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תביעה נגד Stable Diffusion, Midjourney ו-Deviant Art - Breaking News
תביעה נגד Stable Diffusion, Midjourney ו-Deviant Art - Breaking News
המיומנות המוזרה הזו הופכת אותך לעשיר עם ChatGPT
ChatGPT ובינה מלאכותית ישבשו את התעשיות הללו
0:00
there are things and everyone on in the
0:02
audience should know this there are
0:03
things coming down the pipeline on the
0:05
artificial intelligence front that are
0:07
just going to make your hair stand on
0:09
end within the next year because there
0:11
is so much transformation going on in
0:13
that domain and and that's been the case
0:16
particularly for the last six months
0:18
that it's almost unimaginable you're
0:21
going to see things you just can't
0:23
possibly how many of you clap how many
0:25
of you know what chat gbt is so I'll
0:28
tell you what Chow GPT is just so you
0:31
know because you need to know this and I
0:33
don't know what sort of technological
0:35
Revolution this is Gutenberg Press level
0:37
it's something like that this is a big
0:40
deal so this AI system to General
0:44
language processing model was released
0:47
about a week ago a week and a half ago
0:49
and it basically is trained on well a
0:53
massive Corpus of of spoken and or of
0:58
text so it's derived it's models of the
1:01
world from the analysis of human speech
1:03
essentially it isn't using real world
1:06
data yet
1:08
but that will be happening certainly
1:10
within the next year
1:12
so
1:14
and chat GPT
1:16
analyzes a very large Corpus of text and
1:19
now Corpus is growing all the time
1:22
some of you know I've written these
1:24
books 12 rules for life and then beyond
1:26
order 12 more rules because you know you
1:29
can't have enough rules and
1:31
I asked if this is what I asked it to do
1:34
I said write me an essay
1:36
that's a 13th rule for Beyond order
1:39
written in a style that combines the
1:42
King James Bible with the doubting
1:45
that's a pretty difficult
1:47
that's pretty difficult to pull off you
1:50
know any one of those things is hard the
1:53
intersection of all three that's
1:55
impossible well it wrote it in about
1:57
three seconds four pages long and
2:00
it isn't obvious to me for better or
2:03
worse that I would be able to tell that
2:05
I didn't write it okay and that's pretty
2:08
impressive although you know maybe not
2:10
it's relationship to what I've written
2:13
but the fact that it could do that
2:15
grammatically perfectly right and quite
2:18
impressive philosophically I also had it
2:21
write an essay on the intersection
2:23
between the Taoist version of ethical
2:27
morality and the ethics that are
2:30
outlined in The Sermon on the Mount
2:32
which it just nailed got that dead right
2:34
brilliant there is a computer engineer
2:38
who purported to work for Tesla he asked
2:41
GPT child gbt said look I work for Elon
2:44
Musk but I haven't been doing much for
2:46
the last week so I need you to write me
2:48
10 bullet points about what I probably
2:50
would have done as a
2:52
as a engineer at Twitter what 10 things
2:55
did I do last week that were productive
2:57
and valuable and oh if you don't mind
2:59
write me the accompanying computer code
3:01
that goes with each project
3:03
and it did that too three seconds and
3:05
the computer code works right and so
3:07
okay so that's that's already there so
3:09
then a university Professor did this he
3:11
thought oh that's interesting any
3:13
student will be able to write any essay
3:15
on any topic with chat gbt someone gave
3:17
it an s.a.t by the way and it scored
3:19
about as well as the average student in
3:22
a well-functioning public university so
3:24
that's how smart it is so that's
3:26
basically an IQ test he said write me an
3:30
essay gave it a topic wrote the S he
3:32
said now grade it said if we can
3:34
automate the students we should be able
3:35
to automate the professors too
3:37
and so it provided a complete
3:39
comprehensive analysis of its own Essay
3:42
with grade write the screenplay and
3:44
describe the characters for the next 900
3:46
million dollar Hollywood Blockbuster
3:48
it's like bang plot characterizations
3:52
then someone else took the descriptions
3:53
of the actors and said generate computer
3:57
photorealistic computer images for each
3:59
actor and all the AI systems could do
4:00
that so I'm going to tell you what's
4:02
going to happen next this is going to
4:03
happen this year so get ready okay so
4:07
now we have an AI model that can extract
4:09
a model of the world from the entire
4:10
Corpus of language
4:12
all right and it's
4:14
it's smarter than you and it's going to
4:17
be a hell of a lot smarter than you in
4:19
two years so you can get ready for that
4:21
too but it's not that smart yet because
4:23
it's just a Humanities professor at the
4:26
moment that's what a scientist does
4:28
right you come up with a theory that's
4:29
linguistically predicated and then you
4:31
throw it against the world and see if it
4:33
sticks and then the world tells you
4:35
whether or not you're linguistic
4:37
construction is valid
4:39
but the new AI systems will be able to
4:42
extract out patterns from the world
4:45
itself from images and so forth and then
4:47
be able to test their linguistic
4:49
constructions against the world and so
4:51
