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REVOLUTIONIZING NATURAL LANGUAGE PROCESSING WITH AUTO-GPT: THE STATE-OF-THE-ART LANGUAGE MODEL
MATT·APRIL 20, 2023
Natural language processing (NLP) has become increasingly popular in the field of artificial intelligence in recent years. GPT...
מהפכה בעיבוד השפה הטבעית עם GPT אוטומטי: מודל השפה החדיש ביותר
MATT·20 באפריל, 2023
עיבוד שפה טבעית (NLP) הפך יותר ויותר פופולרי בתחום הבינה המלאכותית בשנים האחרונות. GPT...
MATT·APRIL 12, 2023
The world has been captivated by ChatGPT, largely due to its user-friendly design. This AI chatbot effortlessly generates...
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Agent GPT Deploys Auto GPT on the Browser
PART - 1
How to set Open AI usage limits
PART - 2
Agent GPT deploys auto gpt on the browser | AgentGPT - Beginners tutorial | No Code AI agents
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AGI is here! (AutoGPT) Detailed Tutorial + Real Example
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Auto-GPT One-Click Install | ChatGPT Sparks of AGI Guide | Windows
How to Install Auto-GPT on Mac [Step by Step Quick & Easy Tutorial]
How To Install Auto-GPT On Mac OS (Run AutoGPT In Terminal)
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NO Coding - N0 Python
AutoGPT Tutorial - More Exciting Than ChatGPT
Transcript
PART - 1
0:00
so chat GPT is no longer the most
0:02
exciting thing in AI instead everyone's
0:05
freaking out about this new software
0:07
called Auto GPT which can essentially
0:09
automate way more than chat GPT was able
0:12
to this could make you a virtual
0:14
assistant this could be a wedding
0:15
planner this could be a nutritionist
0:17
this could be a lot of different things
0:19
and automate substantially larger tasks
0:21
than Chachi PT was able to now how is it
0:24
able to do this well we're going to talk
0:26
about that throughout this video and
0:27
this is a full tutorial showing you how
0:30
to set it up and how to actually use
0:31
that and I promise I will not be
0:33
skipping any steps at all so even an
0:36
absolute beginner who knows nothing
0:37
about coding can follow along type in
0:40
the letters I type and get to the exact
0:42
same place so that you can run your own
0:44
version of Auto GPT very easily on your
0:47
own computer and I can prove that right
0:49
here this laptop right here I have not
0:51
done this has nothing on there it says
0:53
no coding tools this has no python this
0:55
has nothing like that so we will
0:57
actually be setting this up from scratch
0:59
so we're not skipping any steps now like
1:01
I said Auto GPT is really really
1:04
impressive but why is it different from
1:06
chat GPT well chat GPT is great
1:09
obviously a large language model you're
1:11
able to ask your questions to run
1:12
commands and it can give you kind of one
1:15
response at a time sometimes those can
1:16
be complex responses but nonetheless one
1:19
thing at a time and in addition to that
1:21
you don't really have access to the
1:23
internet with that whereas Auto GPT is
1:26
able to aggregate many different what's
1:28
called apis essentially work with
1:30
different plugins so you can have a
1:32
Google API so it's able to search the
1:34
internet you can have a chat gpta API so
1:37
you're able to use chat GPT you have a
1:39
lot of different things in there it can
1:40
give you images it can output audio
1:43
that's actually like a simulated voice
1:45
it could be your simulated voice really
1:47
Endless Options here and really the big
1:49
difference is rather than just asking
1:51
for one command at a time you can give
1:54
it up to five different goals and then
1:57
it'll iterate on itself it'll run a
1:59
command it'll come up with an output
2:00
it'll give you a reason for that output
2:02
and then it'll come up with what its
2:04
next command is going to be and it can
2:06
iterate on that over and over until it's
2:08
able to get you the results so for
2:10
example if you say I want to plan a
2:12
wedding it could first say you know what
2:14
is the normal stuff for planning a
2:16
wedding and you can have a list of what
2:17
okay this is the results these are what
2:19
I think I need to do in order to plan a
2:21
wedding then the next step it'll say all
2:23
right now let's find local venues and it
2:25
can go and find local venues and then it
2:27
can look up the reviews of the venues
2:29
and then it can find the best reviewed
2:31
venue then it could go after that and
2:33
say all right let's find some catering
2:34
and so it can iterate and continue a
2:36
longer process that otherwise you'd need
2:38
a person to either work with just Google
2:41
or chat gbt to kind of work on this
2:43
themselves so I hope that kind of
2:45
explained it I think a lot of examples
2:47
throughout this video will be very
2:48
helpful but let's get over to my laptop
What do I need to run AutoGPT?
2:50
and start off actually setting up Auto
2:53
GPT like I said it's very simple very
2:55
straightforward you just have to follow
2:57
along and do what I do now before we get
2:59
into the first step I want to point out
3:01
that I will have links down below like
3:03
not affiliate links just regular links
3:05
because it's free to use and this will
3:07
be a link to the GitHub which is the
3:08
repository of where the source code is
3:11
actually stored so we will be
3:12
downloading that and I'll go through
3:14
that link in a second I also have a link
3:16
down there to install python which we
3:18
will need I use Anaconda that's how I've
3:20
always operated with python and we will
3:22
have a link to visual code if you want
3:24
to use that that's not absolutely
3:25
necessary but it does make it so much
3:28
easier to view things like markdown and
3:30
different types of files that we will
3:32
have in the repository and then the
3:34
fourth thing down there is a link to our
3:36
free newsletter so we are launching a
3:38
brand new newsletter because AI is
3:39
moving so quickly so just when you
3:41
thought you got a hold on chat GPT Auto
3:43
GPT came out and there's going to be
3:45
more iterations and more changes and
3:47
more Improvement in this field and so if
3:50
you don't end up keeping up with this
3:51
space you're going to fall behind and
3:53
eventually somebody else is going to
3:55
make the equivalent of Auto gbt to
3:58
replace your job and so really really in
4:00
our opinion the best way to prevent this
4:02
the best way to keep up to date on
4:04
everything is to know what's going on in
4:06
AI so that you're on the Leading Edge so
4:08
you're not the one getting replaced
4:09
you're the one innovating and the most
4:12
valuable person at your company so step
Getting started
4:14
number one is to copy and paste the link
4:15
in the description it goes to github.com
4:17
and this just has latest release so it's
4:20
going to change when you actually go to
4:21
this so right now the latest is V
4:24
0.2.2 and this does of course change as
4:26
they iterate depending on when you're
4:28
watching this video don't worry if it's
4:30
a later version I will you know cover
4:31
everything that might change in this
4:33
video as well as how to see what the
4:35
changes are and if anything changes how
4:37
to actually utilize that so that'll
4:39
bring us to GitHub which if you already
4:41
have done any coding you definitely know
4:42
what this is it's a very very common
4:44
place for any coders to save their
4:47
source code so other people can read it
4:49
they can Fork it make different versions
4:50
of it it's super popular and really a
4:52
powerful tool in the space so going down
4:55
here you can see that auto GPT version
4:57
0.2.2 they have a couple things that
4:59
they change change from the last version
5:01
and down near the bottom we should see
5:03
download source code ZIP right now by
5:06
the way I'm using a Mac this will change
5:07
almost nothing in this tutorial I'll
5:09
point out the things that it does change
5:11
if using Windows essentially what I'm
5:13
saying is you can still follow along and
5:15
it's going to be essentially identical
5:17
so I just made a new folder called Auto
5:19
GPT and I want to make sure that I'm
5:20
downloading this ZIP file to Auto GPT it
