:07

medium-to-smaller side, but through

10:10

tests I've done and through a lot of

10:11

tests other people have done, it's still

10:14

incredibly smart, but you're going to

10:16

get the benefit of really, really good

10:18

speeds. So, I'm going to put this down

10:20

below as well, so feel free to steal

10:22

that. That will go and have your agent

10:24

go into your DGX Spark, search the web

10:27

on there for that model Qwen 3.6 27B,

10:31

find the version that's appropriate for

10:33

the Spark, download it, which might take

10:36

a little bit. These models are pretty

10:37

chunky, but it'll fit onto your new

10:39

computer, and then actually load it into

10:42

memory. Right, these models, the way

10:44

they work is they're loaded onto your

10:46

memory, and then you can start using it

10:48

and communicating with it. This took

10:50

about 20 minutes or so on my computer.

10:53

It might take about the same for you

10:54

depending on your internet speeds and

10:55

all that. So, do that. Feel free to

10:57

pause here if you're doing this

10:58

alongside of me and come on back. So, if

10:59

this is your first time doing this and

11:01

you just set it up and it downloaded

11:03

Qwen and then got it loaded into the

11:05

memory, first of all, congratulations to

11:07

you. You just did something that like

11:09

0.000001%

11:12

of the world has ever done, which is

11:14

host your own super intelligence on your

11:17

desk. Do yourself a favor, look down at

11:20

your computer and go, "Holy crap, I have

11:22

super intelligence on my desk. I am a

11:25

sovereign individual. Nobody can take

11:28

this away from me. No one can cut off my

11:30

AI service. No one can take this away.

11:32

Even if the internet goes out forever, I

11:34

will have super intelligence to get me

11:36

through it. So, shout out you, this is

11:37

your first time. Congratulations. Now,

11:40

let's get into actually using that super

11:42

intelligence. So, here's the plan what

11:44

we're going to do here. We're going to

11:46

set it up inside Hermes agent. I'm going

11:48

to show you how to do that. And then I'm

11:49

going to show you three really awesome

11:51

use cases for Hermes running on local

11:54

models. I just like to do one fun thing

11:56

real quick before we get into that. And

11:58

that is set up a front end chat

12:00

interface for our model. This allows you

12:02

to just test it real quick and kind of

12:04

feel that magical moment of, "Oh my god,

12:06

super intelligence is talking to me

12:07

locally." So, do this. Please build a

12:09

front end for our new local model. Make

12:11

it a chat interface and test that it

12:13

works. I will put that down below as

12:15

well, so you can steal that if need be.

12:17

And when you hit enter in that, your

12:19

Hermes agent's going to go. It's going

12:20

to actually build out a really quick

12:22

front end interface, or really simple

12:24

code it out, and then it will connect it

12:26

to your local model. So, mine is all

12:28

built out here. Look at this. This is

12:29

awesome. Spark 1 3627B. Let's give it a

12:32

test. Hey, are you there? And enter and

12:36

now let's see how we do. Is our local

12:37

model going to work here? Is it going to

12:39

chat with us? Super intelligence, are

12:41

you working? Oh, there it is. Yes, I'm

12:44

here. How can I help you today? That's

12:46

amazing. That came straight from our

12:48

computer on our desk. If you're not

12:50

geeking out with me, then you're not

12:51

alive. That's amazing. So, we've

12:54

confirmed it's working. We confirmed our

12:56

local model is talking to us. We

12:57

confirmed the super intelligence is

12:59

doing its thing. Now, let's actually

13:01

plug this into Hermes agent so we can

13:03

have our local working for us. So, what

13:06

makes Hermes agent

13:10

really cool is it is built in to be

13:12

multi-agent. What that means is it is

13:15

just one command away from Hermes being

13:17

able to create an entirely new Hermes

13:19

agent that can run side by side with

13:22

your current one. So, you can do really

13:24

cool workflows with multiple agents.

