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The best no code mobile app builders in 2023


The best no code mobile app builders in 2023


TRANSCRIPT

PART - 1 

0:00

there are so many different no code app

0:02

Builders out there now does Glide softer

0:05

flutter flow a dollar and so many

0:07

different options out there if I'm being

0:09

honest it's hard to keep track of all of

0:11

them because most of them are shipping

0:13

new features all the freaking time it's

0:16

quite wonderful what are the best no

0:18

code app builder right now though that's

0:20

been a hard question and one that I've

0:22

struggled with in the past few months

0:24

like most tools though it depends on

0:26

your use case in this video I'm going to

0:28

cover three no code app builders that I

0:30

found the most helpful Glide a dollar

0:32

and flutter flow these three no code app

0:35

Builders are mobile focused for the most

0:37

part and I'm going to keep it limited to

0:39

that if you're looking for more of a

0:40

desktop web app softer and bubbler are

0:43

worth checking out I'm not covering

0:45

those two because they are built more

0:46

for desktop web apps so without further

0:48

Ado let's get started by jumping into

0:50

Glide okay so here we are in Glide and

0:53

I've already signed in I'm in my own

0:55

dashboard here and it's pretty simple

0:57

when you log in to Glide which I like so

1:00

what I want to start though is let's say

1:02

we want to create a new project

1:04

supposed to be like a new app so I'm

1:06

going to pick Glide app because we're

1:07

just focusing on these mobile apps here

1:09

in this video so I'm going to do this

1:10

create Matthew's app now here is the

1:13

like the one part that I really really

1:14

like about Glide is that it connects to

1:16

tools that you might be already using

1:18

especially if you've already been

1:19

working with building an MVP or a

1:20

minimum viable product with Google

1:22

Sheets airtable or Excel now for me I

1:25

have a tendency to build stuff an air

1:26

table first and then kind of go from

1:28

there

1:29

um so but the nice thing though is

1:30

you're if you're building a really clean

1:32

air tool base a really clean Google

1:34

Sheets and like data is really clean

1:36

putting all that and connecting that to

1:38

Glide is really easy it makes your life

1:40

a lot easier in terms of building it the

1:42

app and glide because if you want to

1:44

think of Glide as the front end and then

1:46

you can think of airtable Google Sheets

1:48

Excel as your back end so in this

1:51

example though I'm not going to connect

1:52

it to anything I'm just going to use the

1:53

Glide tables which is like where you can

1:55

build out originally and you can even

1:57

import things into Glide really nicely

1:59

too so if you like if you want to start

2:01

with glide tables and import things you

2:02

can do that too so I'm going to create a

2:05

project here

2:06

it's going to load up and it's going to

2:07

kind of give me just like this like

2:09

standardized app kind of looking thing

2:11

but you can see though it's pretty

2:13

intuitive I I that's the part that I

2:15

really like about Glide is it's pretty

2:17

natural and it comes as if you're used

2:18

to especially like web Builders like

2:19

Squarespace Wix you know the simple web

2:22

Builders like building and Glides really

2:24

similar

2:25

um it has a little more complexity to it

2:27

but it just it takes a little bit of

2:29

getting used to but naturally though

2:30

comparatively to the other tools we're

2:32

going to talk about I think it has a

2:33

little more intuitiveness so

2:35

there's like all these different styles

2:37

there's these tiles cards checklists

2:40

um like even a swipe function these

2:42

details uh like map function a calendar

2:44

function

2:46

um a list so there's all these different

2:47

things and if let's say you want to

2:48

change like these bottom bars all you

2:50

have to do is you know let's say I want

2:52

to do a chat well then there's here's

2:53

chat then you can even click here and

2:55

like you know add chats and things like

2:57

that which is really cool so it's really

2:59

nice it's really intuitive there's

3:00

different all these different ways right

3:01

you can organize things and it's like

3:03

you can especially if the data is really

3:05

clean really quickly you can build

3:07