5:24
downloaded to my downloads folder so I'm
5:25
just going to copy and paste it over to
5:27
this folder and we do want to make sure
5:28
it is extracted because that's a zipped
5:30
file so once we're extracted on Mac you
5:33
just double click that on Windows you'll
5:34
click on it and at the top you'll see a
5:36
little menu that says extract all just
5:38
click on that and you'll have it all
5:39
extracted and you should have all these
5:41
files here now it might look a little
5:42
different when you're whenever you're
5:43
downloading that that's the first step
Downloading Python and VisualStudio Code
5:45
we want to do the second step is to
5:47
download python so if we just go to
5:48
anaconda.com that'll bring you to this
5:51
right here and we can download so right
5:53
now it knows that I'm on a Mac so I can
5:54
download for Mac I'm going to click on
5:56
that once again that will download to my
5:58
downloads folder and this is is going to
6:00
give us access to python which is
6:02
incredibly powerful it's free to use and
6:04
is really going to be essential in what
6:06
we're doing in this video so you'll see
6:08
this package is downloading when it's
6:10
done I'm just going to click on that
6:11
it's going to run me through the
6:12
installation
6:13
so I'm going to say continue I'm just
6:15
going to keep continuing and agreeing
6:17
I've already read all this stuff before
6:18
and then when you're done you can click
6:20
on close we're just going to move that
6:21
to trash so what we want to do is
6:23
download visual studio code so then this
6:25
is the next thing so we can go to
6:27
code.visualstudio.com and right here we
6:29
can have download Mac universal that's
6:31
what we want depending on if you're on
6:32
Windows it'll just say windows obviously
6:34
and you'll have that version but it
6:36
should be essentially the same so this
6:37
is going to download I'm going to click
6:39
on it so that when it's done downloading
6:40
it'll open that and we can install it so
6:42
we're going to click on it and open it
6:43
and that'll bring us to
6:45
this page right here so there we go we
6:47
have Visual Studio code now we're going
6:48
to add this to our path so it's easy to
6:50
access later on just kind of saves us
6:52
some steps so hitting command shift p on
6:54
Mac that'll bring up this we can type in
6:57
shell and you'll see shell command
6:58
install code command in path that's
7:01
exactly what we want to do I'm just
7:02
going to say okay I'm going to type in
7:04
my my password for my laptop and now it
Configuring in Terminal
7:07
is successfully installed so we can
7:08
actually close out of this all right so
7:10
here we are now we're ready to actually
7:11
get started if you're on a Mac you can
7:13
hit the magnifying glass or command
7:15
space and type in terminal we're going
7:17
to open Terminal if you're on Windows
7:19
you can simply do this with uh
7:22
Powershell and before anybody gets mad
7:25
at me I'm going to switch over to dark
7:26
mode I had it in light mode because
7:27
other tutorials it was just like easier
7:28
to see but anyway here we go so we're in
7:30
dark mode I'll make this a little bit
7:32
bigger as well the first thing we're
7:34
going to do is set up our anacon or our
7:36
python environments we're going to type
7:37
in conda create dash n Auto Dash GPT
7:41
python equals 3.8 you can use other
7:44
versions depending on when your watching
7:46
this video but we're going to do 3.8
7:47
right now I'm going to hit enter
7:51
and wants to know if we're going to
7:52
proceed so letter Y and then enter means
7:55
yes so it's going to proceed
7:58
now a couple little housekeeping items
7:59
we want to navigate into out of the
8:02
folder that we have so this folder right
8:04
here Auto GPT I'm going to unmack you
8:07
just you know right click down here and
8:09
you can say copy the path name on
8:10
Windows it'll be on the top so you can
8:12
just click on the bar that has all the
8:13
path name listed copy that and then down
8:16
here we can say CD space and then paste
8:19
that and that'll bring you into that now
8:21
if you're not familiar with terminal or
8:23
Powershell essentially what you can do
8:25
CD is going to navigate around different
8:27
folders so if you want to go back a
8:29
folder you could say CD space dot dot
8:31
and that'll bring you back to the
8:32
previous folder and if you don't know
8:34
what's in that folder you can say LS
8:36
that'll list out what is in that folder
8:38
so we're going to list it out I only
8:40
have one thing in this folder you can
8:41
see right there and so if you want to go
8:43
into that you can say CD and then we can
8:45
type in Auto Dash and you can hit tab to
8:48
auto complete that once you have some of
8:50
it typed and hit enter and that's how
8:52
we're going to end up in that folder so
8:54
this is exactly where we want to be
8:56
so now that we're okay so now that we're
8:58
in the right folder if we type LS you'll
8:59
see these are all the files this is
9:01
exactly what we want now we can say code
9:03
space Dot and that'll open up a visual
9:05
studio code as you can see right here
9:07
um so I'm going to trust my own parent
9:09
folder here and you can see on the left
Reading the ReadMe markdown file
9:11
these are all the files now the reason I
9:13
told you to download visual studio code
9:15
is because we have files in here for
9:16
example markdown which is really hard to
9:19
read when you just look at it like this
9:20
but if you right click on it you can go
9:23
and say preview open preview and it'll
9:25
open it up in this really nice looking
9:27
format with pictures and it just looks
9:29
like it's so much easier to read
9:31
something like this now this is the
9:33
readme file which is going to
9:34
essentially be our guide to use to use
9:37
Auto GPT so the reason I wanted to show
9:40
you this I mean first of all we're going
9:41
to follow along in this video but just
9:43
in case anything changes this is where
9:46
you would go to actually find that so
9:47
I'm trying to make this video as future
9:49
proof as possible so that future
9:51
iterations of this if anything subtle
9:53
changes you will still be able to use
9:55
this but I'm confident that for the most
9:57
part everything we're doing in this
9:58
video will be exactly correct no matter
10:01
when you're doing that so right now
10:02
we're at this stage right here so we
10:04
want to we already downloaded that we
10:06
want to install the requirements so
10:08
there's a file over here called
10:09
requirements uh down here requirements
10:12
and we want to install all of the
10:13
necessary packages that we'll need for
10:16
this Auto GPT so I'm just going to copy
10:18
this and we're going to go back to our
10:20
terminal right here our Command terminal
10:22
and we can paste it down there this will
10:24
be pip install Dash R requirements.txt
10:27
hit enter it's going to install a bunch
10:30
of little things down there all right so
10:31
while that's installing going back to
10:32
the readme the next thing we want to do
10:34
is configure Auto GPT now luckily
10:36
there's really not much we have to do
10:38
here we just have to add in our personal
10:41
API key and I'll show you exactly how to
10:43
do that and change one other thing if
Adding your OpenAI API key
10:45
you're using a Mac there's other apis we
10:47
can enable and you can mess around this
10:49
later but just getting it set up for
10:51
like the absolute Basics let's start off
10:53
with adding your open API keys so we
10:55
want to do is go back to terminal and we
10:57
can type in
10:59
cp.env.template space dot EnV so
11:02
essentially what we're doing is we're
11:03
making a copy of env.template and just
11:06
making it dot EnV so I'm going to hit
11:07
enter and that should do that over here
11:09
we can go back to visual studio code and
11:11
see that we now have a file called dot
11:13
EnV and everything is green which means
11:16
it's commented out which means it's not
11:18
going to be run as code but if there's
11:20
anything that you do want to run as code
11:22
so if we go down here let me just search
11:24
for Mac it's somewhere down here there