they'll practice just like scientists
4:53
and the most advanced models are going
4:56
to use text and image and action as well
5:00
because they'll build a mortal Human
5:01
Action and so and all of that's going to
5:05
come down the pipes
5:06
within the next year so hang on to your
5:09
hats ladies and gentlemen because one of
5:13
my friend Jonathan pajo say Giants are
5:15
going to walk the earth once more
5:17
and we're going to live through that
5:19
maybe I mean Elon Musk one of the things
5:22
he's working on see he he thinks that
5:24
the world will be controlled by whoever
5:26
produces the most functional AI system
5:29
the fastest because there'll be a first
5:31
a first
5:33
mover advantage and one of the things
5:36
musk has been working on for a long time
5:38
are distributed AI systems so that
5:40
you'll have your own artificial
5:41
intelligence to protect you against well
5:44
let's say against Google's artificial
5:46
intelligence for starters yeah or or the
5:49
ccp's artificial intelligence because
5:51
you can bet your hat they're working on
5:54
that about as fast as they possibly can
5:55
but let me ask you about the uh aspects
5:59
of the internet you despite the
6:01
persecution you've endured you've had an
6:04
enormous internet following you went
6:06
viral a long time ago and have stayed
6:08
there and yeah I'm worse than the
6:10
pandemic we touched upon this earlier
6:13
didn't it we have this unusual situation
6:15
where we have contemplated legislation
6:18
or regulatory changes in this country
6:21
where the government the federal
6:23
government thinks it can
6:25
have a form of registration of content
6:28
providers and I I suspect what they're
6:31
doing is trying to catch the coattails
6:33
of this reaction in the United States to
6:37
the revelations which are no great
6:38
surprise to anyone who followed it of
6:40
the extreme partisanship and
6:42
professional dishonesty of the major
6:45
major social media platforms and
6:47
political terms but what are we what is
6:51
your advice to this
6:53
to this country into this group about
6:56
preservation of uh
6:59
freedom of expression in the internet I
7:01
mean you you have been a great
7:03
benefactor to all of us but in in your
7:07
chosen Mission a beneficiary of a
7:10
relatively free access expressed concern
7:12
that a poll had revealed that 75 percent
7:16
of Canadians would cheerfully and
7:18
uncomplainingly go back to wearing masks
7:20
and a shutdown if they were told by the
7:23
ostensible authorities to do so even
7:25
though we now know that all of these
7:28
people all of fauci's local emulators
7:30
though there are all they all
7:32
self-identify as Dr Frankenstein's
7:35
monsters and my but my question of you
7:39
is
7:40
can we preserve freedom on the internet
7:43
well I think we have a blessing in
7:46
disguise in the liberal government
7:47
because they're too incompetent to be as
7:49
tyrannical as they want to be I'd
7:51
probably match your typical dim-witted
7:54
gaming 13 year old boy against Trudeau's
7:57
best bureaucrats on the tech front any
7:59
day and so
8:01
so it's not going to be that easy to
8:03
lock down the net and the other thing
8:04
that'll happen too and and perhaps you
8:07
should get prepared for this is that
8:08
anybody in Canada who's got a creative
8:10
bone in their body once they're subject
8:12
to the kind of limitations that the
8:14
Trudeau government is trying to put on
8:16
content providers
8:18
which is anyone by the way you're a
8:21
content provider man if you post on
8:23
Facebook and some of you probably do
8:25
even though maybe you shouldn't
8:27
um
8:28
all they'll do is all the creative
8:29
people just leave
English (auto-generated)
4:17
be a hell of a lot smarter than you in
4:19
two years so you can get ready for that
4:21
too but it's not that smart yet because
4:23
it's just a Humanities professor at the
4:26
moment that's what a scientist does
4:28
right you come up with a theory that's
4:29
linguistically predicated and then you
4:31
throw it against the world and see if it
4:33
sticks and then the world tells you
4:35
whether or not you're linguistic
4:37
construction is valid
4:39
but the new AI systems will be able to
4:42
extract out patterns from the world
4:45
itself from images and so forth and then
4:47
be able to test their linguistic
4:49
constructions against the world and so
4:51
they'll practice just like scientists
4:53
and the most advanced models are going
4:56
to use text and image and action as well
5:00
because they'll build a mortal Human
5:01
Action and so and all of that's going to
5:05
come down the pipes
5:06
within the next year so hang on to your
5:09
hats ladies and gentlemen because one of
5:13
my friend Jonathan pajo say Giants are
5:15
going to walk the earth once more
5:17
and we're going to live through that
5:19
maybe I mean Elon Musk one of the things
5:22
he's working on see he he thinks that
5:24
the world will be controlled by whoever
5:26
produces the most functional AI system
5:29
the fastest because there'll be a first
5:31
a first
5:33
mover advantage and one of the things
5:36
musk has been working on for a long time
5:38
are distributed AI systems so that
5:40
you'll have your own artificial
5:41
intelligence to protect you against well
5:44
let's say against Google's artificial