13:26

What we're going to do is we're going to

13:27

have it set up a second Hermes agent for

13:30

us and we're going to say plug it in to

13:32

our new Qwen 36 model that's running on

13:35

our DGX Spark. So, let's do this. I just

13:37

So, I'm going to use this prompt. I'll

13:38

put this down below as well if you want

13:40

to take it. I just installed Qwen 36 27B

13:44

on our DGX Spark. Please set up a new

13:46

Hermes profile that is plugged into that

13:48

local model and name it Qwen. I like

13:50

that name Qwen. So, I'm going to name

13:51

our new Hermes agent Qwen. Let's hit

13:53

enter on that. Now our Hermes agent's

13:55

going to go and it's going to create

13:57

this new Hermes profile which is

13:59

basically just a second Hermes agent and

14:01

it's going to plug it into that model

14:04

running on our Spark which is going to

14:06

be sick.

14:07

All right, here we go. It found the

14:09

llama server where the uh local model is

14:12

running. It's going to ask us for

14:13

permission. Let's give it the okay on

14:15

this and it's going to start getting to

14:17

work building out that new Hermes agent.

14:19

So, we'll have two Hermes agents working

14:22

for us, two full-time employees, one

14:24

that's going to be completely free run

14:26

on the Spark and I'll walk through all

14:29

of the different use cases and how do

14:30

you do the two models together after

14:32

this. All right, looks like it's all

14:34

set. All right, so to run this all we

14:37

need to do is hermie p Qwen. That's

14:38

going to run the Hermes profile for Qwen

14:42

which they just set up. So, let's get

14:43

this popping. Let's do this. So, I'm

14:45

going to open up my terminal here. I'm

14:46

going to paste in hermes -p Qwen. I'm

14:50

going to hit enter and boom, there we

14:52

go. Look at that Hermes agent. Oh,

14:54

that's incredible. There it is Qwen 36.

14:56

That's the model we got running locally.

14:59

We now have an AI employee 24/7 running

15:04

locally on our desk on our computer.

15:06

Let's say hey here. Let's see how it's

15:07

doing. Hey, are you there, Qwen? Come

15:10

on, here we go. Hey, I'm here. I'm

15:12

actually Hermes agent not Qwen but I'm

15:13

ready to help. What do you need? Okay,

15:14

so it doesn't know its name but it's

15:16

here. It's working. We can talk to it. I

15:18

guess when you set up a profile it

15:19

doesn't give it its name. So, let's give

15:21

it its name now. By the way, your name

15:25

is Quen. And that will save it to

15:27

memory. So, moving forward, we can refer

15:29

to our new AI agent employee by its

15:32

proper name, Quen. Got it. Quen it is.

15:34

I'll go by that from now on. And then

15:35

you can see this is a cool part about

15:37

Hermes. It tells you every tool call,

15:38

every memory updates. Updating the

15:40

memory, the user refers the assistant as

15:42

Quen. Really, really cool. Now, let's go

15:44

into the three use cases for our local

15:48

agent. We have a local 24/7 AI employee.

15:51

What do you do with it? It's probably

15:52

the number one question I get. It's

15:53

like, "Oh, what are the use cases you

15:55

do?" Let's go through three. I'm going

15:56

to give you a beginner one, a moderate

15:58

one, and an advanced one. So, no matter

16:00

where you are, you're going to have a

16:01

use case that works for you. Let's start

16:03

with the beginner one. I strongly

16:05

believe everyone should be investing. I

16:08

don't think that's a crazy take. I do a

16:10

lot of investing myself. My favorite way

16:13

to do investing and learn about

16:15

investing and get better at it is by

16:17

using my AI agents. And so, what we're

16:19

going to do is we're going to have Quen

16:21

set up a daily report for us that is

16:23

going to investigate AI stocks and AI

16:26

companies cuz I personally, not

16:28

financial advice, think that's a great

16:29

place to be investing. So, let's do

16:31

this. All right. So, here's the prompt

16:32

I'm going to do for this. Please, every

16:34

morning at 9:00 a.m. research AI stocks

16:36

for me. These are stocks for companies

16:38

that stand to benefit from a 10-year AI

16:40

build-out. Give me a report on the top

16:42

companies that have great moats and

16:43

great businesses and tell me why they

16:45

have moats. I want to invest in

16:47

companies that don't really have

16:48

competition or are the very best in

16:51

their field. So, that's why I want to

16:52

know about these moats. What's great

16:54

about Hermes agent is you can have these

16:56

scheduled tasks. So, every day at

16:59

specific times, it does things for me.

17:01

So, I do this. I have this built out.