11:26
we go so because we're using Mac right
11:28
here the thing that is single commented
11:30
I'm just going to delete that little
11:31
hash and now we are using Mac and it's
11:34
set to false I'm going to change that to
11:37
true so we're going to set that to true
11:38
now the only other thing on here that
11:40
I'm going to change initially like I
11:42
said there's other things we can add we
11:43
can add an API for image output or Voice
11:46
output or different things like that but
11:48
the only thing that you actually need to
11:50
add to run this is your own API key
11:53
which you can see right here so I'm
11:54
going to delete that right now and we're
11:56
going to go over to chat GPT or open
PART - 2
12:00
II's website rather and we're going to
12:01
get our API key our secret key that is
12:04
personal for us that we can use right
12:06
here
12:07
so what I'm going to do is from my
12:09
browser go to
12:10
platform.openai.com account slash API
12:13
Dash Keys again I have a link in the
12:15
description so you can follow along
12:17
there I'm going to hit enter and from
12:19
here I'm just gonna have to sign in so
12:20
you should already have a chat GPT
12:22
account if you don't uh you can sign up
12:24
right now and I highly recommend you
12:26
watch my full video about chat GPT where
12:28
I go through the 10 different major
12:30
commands and modifiers that you can use
12:32
to really optimize your Effectiveness on
12:35
chat GPT to become better in life at
12:38
work whatever you're doing whatever
12:39
you're using it for highly recommend
12:41
that video right now it has 1.4 million
12:43
views and a lot of people are really
12:45
finding it helpful but regardless
12:46
assuming you already watched that video
12:48
the next thing is to log in so that
12:50
should take you to a page that looks
12:52
just like this you probably won't have
12:53
these two right here I actually don't
12:56
even need those so I can delete those as
12:57
well so we're going to revoke that key
12:59
and we're just going to click on create
13:00
new secret key I'm going to do this in
13:02
this video I'm going to delete it so you
13:04
guys don't use my credits here but if we
13:06
clicks create new secret key we can call
13:08
this whatever we want so I'm going to
13:10
call it auto GPT I can copy that that
13:13
secret key we're going to say done and
13:16
then going back to visual studio code we
13:18
have Visual Studio code right here I can
13:20
paste it right in there now you could
13:22
add this with quotes on either side I
13:24
don't believe you need to because they
13:26
didn't originally I did last time this
13:28
time I'm going to not do that and it
13:30
should work either way that's just a
13:32
string of text there so then when you're
13:33
done with this we can save it so we're
13:35
going to hit Ctrl or command s control s
13:37
depending on what you're using and of
13:38
course I do also want to save this
13:40
workspace so we're going to go to file
13:42
save workspace As and we're going to
13:44
call it that looks fine to me and it's
13:46
in this folder so we're going to say
13:47
save and now there is one more thing we
13:50
have to do on open airi's website and we
13:52
have to add a billing method so you just
13:54
go down to billing and it'll prompt you
13:56
to add a payment method otherwise you'll
13:59
just click on payment methods you can
14:00
add a new one there but essentially it's
14:03
not free to use but don't worry it's not
14:04
like you're not paying anywhere near
14:06
dollars if we go to billing history for
14:08
me it was like a couple cents or uh was
14:10
it usage so if I go to usage limits I
14:12
was messing around this yesterday I
14:14
spent 15 cents on this after a couple
14:16
dozen commands on this account in
14:19
particular so like I said it's really
14:21
not going to cost you basically anything
14:23
at all but I highly recommend still go
14:24
to usage limits and add your own limit
14:26
on there hard limit's going to be like
14:28
do not spend more than this amount just
14:30
in case you send it on like full
14:32
autonomous mode and iterates like a
14:34
million times you don't want to end up
14:36
spending more than you expected and the
14:38
soft limit is going to email you when
14:39
you get to that limit just so you have
14:41
an idea of where you are so you don't
14:42
accidentally terminate like some big you
14:45
know Loop that you don't want to
14:46
terminate so that's nice to have the
14:48
soft limit as well but right now like I
Running AutoGPT
14:50
said I'm only 15 cents in so it's going
14:52
to take a while to get anywhere near
14:53
those limits all right so now let's go
14:55
back to terminal and we want to activate
14:57
that environment we made a while ago
14:58
remember we did the conda activate so
15:00
I'm just going to type in conda activate
15:03
Auto GPT so I'm going to hit enter
15:05
that'll activate that and now in the
15:07
beginning instead of saying base it'll
15:08
say Auto GPT so we're in this new
15:10
environment and now there's one last
15:12
thing we need to do before we can start
15:13
using Auto GPT and this is agree to the
15:16
licenses so in order to do that you
15:18
simply need to type sudo Space X code
15:22
build space Dash license and hit enter
15:25
and it's going to ask for your your
15:27
password that is the password for your
15:28
computer so I'm just going to type that
15:30
in and now it's going to ask us to press
15:32
the return key to view the license
15:34
agreement and we're going to keep
15:35
pressing this until we press spacebar
15:37
until we get to the bottom so you can
15:39
read through all this this is the
15:40
license agreement for what you're doing
15:42
and at the end you can type in agree
15:45
type in agree and we'll be ready to go
15:47
so now we're able to run auto GPS so
15:49
we're ready to go now if you go back to
15:51
the readme it tells you to run uh to say
15:54
dot slash run dot sh space start you
15:58
probably don't actually want to do that
15:59
instead you could just type in like
16:01
forget the word start and just run it
16:03
like this and it should be running
16:04
chanchi or it should be running Auto GPT
16:07
you have your API if everything goes
16:09
according to plan this will be running
16:11
and it'll prompt you in just a minute to
16:13
ask a couple fundamental questions like
16:15
what is the name and what are the goals
16:17
of your auto GPT alright and there we go
16:19
once you see this color text you'll know
16:21
that you are ready to go we're using
16:23
Auto GPT now and so it wants to know
16:25
first of all what the name is I'm just
16:27
going to call this one micbot but again
16:29
you can use this for many different
16:30
things you can search other examples of
16:33
people that used it to make an assistant
16:34
to to plan a wedding to do things like
16:36
that so let's do this I'm going to
16:38
create a new document we're going to say
16:39
file save as so I'm just going to save
16:41
this called diet and we want this to be
16:43
plain text Dot so dot txt let's save it
16:46
and
16:48
we're going to
16:51
say okay now we have just regular
16:53
document called diet it's a plain text
16:54
file so in Auto GPT we can say the AI
16:57
name this is going to be Mike Mike's
17:00
nutritionist Mike's diet or nutritionist
17:05
now it's going to ask us to Define it so
17:07
that describe the role we're going to
17:08
say create a meal plan
17:12
for this week
17:14
and so I'm just going to say let's
17:16
create a 70 meal plan we want to write
17:18
the recipes for each one and at the end
17:20
we want to just save to the file and
17:22
then stop and if we only have three
17:23
goals instead of five you just hit enter
17:25
again and it'll start running this is
17:27
using local memory by the way you could
17:29
pay and use pine cone or some of the
17:30
other ones to not need local memory but
17:33
obviously for something like this local
17:34
memory is just fine
17:36
now the way this works is it'll run
17:38
through one prompt at a time so it'll
17:40
tell you that first of all this is what
17:42
it thinks it's supposed to do it should
17:43