things really fast which is awesome okay

3:09

so now we've covered the intuitiveness

3:11

though but the one thing I before we

3:12

jump out of this app is that one I want

3:14

to show you right is this so you can see

3:15

this like data editor this is the back

3:18

end of the app so this is a this is just

3:20

like a Google sheet it's a spreadsheet

3:22

essentially right and here's all the

3:24

different tables and things like that

3:25

and you can edit and then what happens

3:27

right is that Clyde then takes all that

3:29

and just makes it pretty here in these

3:31

app looking function and then you can

3:33

publish it and you can have people check

3:35

it out with this just like link so it's

3:37

a really quick way to spin up apps

3:39

especially if it's a really simple app

3:41

and have people play around with it it

3:43

doesn't one of the cons though of Glide

3:45

is that you can't send stuff to the app

3:48

store which is a little bit of a bummer

3:50

I think there's a legitimacy piece when

3:52

you can push stuff to the App Store yes

3:54

there's hurdles to get into the App

3:55

Store with you know with pricing and the

3:57

amount of time it can take depending on

3:59

which stores you're going towards but

4:01

definitely like I think it's a

4:03

legitimacy part when you're actually

4:04

building an app and launching it for

4:06

real so this works for like just kind of

4:08

getting an MVP and testing things out

4:10

but in terms of like scalability and

4:12

things like that that that's limiting

4:15

um now you can publish the different

4:18

ways to publish a Glide app to the App

4:19

Stores but the one thing that I've read

4:22

and I've seen is that Glide actually

4:23

takes their support away from you if you

4:25

do that because it's not supported um

4:28

Glide doesn't support that going to the

4:29

App Store so

4:31

there's pros and cons to that

4:33

um but I think if you lose support like

4:34

that's a really big deal and I think

4:35

that's like if you're trying to scale up

4:37

with glide I think that's a something to

4:39

be definitely be considering as you're

4:40

moving forward

4:41

but again if you're just kind of testing

4:43

things out I want to see if you have

4:44

something for real

4:45

this works now that we've gotten this

4:47

app I want to actually jump back into

4:49

the dashboard to show a couple other

4:50

things

4:51

um and one is this learned piece and

4:53

actually there's a lot of different

4:54

tutorials and things like that this

4:56

campus for learning Glide is actually

4:58

pretty stinking good so you can see like

5:00

there's different examples you can build

5:02

um how to manage data in Glide and then

5:04

like these like really simple like you

5:07

know kind of intro pieces to Glide so if

5:09

you're looking to learn Glide and maybe

5:11

you know be able to be build a little

5:13

more robustness in your apps like

5:14

definitely this is definitely the place

5:16

to start

5:17

um in terms of like how to learn Glide

5:19

so that's the learning piece of Glide

5:21

the last thing that I want to show you

5:22

in Glide is actually the all the

5:24

different templates that they have so if

5:25

I go back to glideapps.com their web

5:27

page I kind of wish they had templates

5:29

better like this is your own templates I

5:30

wish they had templates is more

5:31

accessible here on this dashboard but

5:33

that's minor but the nice thing right is

5:36

if you go to templates here you can see

5:38

there is so many different templates

5:39

that you can use like a company if you

5:41

want to build your own company CRM an

5:43

inventory tracker

5:45

um you know to simple store task

5:47

trackers you can do all these different

5:49

things right here in the Glide templates

5:51

Gallery so you don't have to be an

5:54

expert in Glide to just pick these up

5:55

it's really nice if you especially if

5:58

you just want to make things pretty

5:58

really quickly maybe you have a really

6:00

nice Airtel base but people don't love

6:01

like the because air table can be a

6:03

little bit complex especially if you

6:05

have some bigger bases these Cloud apps

6:07

can make it a little bit simpler to use

6:09

which is really really nice okay so

6:12

that's Glide let's move into the second

6:14

mobile app builder and that is a dollar

6:16

so here we are in the second app builder

6:19

I want to talk about and that is a

6:20