17:03

It's going to now send this to me every

17:05

morning at 9:00 a.m. Every morning at

17:07

9:00 a.m. it will deliver me this report

17:10

so I can read it, see if there's

17:11

businesses I want to invest in, make

17:13

sure I spend my money wisely, and make

17:15

sure I can grow in the future. Now, my

17:17

AI employee is going to be a stock

17:19

researcher for me. This is really

17:21

beginner. Anyone can do this and you're

17:22

going to get value out of doing this.

17:24

What this is doing in the background is

17:26

just scheduling a cron job. For those

17:28

that don't know, cron jobs are basically

17:29

just scheduled task for computers. In

17:32

this case, it is for our agent. And now

17:34

every day at 9:00 a.m., the cron job

17:36

will fire. It'll tell our agent, which

17:38

is running on our local model, to go and

17:41

do the research for us and give us that

17:42

report. And boom, look at this. Done.

17:45

The cron job is scheduled here. The

17:46

details, daily AI stock report, every

17:49

day at 9:00 a.m. Next run's going to be

17:50

tomorrow, 9:00 a.m. And it is all set.

17:53

Each morning will search for the current

17:55

stock prices and news. That is sick. So,

17:57

now we have our daily research reports

17:59

up. Let's get into the intermediate use

18:01

case for a local AI agent.

18:04

And again, this is completely free other

18:06

than the cost of the electricity going

18:09

into your computer. So, you basically

18:11

have your own personal local free AI

18:14

researcher, which is amazing. Let's get

18:16

into the moderate use case here. This

18:19

next one is really cool. It's something

18:21

I do often and that is repurpose

18:23

content. What I'm going to do is I'm

18:25

going to give our local agent a link to

18:28

a YouTube video. Even if you're not a

18:30

content creator, this will be helpful

18:31

for you. What I like to do is I give it

18:33

links to my own YouTube videos and say

18:35

repurpose this into a newsletter for me.

18:38

But what you can do is say, "Hey, check

18:39

out this video link, get the transcript,

18:42

and tell me what lessons we can learn

18:44

from it." You can do it on this video

18:45

right now that we have here. So, let's

18:47

do this. I'm going to grab one of my

18:48

past videos and I'm going to say, "Get

18:51

me the transcript of this video, then

18:55

repurpose it into a newsletter." And I

18:59

paste it in and I'm going to hit enter

19:00

and it will be off to the races. It's

19:03

going to go And one thing Hermes does

19:04

really well is just figure out how to do

19:06

things. It'll figure out how to get that

19:08

transcript, download it, and then

19:11

repurpose it new content for us. Again,

19:13

for you, you can have it get the

19:15

transcript and then take learnings from

19:17

it, right? Say, "Hey, Hermes agent,

19:19

check this out and see what we can learn

19:21

from this video. Apply new skills. Get

19:23

me the top lessons." and it'll do it for

19:25

you. So, so many things you guys can do

19:27

with this as well. If you want to do as

19:28

long as I mean, just take the link to

19:29

this video and give it to your agent.

19:31

And this is so cool. Look at this. It's

19:32

figuring out the skill to get YouTube

19:34

content. It's building its own skills.

19:36

Got the full transcript. Here's the

19:37

newsletter version and boom, it's

19:39

writing out the newsletter for me. It

19:41

just like so amazing to think about how

19:43

this is happening all locally, all just

19:46

on the computer on my desk. This is all

19:47

just getting figured out. I mean, we

19:49

really live in the most amazing time

19:51

ever. So incredible. And here's a little

19:53

twist on this use case because it's

19:55

happening locally, right? Because I'm

19:57

not paying for tokens on a cloud, maybe

19:59

I schedule this so every hour it

20:01

searches YouTube for a new AI video,

20:04

downloads it, gets the transcript, gets

20:06

the lessons, and now my Hermes agent is

20:10

automated improving itself every hour

20:13

searching for AI videos, getting lessons

20:15

from it, self-improving itself, and

20:17

doing that non-stop. That's incredible

20:19

to think about. That's something you

20:20

can't really do with cloud models cuz

20:22

you'd be paying for every single cycle,

20:25

for every single token. Because this

20:27

just costs the electricity going in

20:29

computer, you can just have this go all

20:31

day, right? Just constantly downloading

20:33

new videos and self-improving itself. It

20:34

really is amazing the possibilities to

20:36

think about with the Hermes and the

20:38

local model. All right, here we go.