start looking up healthy meal plans for
17:44
the week the reasoning it's going to
17:46
tell you why it's doing this the
17:47
criticism maybe what it doesn't want to
17:49
do and then it'll tell you what it's
17:51
going to do next and we could just say
17:53
why for yes to mean to go ahead and do
17:55
it n is going to be no meaning don't do
17:57
it it's going to exit the program or you
17:59
can add your own feedback in there as
18:01
well I'm just going to say why and let
18:02
it run and right now you can see right
18:04
there Google returns so it's actually
18:06
searching on Google right now to find
18:07
some results from the internet so the
18:09
first thing it wants to know what
18:10
dietary restrictions or preferences they
18:12
have so I'm going to say I have no
18:16
dietary restrictions
18:19
I love Mexican and Asian food as well as
18:25
American
18:28
food I have
18:31
plenty of vegetables
18:33
okay so there we go just give it some
18:35
feedback that's what he was asking so it
18:37
said like before we proceed he needs to
18:38
know any dietary restrictions or what it
18:40
wants for the meal plan or what I want
18:42
for the meal plan
18:43
it's gonna ask me about each meal as we
18:45
go along and so yeah stir fry sounds
18:47
good I love some stir fry for Tuesday
18:49
how about make some tacos we can use
18:51
ground turkey let's say let's use
18:54
shredded
18:56
chicken so you could say like yeah I
18:58
like tacos but let's change that I don't
19:00
actually want ground turkey uh let's do
19:02
something else so you don't always have
19:03
to say why or n for yes or no on these
19:05
things you can give some other feedback
19:07
and it'll kind of iterate and keep
19:09
making your your diet plan around that
19:11
so let's see great we can use shredded
19:13
chicken yeah no problem so now we're
19:15
gonna go on to the next thing press Y
19:16
and it's going to kind of keep iterating
19:18
on this and it should hopefully make my
19:20
diet by the end
19:21
now there now if you get tired of
19:24
pressing y every time or giving it
19:26
feedback like this there are also fully
19:29
autonomous ways to do this so if you go
19:31
into the readme so let me just open it
19:33
up real quick while it's running you can
19:35
go to down down near the bottom just
19:37
look for like a little skull emoji
19:38
because they tell you it's dangerous but
19:40
I'm still interested in doing it and
19:42
[Music]
19:46
there we go continuous mode so right
19:47
here you can actually run in continuous
19:49
mode here it'll iterate continuously
19:51
until you press Ctrl C so obviously like
19:54
this said it could get stuck in Loops it
19:56
could do things that you don't want it
19:57
to do so definitely be careful with this
20:00
um but again you don't always have to
20:02
press y if you set up continuous mode
20:04
I'm not recommending you do that but
20:06
I might end up doing that just it's
20:08
interesting I don't know and by the way
20:10
in case you ever get stuck in a loop on
20:12
here or if it's running something and
20:14
it's stuck it it's not you have some
20:15
kind of error and it doesn't actually
20:16
stop you can terminate any of these by
20:18
saying Ctrl C this is on Mac if you're
20:22
on Windows I don't think it's
20:23
controlling against alt but it's a
20:24
control C and it's going to quit we can
20:26
hit any key and we're back to where we
20:28
were and if you want to run it again you
20:30
can just go press the up key to the most
20:31
recent command which was dot slash
20:33
run.sh hit enter and it's going to run
20:36
it again and we'll be able to start off
20:37
again with a brand new auto GPT all you
20:40
have to do down here it's going to ask
20:41
if you want to continue you just press
20:43
the letter n and you'll go from scratch
20:45
so now it found a diet it's going to
20:47
write that to the document sometimes it
20:49
takes a minute to think it's a little
20:51
bit slower if a lot of people are on it
20:52
you can go and check the uptime and you
20:54
can check basically the status of open
20:55
ai's chat gbt there's a nice website for
20:58
that as well if it's ever not working
21:00
maybe that would be a reason otherwise
21:02
if you ever have any bugs in this if
21:04
anything ever doesn't work you should be
21:07
getting like I said you could hit Ctrl C
21:08
that'll terminate this if it gets stuck
21:10
on thinking for too long and you could
21:12
debug it using chat GPT it's one of the
21:14
greatest tools out there especially if
21:16
you don't know what you're doing you
21:18
just copy the error code onto chat GPT
21:20
tell it what you're trying to do ask why
21:23
it's not working and it can walk you
21:24
through things surprisingly well in
21:26
plain English I found this works
21:28
tremendously well on many different
21:30
programs out there that you find on
21:31
GitHub that maybe have a bug or you know
21:33
something's not right with them so I'm
21:35
editing the video right now and I
21:36
realized I used a really simple example
21:38
here so you might be wondering how this
21:40
is even different from regular chat GPT
21:42
like I could ask Chad gbt to make me a
21:45
diet plan and it could do something
21:46
pretty similar to this so really the
21:48
benefit of Auto GPT is that it connects
21:50
and integrates with different apis
21:52
different things as well so you could
21:54
add into this use my voice like you can
21:57
use a plugin and use my voice to speak
21:59
it to me you could translate videos you
22:01
could output images there's a lot of
22:04
different things you can connect with
22:05
this so that's really where the power of
22:06
Auto GPT is and so as you start to like
22:09
this is a great first example and I
22:10
recommend you do this just so you get
22:13
Auto GPT running and start getting used
22:15
to it and mess around with little you
22:16
know some little commands like this but
22:18
eventually what you want to do is start
22:19
using those Integrations so you can
22:22
really get this to the next level in
22:23
addition this can also do things like
22:25
write to text files do you know do a lot
22:27
more that auto that chat GPT cannot so
22:30
chat GPT is purely on the Internet it's
22:32
stuck there like what you're doing on
22:34
that interface you're just going to get
22:35
text output whereas this like I said can
22:37
change files can do things on your
22:39
computer it can output different files
22:41
as well whether they're audio files that
22:43
are recordings of a like an AI simulated
22:46
version of your voice or images there's
22:49
a lot more you can do with this this is
22:51
really only the beginning but I mean I
22:54
just wanted to clarify that in case
22:55
you're watching this video and wondering
22:57
how this was even different from chat
22:59
GPT and of course it's able to access
23:01
the internet while also accessing chat
23:03
GPT so it's kind of a nice bridge
23:05
between chat GP T and the internet so
23:07
you can find more relevant and more
23:09
recent information so that is my
23:12
tutorial on how to use Auto GPT it's
23:14
really just the tip of the iceberg here
23:16
this is a massive software and you can
23:18
do a lot of automations so I highly
23:19
encourage you start messing around with
23:21
that and please leave a comment Down
23:22
Below on this video and let me know what
23:25
you would use Auto GPT for I really I'm
23:27
always interested are you using it for a
23:29
personal assistant are you using it to
23:31
emulate your voice and you know open
23:34
images and do different things there's
23:35
really Endless Options that you could do
23:37
so I would love to hear what your
23:39
thoughts are on the best uses for auto
23:40
GPT and once again if you guys want to
23:42
keep up with the latest here anything
23:44
that changes with auto GPT we will be
23:46
covering in that newsletter which is
23:48
linked down below if you enjoyed the
23:50
video consider liking and subscribing
23:52
I'm Mike O'Brien thanks for watching and
23:54
we'll see you in the next one
SHOW MORE
68,664 views 24 Apr 2023
In this video, I show you how to use the latest breakthrough in AI innovation, AutoGPT. This is a step by step tutorial.