dollar now a dollar can do desktop and

6:22

Native mobile apps as well but again

6:24

we're going to focus on these mobile

6:26

apps portion so in this I'm going to

6:28

create native mobile app here do that

6:31

and then this is where I kind of like

6:33

Get over Glides that the templates a

6:35

little easier to get to but you don't

6:37

have to go with these templates but

6:39

let's say for just for showing those

6:41

things off I'm going to use this

6:42

appointments one

6:44

so let next and you can do let's say the

6:47

appointments tutorial

6:50

um select like which kind of users are

6:52

so customers in my startup and then I'm

6:54

just going to go up the standard colors

6:56

okay so it's creating the app and this

6:58

is where a dollar is a little more

7:00

complex than Glide right so there's

7:03

always different screens so if you have

7:05

more of a design background and

7:07

especially if you use a tool like maybe

7:08

Adobe XD things like that a dollar might

7:11

come more naturally to you rather than

7:13

link Glide

7:14

um Glide has a more again the the

7:16

Squarespace Wix feel to it where whereas

7:18

a dollar has more of that Designer feel

7:20

to it and you can design everything in

7:23

the Nitty Gritty pieces of it so you can

7:25

see here's all the different options you

7:27

can use the like all these buttons lists

7:29

um you know every little components

7:33

um that are here and that and then you

7:35

can hit add screen but then you have to

7:37

connect everything with you can see all

7:38

the different actions that are flowing

7:39

like if you sign up it's going to send

7:41

you to this it's gonna you're mapping

7:43

all these different things together so

7:45

again it has much for like all these

7:47

different screens are different pages

7:50

that you're building out on your app so

7:53

it has a little more robustness I

7:54

compare it to Glide which I like I think

7:57

it's a little more scalable than like a

7:59

Glide and I think it's where it Glide

8:01

right Glide can be more I think an

8:02

internal tool if you have a or a bigger

8:04

organization and you want to use it as


PART - 2 

8:06

an internal tool I think that's where

8:07

glider really shines where I think a

8:09

dollar can shine is actually more like

8:11

in this room a little more robustness

8:13

especially if you're not Technical and

8:15

like you know maybe you have more

8:17

especially if you have a design

8:18

background a dollar can really get

8:20

things going really quickly too so

8:22

especially since these templates are

8:23

really nice so

8:25

and then if I hit preview right you can

8:27

actually preview the entire app you can

8:29

see what it looks like and they have all

8:31

these different kinds of phones too

8:32

which is kind of nice now so you can see

8:34

what it looks like on those different

8:35

phones

8:37

um it's not great but it works

8:39

um and then you can also share it out

8:40

too right so if it's a previewer it has

8:42

like what the app looks like and you can

8:44

share it there's a little QR code which

8:45

is really cool too so I like that quite

8:48

a bit

8:49

um the database too right so this has

8:51

like you know it's similar to like where

8:54

I think light is right so you can you

8:55

can connect to the airtable Google or

8:57

different maybe sources that you have

8:58

which is awesome you do have to be a

9:00

doing it in the paid in the pro versions

9:02

of adala but that's going to be if

9:04

you're going to do this do this for real

9:06

right you're going to pay for

9:07

description anyways but you can also

9:09

build the data right here in a dollar

9:11

which is cool too so there's that you

9:14

can hit the publish you can see that all

9:15

the different versions that you might

9:17

have published which I think is really

9:18

cool you can also see like right how

9:20

you're developing you can really build a

9:22

product roadmap with a dollar which I

9:23

like I think it's a good thing you can

9:25

see the analytics right here if you're

9:27

especially if you've launched already so

9:29

there's a little more robustness to a

9:31

dollar which I like which is really

9:32

awesome one thing that I want to add to

9:34

you right is these components right so

9:36

there's actually some like really cool

9:38

Marketplace components that you can

9:39

actually buy and they're pretty

9:40

affordable too which I I think is good

9:42