20:39

Let's get into the advanced use case and

20:42

that is vibe coding. We are going to

20:44

have our Hermes agent vibe code a to-do

20:47

list app for us. So, very simple, just

20:49

for demonstration purposes. You can now

20:53

have your local models do vibe coding

20:56

for you. This is one of the most

20:57

compute-intensive activities people do.

21:00

Some people spend thousands of dollars a

21:02

month on these different vibe coding

21:04

tools. You can now get it just for the

21:06

cost of electricity. So, let's have Qwen

21:09

vibe code for us. Really is amazing

21:11

thing about this, you just now have

21:12

unlimited vibe coding, but that's one of

21:14

the benefits. That's how you get an ROI

21:16

on these investments in these computers

21:18

is doing things like this. So, let's do

21:20

this. Please build me a to-do list app

21:22

where I can add new task with priorities

21:24

and dates for those tasks. Make the app

21:26

beautiful and clean, and we're going to

21:28

hit enter. And now our 24/7 AI employee

21:31

is going to be building out us out an

21:33

entire app. All done locally. Really,

21:36

really cool. And what's great is you can

21:38

even go and you can plug this local

21:41

model in to the many various vibe coding

21:44

tools out there. There are ways to plug

21:46

it into Claude code, Codex, open code,

21:48

whatever you want to use. You can now

21:50

leverage this local model in any vibe

21:52

coding tool you want, but Hermes is a

21:55

great coder. So, using Hermes to build

21:57

things out works totally fine. All

21:59

right, look at this. It is all complete.

22:01

Open in your browser. All right, we're

22:03

going to open this up. Here's what it

22:04

does. Add task, mark complete, delete

22:06

tasks, filter between all active, done.

22:09

Wow, it's got a lot in it. This is

22:10

amazing. Let's go. And this is all built

22:12

locally. How incredible is that? All

22:14

right, let's do this. Let's take the

22:16

command, and we are going to run it so

22:18

we can use our new app. And it opens up.

22:21

Let's see what we got. Let's see what

22:22

was built 100%

22:25

locally. Look at this. This is actually

22:28

sick. This looks like it was made by

22:31

like a cloud top-of-the-line frontier

22:34

model. how good Qwen 3.6 is. Let's do

22:37

this.

22:38

Edit the DGX Spark Hermes video. Let's

22:44

add this task. Boom, there it is. And

22:46

you see that nice animation? That

22:48

animation was so sick. Let's do I want

22:50

to see that again. Make another video.

22:54

Add the task. See, oh, that is nice.

22:56

That is nice. I love that. Now you have

22:59

your free unlimited vibe coding tool

23:02

ready to go. You can build whatever you

23:05

want. No limitations at all. That is the

23:08

beauty of this. This is amazing.

23:10

Anything you want to build, you now can

23:12

build it. All done locally on your desk.

23:15

Really, really well done. If you learned

23:17

anything at all, make sure to leave a

23:19

like down below. Subscribe. Turn on

23:21

notifications. All I do is make amazing

23:23

videos about AI. I do live bootcamps on

23:26

vibe coding and building things every

23:28

single Friday in the vibe coding

23:30

academy. Link down below for that. So,

23:32

check that out as well. Shout out Nvidia

23:35

for partnering up on this. I've had the

23:37

DGX Spark forever. I've been running AI

23:39

agents on it forever. So, for them to

23:41

reach out was amazing. So, thank you so

23:42

much for that. Also, another thing, make

23:44

sure to hit the link down below for more

23:46

information on the Nvidia DGX Spark. An

23:49

incredible device to be hosting your own

23:51

models on. Appreciate you guys watching.

23:54

Let me know down below in the comments

23:55

what you want to see next. Do you want

23:57

to see more use cases for Hermes agents?

23:59

want to see more advanced workflows? I'd

24:01

love to hear your opinion. Thank you for

24:04

watching. It truly means the world and

24:05

I'll see you in the next video.

Interactive Summary

This video demonstrates how to set up an AI-powered 'employee' using a local model on an Nvidia DGX Spark, ensuring a private, secure, and free-to-operate setup. The creator walks through the configuration of an AI agent, the installation of the Qwen 3.6 27B model, and provides examples of practical use cases such as automated stock research, content repurposing, and 'vibe coding' web applications.

Suggested questions

3 ready-made prompts