🧠 The world's leading AI newsletter: https://neuralfrontier.beehiiv.com/su...
AutoGPT Github: https://github.com/Significant-Gravit...
Download Python: https://www.anaconda.com/
Download VisualStudio Code: https://code.visualstudio.com/
Find your OpenAI API Keys: https://platform.openai.com/account/a...
Add OpenAI Billing: https://platform.openai.com/account/b...
🏦 Form your LLC: https://santrelmedia.com/incfile
💻 Create a website on Squarespace: https://santrelmedia.com/squarespace
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⏰ Double your productivity with this software: https://santrelmedia.com/Productivity
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SUBSCRIBE: / santrelmedia
Summary of steps:
Install anaconda
Install visual code
Open terminal
Download stable not master from github
In command line, navigate to the folder, then type “conda create -n auto-gpt python=3.8”
Then cd into the auto gpt master folder which was downloaded from GITHUB
Open visual studio code, cmnd+n to open new, then cmnd+shift+p for command palette
Type “shell” then select install to path
Type “code .” in terminal to open VS code
Save workspace as
This will install your environment, then you can activate it with “conda activate auto-gpt”
In terminal, type “pip install -r requirements.txt”
Open readme.md then right click tab and open preview
Type cp .env.template .env
Then type code .
Open .env in VScode
Copy and paste your API from https://platform.openai.com/account/a...
Remove hash for Use Mac
Save it
In Terminal, type “sudo xcodebuild -license”
Enter your pw
agree
Add billing to https://platform.openai.com/account/b...
In Terminal, type ./run.sh
Customize your auto-gpt!
Some Terminal commands you may want to know:
Cd [navigates to the folder path you type next]
Cd .. [goes back one]
Ls [lists everything in the current folder]
Python [opens python]
quit() [quits python]
Clear [deletes everything on the screen]
TIMESTAMPS:
0:00 What is AutoGPT?
2:50 What do I need to run AutoGPT?
4:13 Getting started
5:45 Downloading Python and VisualStudio Code
7:05 Configuring in Terminal
9:10 Reading the ReadMe markdown file
10:45 Adding your OpenAI API key
14:50 Running AutoGPT
DISCLAIMER: This video and description contains affiliate links, which means that if you click on one of the product links, I’ll receive a small commission. This helps support the channel and allows us to continue to make videos like this. Thank you for the support! Everything in this video is based on information we learned from online resources, our own experience, and books we have read. Please do your own research before making any important decisions. You and only you are responsible for any and all digital marketing decisions you make. Thank you for watching!
ChatGPT API in JavaScript for Beginners - AI Chatbot Tutorial
Ultimate Guide To Auto-GPTs in a Browser
Ultimate Guide To Auto-GPTs in a Browser
AI-driven virtual assistant with ASR, ChatGPT, TTS, Audio2face & Metahuman.
AI-driven virtual assistant with ASR, ChatGPT, TTS, Audio2face & Metahuman.
MASTER Auto-GPT
MASTER Auto-GPT in under 60 MINUTES | Ultimate Guide
AutoGPT: Turn GPT-4 Into A Powerful Self Learning AI
Auto-GPT: An Autonomous GPT-4 Experiment
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Auto-GPT: An Autonomous GPT-4 Experiment
🔴 🔴 🔴 Urgent: USE stable not master 🔴 🔴 🔴
Download the latest stable release from here: https://github.com/Significant-Gravitas/Auto-GPT/releases/latest.
The master branch may often be in a broken state.
Auto-GPT is an experimental open-source application showcasing the capabilities of the GPT-4 language model. This program, driven by GPT-4, chains together LLM "thoughts", to autonomously achieve whatever goal you set. As one of the first examples of GPT-4 running fully autonomously, Auto-GPT pushes the boundaries of what is possible with AI.
Demo April 16th 2023
Auto-GPT
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Print the current Git branch on startup - warn if unsupported
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ALL 5 STAR AI.IO PAGE STUDY
How AI and IoT are Creating An Impact On Industries Today
HELLO AND WELCOME TO THE
5 STAR AI.IOT TOOLS FOR YOUR BUSINESS
ARE NEW WEBSITE IS ABOUT 5 STAR AI and io’t TOOLS on the net.
We prevaid you the best
Artificial Intelligence tools and services that can be used to create and improve BUSINESS websites AND CHANNELS .
This site is includes tools for creating interactive visuals, animations, and videos.
as well as tools for SEO, marketing, and web development.
It also includes tools for creating and editing text, images, and audio. The website is intended to provide users with a comprehensive list of AI-based tools to help them create and improve their business.
https://studio.d-id.com/share?id=078f9242d5185a9494e00852e89e17f7&utm_source=copy
This website is a collection of Artificial Intelligence (AI) tools and services that can be used to create and improve websites. It includes tools for creating interactive visuals, animations, and videos, as well as tools for SEO, marketing, and web development. It also includes tools for creating and editing text, images, and audio. The website is intended to provide users with a comprehensive list of AI-based tools to help them create and improve their websites.
אתר זה הוא אוסף של כלים ושירותים של בינה מלאכותית (AI) שניתן להשתמש בהם כדי ליצור ולשפר אתרים. הוא כולל כלים ליצירת ויזואליה אינטראקטיבית, אנימציות וסרטונים, כמו גם כלים לקידום אתרים, שיווק ופיתוח אתרים. הוא כולל גם כלים ליצירה ועריכה של טקסט, תמונות ואודיו. האתר נועד לספק למשתמשים רשימה מקיפה של כלים מבוססי AI שיסייעו להם ליצור ולשפר את אתרי האינטרנט שלהם.