so there's actually like there's free

9:43

ones here so like Google Maps

9:46

um all these like different Apple sign

9:47

in like there's all these different

9:48

things you can build in which isn't

9:50

really nice and then here's all like

9:51

these premium things which for some like

9:53

some of these are kind of silly like why

9:55

would you pay for it but like a loading

9:57

spinner like do you really need a

9:58

loading spinner but maybe it's a big

10:00

part of your design and branding I don't

10:02

know

10:03

um but you know for some of these things

10:04

right it's it's a really big deal you

10:06

want maybe an advanced calendar

10:08

um you know there's certain things that

10:10

might make sense for others which is

10:12

really nice and again you can see it's

10:14

like 25 bucks it's 14 like these are

10:16

pretty affordable features components

10:18

that you can buy which is really cool I

10:20

think it's a really nice component in

10:22

part of a dollar okay and then the other

10:24

thing about a dollar two which is really

10:26

nice and I think this is where it has

10:27

the biggest Edge on glide is that you

10:30

can actually publish to the app stores

10:32

right in a dollar so if you hit publish

10:34

here now I don't have the pro version of

10:36

a dollar here but you can actually just

10:38

hit if you upgrade it then you have an

10:40

Android and iOS and a web app and you

10:42

can publish right in a dollar which is

10:44

really nice so now that we've covered

10:46

publishing we've covered what these like

10:48

the main screens look like here in a

10:49

dollar well I wanted a couple of things

10:51

that I want to just mention lastly

10:52

before moving on to the last tool is

10:54

that a dollar does have their own

10:56

Learning Academy as well so you can see

10:58

the dollar App Academy right here on

11:00

their main website and they have all

11:02

these different courses and there's all

11:04

these different things to learn how to

11:06

build in a dollar so that's a really

11:08

nice piece as well now for the downsides

11:11

of a dollar I think there's a couple

11:12

just to keep in mind but I don't think

11:14

any of them are necessarily deal

11:15

breakers one that I've seen through

11:17

comments and seeing how others have

11:19

launched apps on the dollar is that

11:20

sometimes especially if someone else has

11:23

gone viral maybe with their app and they

11:24

have a lot of user growth and things

11:25

like that it can crash others because

11:28

everyone's using the same databases and

11:30

things like that or at least it's using

11:32

the same server power as maybe your app

11:34

as well and a dollar really hasn't built

11:36

that structure just yet so scaling can

11:38

be a little questionable but I think

11:41

especially if you're launching me this

11:42

is your first app and or maybe you're in

11:44

like this intermediate stage from

11:45

between MVP and like hey we can scale to

11:47

millions of users I think if you're in

11:48

this like 100 to you know a few thousand

11:51

people using it for the first time I

11:53

think a dollar can do it I think just

11:55

keep in mind like right there might be

11:56

some scaling problems with it because

11:57

the dollar is also a startup themselves

12:00

and they're figuring out how to scale so

12:01

I think it's going to be okay but I

12:03

think like I just be aware of it that it

12:05

could happen like your app breaks

12:07

because there's some scaling problems

12:09

the other thing too that I've heard and

12:10

seen in comments and you know from

12:12

different places and reviews is that

12:13

sometimes the support team of a dollar

12:15

can be a little bit lackluster so again

12:18

keep this in mind when you're scaling up

12:20

and just be able to support I think be

12:22

ready to support your own stuff on adalo

12:24

and don't bet on the customer support

12:26

team just get with the dollar but again

12:27

like I mentioned at the very very

12:29

beginning this video These appealers are

12:32

changing like so fast like the support

12:34

team might look way different in even a

12:36

month from this video it might be

12:37

outdated so

12:38

but so far like I really like a dollar I

12:41

think it's got a lot of robustness to it

12:43

um but it's also kind of intuitive as

12:45

well especially if you again you are a

12:47

designer enough of a dollar let's move

12:49

into the last app builder that I want to

12:51

talk about and that is flutter flow so

12:53

here we are in flutter flow and this is

12:55

the main dashboard once you've logged in

12:57

you can see it looks a lot like the

12:59

dashboard in Glide now to get started in

13:02

flutterfly I'm just going to hit create

13:04

new and the one thing though they have a

13:07

lot of different templates and things

13:08

like that but I think you actually need

13:09

for any of these templates to have a pro

13:12

subscription so I'm just going to create

13:14

a blank one create a name let's say just

13:17

example app hit create blank

13:21

and it shows that you're like hey

13:22

starting a new project things like that

13:24

it'll actually walk you through a little

13:25

bit

13:26

um but that's okay so I'm not gonna do

13:29

the tutorial but this is a really nice

13:31

feature right at flirt photos it

13:32

actually has a tutorial built into what

13:34

you're doing and their content is a

13:36

little lackluster they don't have the

13:38

same like app academies that adalo and

13:40

glide have but they do have some people

13:42

in YouTube doing it but it's not as

13:44

organized I think this is coming there's

13:46

the documentation in flutter flow is

13:48

really nice and like written text but

13:50

the like video tutorials aren't all

13:51

there just yet so I'm going to start

13:54

building for now as you can see this has

13:57

a lot of like the Glide like this is

13:59

kind of a combination of like Glide and

14:01

a dollar a little bit like right there's

14:02

these elements there's the components

14:05

like components elements same difference

14:06

I think at this point

14:08

but I will say flirt flow is definitely

14:10

the most technical of these three apps

14:13

it is definitely the highest learning

14:15

curve of the three so it's not a tool

14:17

that you're just gonna pick up overnight

14:19

and be able to have a fully functioning

14:20

app I wouldn't say isn't as big of a

14:22

learning curve I think as like a bubble

14:24

if you're used to Bubble or at least

14:25

play with it no but it definitely has a

14:28

learning curve to it now if you have

14:29

maybe a more technical background maybe

14:31

you have you can code it just a little

14:32

bit or even maybe you are a full stack

14:34

developer and this can be a faster way

14:37

to get things going because you you have

14:38

all the design elements you're not

14:40

recreating the wheel that can be really

14:42

really nice so but again it's not this

14:45

isn't the easiest app to build pickup so

14:47

if you're not a designer if you're not

14:49

especially technical I wouldn't pick up

14:50

flutter flow right away this could be

14:52

like maybe version two three down the

14:54

line if you wouldn't especially if

14:56

you're building your first app rant over

14:57

let's jump into some of these toggles

14:59

here in flutter flow so as I mentioned

15:02

right there's all the different elements

15:03

or components of some of the app

15:05

Builders I've talked about and mentioned

15:06

named them but this has a little bit of

15:09

like they they're kind of a combo right

15:11

of a dollar and glide so you can see

15:13

there's elements and you can drag and

15:14

drop things in here but this is where

15:17

like I think if you're used to webflow

15:19

actually flutterflow has a lot of the

15:21

same components right so like there's

15:22

like the padding and Alignment so like

15:24

this like this right side of the screen

15:25

has a lot of the like webflow type of

15:29

Vibes in terms of like logic and how you

15:31

build things so if you like webflow I

15:33

think you'll like flutterflow um maybe

15:36

even better than the Glide or a dollar

15:38

the other thing right too and similar to

15:40

webflow rate is that it can be a little

15:41

more technical that than more than most

15:44

people want to actually handle so and

15:45

what I think the biggest feature right

15:47

that I think that flutter flow can

15:48

especially if you're more technical is

15:50

this custom functions tab now you can

15:52

actually add your own custom code right

15:55

into flutter flow which is really cool

15:57

so maybe there's like a widget or a part

15:59

that you want to just custom code that

16:00

maybe isn't in the some of the elements

16:02

that you can include in flutter flow

16:04

well you can just custom code them right