Hello and welcome to our new site that shares with you the most powerful web platforms and tools available on the web today
All platforms, websites and tools have artificial intelligence AI and have a 5-star rating
All platforms, websites and tools are free and Pro paid
The platforms, websites and the tool's are the best for growing your business in 2022/3
שלום וברוכים הבאים לאתר החדש שלנו המשתף אתכם בפלטפורמות האינטרנט והכלים החזקים ביותר הקיימים היום ברשת. כל הפלטפורמות, האתרים והכלים הם בעלי בינה מלאכותית AI ובעלי דירוג של 5 כוכבים. כל הפלטפורמות, האתרים והכלים חינמיים ומקצועיים בתשלום הפלטפורמות, האתרים והכלים באתר זה הם הטובים ביותר והמועילים ביותר להצמחת ולהגדלת העסק שלך ב-2022/3
A Guide for AI-Enhancing Your Existing Business Application
A guide to improving your existing business application of artificial intelligence
מדריך לשיפור היישום העסקי הקיים שלך בינה מלאכותית
What is Artificial Intelligence and how does it work? What are the 3 types of AI?
What is Artificial Intelligence and how does it work? What are the 3 types of AI? The 3 types of AI are: General AI: AI that can perform all of the intellectual tasks a human can. Currently, no form of AI can think abstractly or develop creative ideas in the same ways as humans. Narrow AI: Narrow AI commonly includes visual recognition and natural language processing (NLP) technologies. It is a powerful tool for completing routine jobs based on common knowledge, such as playing music on demand via a voice-enabled device. Broad AI: Broad AI typically relies on exclusive data sets associated with the business in question. It is generally considered the most useful AI category for a business. Business leaders will integrate a broad AI solution with a specific business process where enterprise-specific knowledge is required. How can artificial intelligence be used in business? AI is providing new ways for humans to engage with machines, transitioning personnel from pure digital experiences to human-like natural interactions. This is called cognitive engagement. AI is augmenting and improving how humans absorb and process information, often in real-time. This is called cognitive insights and knowledge management. Beyond process automation, AI is facilitating knowledge-intensive business decisions, mimicking complex human intelligence. This is called cognitive automation. What are the different artificial intelligence technologies in business? Machine learning, deep learning, robotics, computer vision, cognitive computing, artificial general intelligence, natural language processing, and knowledge reasoning are some of the most common business applications of AI. What is the difference between artificial intelligence and machine learning and deep learning? Artificial intelligence (AI) applies advanced analysis and logic-based techniques, including machine learning, to interpret events, support and automate decisions, and take actions. Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Deep learning is a subset of machine learning in artificial intelligence (AI) that has networks capable of learning unsupervised from data that is unstructured or unlabeled. What are the current and future capabilities of artificial intelligence? Current capabilities of AI include examples such as personal assistants (Siri, Alexa, Google Home), smart cars (Tesla), behavioral adaptation to improve the emotional intelligence of customer support representatives, using machine learning and predictive algorithms to improve the customer’s experience, transactional AI like that of Amazon, personalized content recommendations (Netflix), voice control, and learning thermostats. Future capabilities of AI might probably include fully autonomous cars, precision farming, future air traffic controllers, future classrooms with ambient informatics, urban systems, smart cities and so on. To know more about the scope of artificial intelligence in your business, please connect with our expert.
מהי בינה מלאכותית וכיצד היא פועלת? מהם 3 סוגי הבינה המלאכותית?
מהי בינה מלאכותית וכיצד היא פועלת? מהם 3 סוגי הבינה המלאכותית? שלושת סוגי הבינה המלאכותית הם: בינה מלאכותית כללית: בינה מלאכותית שיכולה לבצע את כל המשימות האינטלקטואליות שאדם יכול. נכון לעכשיו, שום צורה של AI לא יכולה לחשוב בצורה מופשטת או לפתח רעיונות יצירתיים באותן דרכים כמו בני אדם. בינה מלאכותית צרה: בינה מלאכותית צרה כוללת בדרך כלל טכנולוגיות זיהוי חזותי ועיבוד שפה טבעית (NLP). זהו כלי רב עוצמה להשלמת עבודות שגרתיות המבוססות על ידע נפוץ, כגון השמעת מוזיקה לפי דרישה באמצעות מכשיר התומך בקול. בינה מלאכותית רחבה: בינה מלאכותית רחבה מסתמכת בדרך כלל על מערכי נתונים בלעדיים הקשורים לעסק המדובר. זה נחשב בדרך כלל לקטגוריית הבינה המלאכותית השימושית ביותר עבור עסק. מנהיגים עסקיים ישלבו פתרון AI רחב עם תהליך עסקי ספציפי שבו נדרש ידע ספציפי לארגון. כיצד ניתן להשתמש בבינה מלאכותית בעסק? AI מספקת דרכים חדשות לבני אדם לעסוק במכונות, ומעבירה את הצוות מחוויות דיגיטליות טהורות לאינטראקציות טבעיות דמויות אדם. זה נקרא מעורבות קוגניטיבית. בינה מלאכותית מגדילה ומשפרת את האופן שבו בני אדם קולטים ומעבדים מידע, לעתים קרובות בזמן אמת. זה נקרא תובנות קוגניטיביות וניהול ידע. מעבר לאוטומציה של תהליכים, AI מאפשר החלטות עסקיות עתירות ידע, תוך חיקוי אינטליגנציה אנושית מורכבת. זה נקרא אוטומציה קוגניטיבית. מהן טכנולוגיות הבינה המלאכותית השונות בעסק? למידת מכונה, למידה עמוקה, רובוטיקה, ראייה ממוחשבת, מחשוב קוגניטיבי, בינה כללית מלאכותית, עיבוד שפה טבעית וחשיבת ידע הם חלק מהיישומים העסקיים הנפוצים ביותר של AI. מה ההבדל בין בינה מלאכותית ולמידת מכונה ולמידה עמוקה? בינה מלאכותית (AI) מיישמת ניתוח מתקדמות וטכניקות מבוססות לוגיקה, כולל למידת מכונה, כדי לפרש אירועים, לתמוך ולהפוך החלטות לאוטומטיות ולנקוט פעולות. למידת מכונה היא יישום של בינה מלאכותית (AI) המספק למערכות את היכולת ללמוד ולהשתפר מניסיון באופן אוטומטי מבלי להיות מתוכנתים במפורש. למידה עמוקה היא תת-קבוצה של למידת מכונה בבינה מלאכותית (AI) שיש לה רשתות המסוגלות ללמוד ללא פיקוח מנתונים שאינם מובנים או ללא תווית. מהן היכולות הנוכחיות והעתידיות של בינה מלאכותית? היכולות הנוכחיות של AI כוללות דוגמאות כמו עוזרים אישיים (Siri, Alexa, Google Home), מכוניות חכמות (Tesla), התאמה התנהגותית לשיפור האינטליגנציה הרגשית של נציגי תמיכת לקוחות, שימוש בלמידת מכונה ואלגוריתמים חזויים כדי לשפר את חווית הלקוח, עסקאות בינה מלאכותית כמו זו של אמזון, המלצות תוכן מותאמות אישית (Netflix), שליטה קולית ותרמוסטטים ללמידה. יכולות עתידיות של AI עשויות לכלול כנראה מכוניות אוטונומיות מלאות, חקלאות מדויקת, בקרי תעבורה אוויריים עתידיים, כיתות עתידיות עם אינפורמטיקה סביבתית, מערכות עירוניות, ערים חכמות וכן הלאה. כדי לדעת יותר על היקף הבינה המלאכותית בעסק שלך, אנא צור קשר עם המומחה שלנו.
Glossary of Terms
Application Programming Interface(API):
An API, or application programming interface, is a set of rules and protocols that allows different software programs to communicate and exchange information with each other. It acts as a kind of intermediary, enabling different programs to interact and work together, even if they are not built using the same programming languages or technologies. API's provide a way for different software programs to talk to each other and share data, helping to create a more interconnected and seamless user experience.
Artificial Intelligence(AI):
the intelligence displayed by machines in performing tasks that typically require human intelligence, such as learning, problem-solving, decision-making, and language understanding. AI is achieved by developing algorithms and systems that can process, analyze, and understand large amounts of data and make decisions based on that data.
Compute Unified Device Architecture(CUDA):
CUDA is a way that computers can work on really hard and big problems by breaking them down into smaller pieces and solving them all at the same time. It helps the computer work faster and better by using special parts inside it called GPUs. It's like when you have lots of friends help you do a puzzle - it goes much faster than if you try to do it all by yourself.
The term "CUDA" is a trademark of NVIDIA Corporation, which developed and popularized the technology.
Data Processing:
The process of preparing raw data for use in a machine learning model, including tasks such as cleaning, transforming, and normalizing the data.
Deep Learning(DL):
A subfield of machine learning that uses deep neural networks with many layers to learn complex patterns from data.
Feature Engineering:
The process of selecting and creating new features from the raw data that can be used to improve the performance of a machine learning model.
Freemium:
You might see the term "Freemium" used often on this site. It simply means that the specific tool that you're looking at has both free and paid options. Typically there is very minimal, but unlimited, usage of the tool at a free tier with more access and features introduced in paid tiers.
Generative Art:
Generative art is a form of art that is created using a computer program or algorithm to generate visual or audio output. It often involves the use of randomness or mathematical rules to create unique, unpredictable, and sometimes chaotic results.
Generative Pre-trained Transformer(GPT):
GPT stands for Generative Pretrained Transformer. It is a type of large language model developed by OpenAI.
GitHub:
GitHub is a platform for hosting and collaborating on software projects
Google Colab:
Google Colab is an online platform that allows users to share and run Python scripts in the cloud
Graphics Processing Unit(GPU):
A GPU, or graphics processing unit, is a special type of computer chip that is designed to handle the complex calculations needed to display images and video on a computer or other device. It's like the brain of your computer's graphics system, and it's really good at doing lots of math really fast. GPUs are used in many different types of devices, including computers, phones, and gaming consoles. They are especially useful for tasks that require a lot of processing power, like playing video games, rendering 3D graphics, or running machine learning algorithms.
Large Language Model(LLM):
A type of machine learning model that is trained on a very large amount of text data and is able to generate natural-sounding text.
Machine Learning(ML):
A method of teaching computers to learn from data, without being explicitly programmed.
Natural Language Processing(NLP):
A subfield of AI that focuses on teaching machines to understand, process, and generate human language
Neural Networks:
A type of machine learning algorithm modeled on the structure and function of the brain.
Neural Radiance Fields(NeRF):
Neural Radiance Fields are a type of deep learning model that can be used for a variety of tasks, including image generation, object detection, and segmentation. NeRFs are inspired by the idea of using a neural network to model the radiance of an image, which is a measure of the amount of light that is emitted or reflected by an object.
OpenAI:
OpenAI is a research institute focused on developing and promoting artificial intelligence technologies that are safe, transparent, and beneficial to society
Overfitting:
A common problem in machine learning, in which the model performs well on the training data but poorly on new, unseen data. It occurs when the model is too complex and has learned too many details from the training data, so it doesn't generalize well.
Prompt:
A prompt is a piece of text that is used to prime a large language model and guide its generation
Python:
Python is a popular, high-level programming language known for its simplicity, readability, and flexibility (many AI tools use it)
Reinforcement Learning:
A type of machine learning in which the model learns by trial and error, receiving rewards or punishments for its actions and adjusting its behavior accordingly.
Spatial Computing:
Spatial computing is the use of technology to add digital information and experiences to the physical world. This can include things like augmented reality, where digital information is added to what you see in the real world, or virtual reality, where you can fully immerse yourself in a digital environment. It has many different uses, such as in education, entertainment, and design, and can change how we interact with the world and with each other.
Stable Diffusion:
Stable Diffusion generates complex artistic images based on text prompts. It’s an open source image synthesis AI model available to everyone. Stable Diffusion can be installed locally using code found on GitHub or there are several online user interfaces that also leverage Stable Diffusion models.
Supervised Learning:
A type of machine learning in which the training data is labeled and the model is trained to make predictions based on the relationships between the input data and the corresponding labels.
Unsupervised Learning:
A type of machine learning in which the training data is not labeled, and the model is trained to find patterns and relationships in the data on its own.
Webhook:
A webhook is a way for one computer program to send a message or data to another program over the internet in real-time. It works by sending the message or data to a specific URL, which belongs to the other program. Webhooks are often used to automate processes and make it easier for different programs to communicate and work together. They are a useful tool for developers who want to build custom applications or create integrations between different software systems.