16:06

here which is really cool the other

16:09

thing about flutterflow which I think is

16:10

really really awesome is that let's say

16:13

like maybe flutter flow goes out of

16:14

business for some reason you can

16:16

actually export all that code that

16:18

you've built out your app with and it's

16:20

real code it's like built out and then

16:22

you start building it in real coding so

16:24

you can actually you can leave flutter

16:26

flow if you want to which is really cool

16:29

right all that code is there so maybe

16:31

like you're scaling and maybe this you

16:33

just scale to a point where like flutter

16:35

flow can't support it for some reason

16:36

you it you can actually get away from

16:39

that and still continue in building what

16:40

you're actually working on so that's

16:42

really really cool the other thing

16:45

similar to a dollar is you actually can

16:46

publish to the App Store in flutterflow

16:49

which is really awesome as well

16:51

now this is where I think flutter flow

16:54

can get really overwhelming I think is

16:56

right if you go to settings right here's

16:58

all these different things you can have

16:59

light mode theme a dark mode theme which

17:01

for some people it's great

17:03

um typography this I really like how

17:05

they've actually standardized this the

17:06

apps a lot of these no code apps haven't

17:08

actually done this but this has a lot of

17:10

like canva Vibes which I like

17:12

um there's all these different things

17:14

you can just kind of standardize which

17:15

is really cool but as you can see right

17:17

there's a lot of different Integrations

17:18

just built into flutter flow so like the

17:21

stripe there's GitHub

17:23

um there's Google analytics so if you

17:24

want to track analytics to through your

17:26

flutter fill app you can do that so

17:28

again if you like to if you want to be a

17:30

little more Technical and be able to

17:32

maybe not code the whole thing but have

17:34

code available to you flutterfail is

17:37

really great at being able to do that

17:38

and if you have maybe like a design

17:40

background it can code just a little bit

17:42

flutter fill might be the best example

17:44

for you the last thing I want to mention

17:46

here in flutter flow is actually one of

17:49

these cool features that especially is

17:50

important if you have a team working on

17:52

building this app so let's say You're

17:54

Building all these different features

17:55

and you want to get feedback on it one

17:58

of the cool things I think that the

17:59

other tools don't have at least yet is

18:01

that you can add comments and actually

18:02

kind of like a Google doc and or notion

18:04

document like add a comment so be like

18:06

hey what do you think of

18:09

of the this part or this element right

18:12

you had a comment you can tag people so

18:14

that's really really cool you can just

18:16

like tag it have all the communication

18:17

all in one place rather than like hey

18:19

things are in slack or airtable wherever

18:21

they like you're tracking these kind of

18:22

different things you can add comments

18:24

you can add things resolve them just

18:26

like you would in Google Docs which

18:27

these app others haven't done just yet

18:30

but I think this is a really nice piece

18:31

it makes your communication is going

18:33

really well especially if you have a

18:35

team like maybe there's even just two of

18:36

you working on building an app in

18:38

flutter flow so those are my three

18:41

favorite no code app builders for mobile

18:43

apps I would love to learn what your

18:44

experiences happen with any of these

18:46

three if you have any feedback leave a

18:48

comment down below if you found this

18:50

video helpful I would love it if you can

18:52

give it a like if you're looking for

18:54

more content like this you can check out

18:55

other videos on this channel like this

18:58

one here

19:03

foreign

19:08

foreign


Taking YOUR Existing BUSINESS

With AI IoT no-code mobile app builders

I’m Matthew Gira. I'm an entrepreneur, creator, and currently the Director of Student Programming at the Tsai Center for Innovative Thinking at Yale. At the moment, I'm focused on helping others create scalable, non-VC backed startups. 

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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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