מילון מונחים
ממשק תכנות יישומים (API): API, או ממשק תכנות יישומים, הוא קבוצה של כללים ופרוטוקולים המאפשרים לתוכנות שונות לתקשר ולהחליף מידע ביניהן. הוא פועל כמעין מתווך, המאפשר לתוכניות שונות לקיים אינטראקציה ולעבוד יחד, גם אם הן אינן בנויות באמצעות אותן שפות תכנות או טכנולוגיות. ממשקי API מספקים דרך לתוכנות שונות לדבר ביניהן ולשתף נתונים, ועוזרות ליצור חווית משתמש מקושרת יותר וחלקה יותר. בינה מלאכותית (AI): האינטליגנציה שמוצגת על ידי מכונות בביצוע משימות הדורשות בדרך כלל אינטליגנציה אנושית, כגון למידה, פתרון בעיות, קבלת החלטות והבנת שפה. AI מושגת על ידי פיתוח אלגוריתמים ומערכות שיכולים לעבד, לנתח ולהבין כמויות גדולות של נתונים ולקבל החלטות על סמך הנתונים הללו. Compute Unified Device Architecture (CUDA): CUDA היא דרך שבה מחשבים יכולים לעבוד על בעיות קשות וגדולות באמת על ידי פירוקן לחתיכות קטנות יותר ופתרון כולן בו זמנית. זה עוזר למחשב לעבוד מהר יותר וטוב יותר על ידי שימוש בחלקים מיוחדים בתוכו הנקראים GPUs. זה כמו כשיש לך הרבה חברים שעוזרים לך לעשות פאזל - זה הולך הרבה יותר מהר מאשר אם אתה מנסה לעשות את זה לבד. המונח "CUDA" הוא סימן מסחרי של NVIDIA Corporation, אשר פיתחה והפכה את הטכנולוגיה לפופולרית. עיבוד נתונים: תהליך הכנת נתונים גולמיים לשימוש במודל למידת מכונה, כולל משימות כמו ניקוי, שינוי ונימול של הנתונים. למידה עמוקה (DL): תת-תחום של למידת מכונה המשתמש ברשתות עצביות עמוקות עם רבדים רבים כדי ללמוד דפוסים מורכבים מנתונים. הנדסת תכונות: תהליך הבחירה והיצירה של תכונות חדשות מהנתונים הגולמיים שניתן להשתמש בהם כדי לשפר את הביצועים של מודל למידת מכונה. Freemium: ייתכן שתראה את המונח "Freemium" בשימוש לעתים קרובות באתר זה. זה פשוט אומר שלכלי הספציפי שאתה מסתכל עליו יש אפשרויות חינמיות וגם בתשלום. בדרך כלל יש שימוש מינימלי מאוד, אך בלתי מוגבל, בכלי בשכבה חינמית עם יותר גישה ותכונות שהוצגו בשכבות בתשלום. אמנות גנרטיבית: אמנות גנרטיבית היא צורה של אמנות שנוצרת באמצעות תוכנת מחשב או אלגוריתם ליצירת פלט חזותי או אודיו. לרוב זה כרוך בשימוש באקראיות או בכללים מתמטיים כדי ליצור תוצאות ייחודיות, בלתי צפויות ולעיתים כאוטיות. Generative Pre-trained Transformer(GPT): GPT ראשי תיבות של Generative Pre-trained Transformer. זהו סוג של מודל שפה גדול שפותח על ידי OpenAI. GitHub: GitHub היא פלטפורמה לאירוח ושיתוף פעולה בפרויקטי תוכנה
Google Colab: Google Colab היא פלטפורמה מקוונת המאפשרת למשתמשים לשתף ולהריץ סקריפטים של Python בענן Graphics Processing Unit(GPU): GPU, או יחידת עיבוד גרפית, הוא סוג מיוחד של שבב מחשב שנועד להתמודד עם המורכבות חישובים הדרושים להצגת תמונות ווידאו במחשב או במכשיר אחר. זה כמו המוח של המערכת הגרפית של המחשב שלך, והוא ממש טוב לעשות הרבה מתמטיקה ממש מהר. GPUs משמשים סוגים רבים ושונים של מכשירים, כולל מחשבים, טלפונים וקונסולות משחקים. הם שימושיים במיוחד למשימות הדורשות כוח עיבוד רב, כמו משחקי וידאו, עיבוד גרפיקה תלת-ממדית או הפעלת אלגוריתמים של למידת מכונה. מודל שפה גדול (LLM): סוג של מודל למידת מכונה שאומן על כמות גדולה מאוד של נתוני טקסט ומסוגל ליצור טקסט בעל צליל טבעי. Machine Learning (ML): שיטה ללמד מחשבים ללמוד מנתונים, מבלי להיות מתוכנתים במפורש. עיבוד שפה טבעית (NLP): תת-תחום של AI המתמקד בהוראת מכונות להבין, לעבד וליצור שפה אנושית רשתות עצביות: סוג של אלגוריתם למידת מכונה המבוססת על המבנה והתפקוד של המוח. שדות קרינה עצביים (NeRF): שדות קרינה עצביים הם סוג של מודל למידה עמוקה שיכול לשמש למגוון משימות, כולל יצירת תמונה, זיהוי אובייקטים ופילוח. NeRFs שואבים השראה מהרעיון של שימוש ברשת עצבית למודל של זוהר תמונה, שהוא מדד לכמות האור שנפלט או מוחזר על ידי אובייקט. OpenAI: OpenAI הוא מכון מחקר המתמקד בפיתוח וקידום טכנולוגיות בינה מלאכותית שהן בטוחות, שקופות ומועילות לחברה. Overfitting: בעיה נפוצה בלמידת מכונה, שבה המודל מתפקד היטב בנתוני האימון אך גרועים בחדשים, בלתי נראים. נתונים. זה מתרחש כאשר המודל מורכב מדי ולמד יותר מדי פרטים מנתוני האימון, כך שהוא לא מכליל היטב. הנחיה: הנחיה היא פיסת טקסט המשמשת לתכנון מודל שפה גדול ולהנחות את הדור שלו Python: Python היא שפת תכנות פופולרית ברמה גבוהה הידועה בפשטות, בקריאות ובגמישות שלה (כלי AI רבים משתמשים בה) למידת חיזוק: סוג של למידת מכונה שבה המודל לומד על ידי ניסוי וטעייה, מקבל תגמולים או עונשים על מעשיו ומתאים את התנהגותו בהתאם. מחשוב מרחבי: מחשוב מרחבי הוא השימוש בטכנולוגיה כדי להוסיף מידע וחוויות דיגיטליות לעולם הפיזי. זה יכול לכלול דברים כמו מציאות רבודה, שבה מידע דיגיטלי מתווסף למה שאתה רואה בעולם האמיתי, או מציאות מדומה, שבה אתה יכול לשקוע במלואו בסביבה דיגיטלית. יש לו שימושים רבים ושונים, כמו בחינוך, בידור ועיצוב, והוא יכול לשנות את האופן שבו אנו מתקשרים עם העולם ואחד עם השני. דיפוזיה יציבה: דיפוזיה יציבה מייצרת תמונות אמנותיות מורכבות המבוססות על הנחיות טקסט. זהו מודל AI של סינתזת תמונות בקוד פתוח הזמין לכולם. ניתן להתקין את ה-Stable Diffusion באופן מקומי באמצעות קוד שנמצא ב-GitHub או שישנם מספר ממשקי משתמש מקוונים הממנפים גם מודלים של Stable Diffusion. למידה מפוקחת: סוג של למידת מכונה שבה נתוני האימון מסומנים והמודל מאומן לבצע תחזיות על סמך היחסים בין נתוני הקלט והתוויות המתאימות. למידה ללא פיקוח: סוג של למידת מכונה שבה נתוני האימון אינם מסומנים, והמודל מאומן למצוא דפוסים ויחסים בנתונים בעצמו. Webhook: Webhook הוא דרך של תוכנת מחשב אחת לשלוח הודעה או נתונים לתוכנית אחרת דרך האינטרנט בזמן אמת. זה עובד על ידי שליחת ההודעה או הנתונים לכתובת URL ספציפית, השייכת לתוכנית האחרת. Webhooks משמשים לעתים קרובות כדי להפוך תהליכים לאוטומטיים ולהקל על תוכניות שונות לתקשר ולעבוד יחד. הם כלי שימושי למפתחים שרוצים לבנות יישומים מותאמים אישית או ליצור אינטגרציות בין מערכות תוכנה שונות.
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