5:46
intelligence for starters yeah or or the
5:49
ccp's artificial intelligence because
5:51
you can bet your hat they're working on
5:54
that about as fast as they possibly can
5:55
but let me ask you about the uh aspects
5:59
of the internet you despite the
6:01
persecution you've endured you've had an
6:04
enormous internet following you went
6:06
viral a long time ago and have stayed
6:08
there and yeah I'm worse than the
6:10
pandemic we touched upon this earlier
6:13
didn't it we have this unusual situation
6:15
where we have contemplated legislation
6:18
or regulatory changes in this country
6:21
where the government the federal
6:23
government thinks it can
6:25
have a form of registration of content
6:28
providers and I I suspect what they're
6:31
doing is trying to catch the coattails
6:33
of this reaction in the United States to
6:37
the revelations which are no great
6:38
surprise to anyone who followed it of
6:40
the extreme partisanship and
6:42
professional dishonesty of the major
6:45
major social media platforms and
6:47
political terms but what are we what is
6:51
your advice to this
6:53
to this country into this group about
6:56
preservation of uh
6:59
freedom of expression in the internet I
7:01
mean you you have been a great
7:03
benefactor to all of us but in in your
7:07
chosen Mission a beneficiary of a
7:10
relatively free access expressed concern
7:12
that a poll had revealed that 75 percent
7:16
of Canadians would cheerfully and
7:18
uncomplainingly go back to wearing masks
7:20
and a shutdown if they were told by the
7:23
ostensible authorities to do so even
7:25
though we now know that all of these
7:28
people all of fauci's local emulators
7:30
though there are all they all
7:32
self-identify as Dr Frankenstein's
7:35
monsters and my but my question of you
7:39
is
7:40
can we preserve freedom on the internet
7:43
well I think we have a blessing in
7:46
disguise in the liberal government
7:47
because they're too incompetent to be as
7:49
tyrannical as they want to be I'd
7:51
probably match your typical dim-witted
7:54
gaming 13 year old boy against Trudeau's
7:57
best bureaucrats on the tech front any
7:59
day and so
8:01
so it's not going to be that easy to
8:03
lock down the net and the other thing
8:04
that'll happen too and and perhaps you
8:07
should get prepared for this is that
8:08
anybody in Canada who's got a creative
8:10
bone in their body once they're subject
8:12
to the kind of limitations that the
8:14
Trudeau government is trying to put on
8:16
content providers
8:18
which is anyone by the way you're a
8:21
content provider man if you post on
8:23
Facebook and some of you probably do
8:25
even though maybe you shouldn't
8:27
um
8:28
all they'll do is all the creative
8:29
people just leave
0:00
there are things and everyone on in the
0:02
audience should know this there are
0:03
things coming down the pipeline on the
0:05
artificial intelligence front that are
0:07
just going to make your hair stand on
0:09
end within the next year because there
0:11
is so much transformation going on in
0:13
that domain and and that's been the case
0:16
particularly for the last six months
0:18
that it's almost unimaginable you're
0:21
going to see things you just can't
0:23
possibly how many of you clap how many
0:25
of you know what chat gbt is so I'll
0:28
tell you what Chow GPT is just so you
0:31
know because you need to know this and I
0:33
don't know what sort of technological
0:35
Revolution this is Gutenberg Press level
0:37
it's something like that this is a big
0:40
deal so this AI system to General
0:44
language processing model was released
0:47
about a week ago a week and a half ago
0:49
and it basically is trained on well a
0:53
massive Corpus of of spoken and or of
0:58
text so it's derived it's models of the
1:01
world from the analysis of human speech
1:03
essentially it isn't using real world
1:06
data yet
1:08
but that will be happening certainly
1:10
within the next year
1:12
so
1:14
and chat GPT
1:16
analyzes a very large Corpus of text and
1:19
now Corpus is growing all the time
1:22
some of you know I've written these
1:24
books 12 rules for life and then beyond
1:26
order 12 more rules because you know you
1:29
can't have enough rules and
1:31
I asked if this is what I asked it to do
1:34
I said write me an essay
1:36
that's a 13th rule for Beyond order
1:39
written in a style that combines the
1:42
King James Bible with the doubting
1:45
that's a pretty difficult
1:47
that's pretty difficult to pull off you
1:50
know any one of those things is hard the
1:53
intersection of all three that's
1:55
impossible well it wrote it in about
1:57
three seconds four pages long and
2:00
it isn't obvious to me for better or
2:03
worse that I would be able to tell that
2:05
I didn't write it okay and that's pretty
2:08
impressive although you know maybe not
2:10
it's relationship to what I've written
2:13
but the fact that it could do that
2:15
grammatically perfectly right and quite
2:18
impressive philosophically I also had it
2:21
write an essay on the intersection
2:23
between the Taoist version of ethical
2:27
morality and the ethics that are
2:30
outlined in The Sermon on the Mount
2:32
which it just nailed got that dead right
2:34
brilliant there is a computer engineer
2:38
who purported to work for Tesla he asked
2:41
GPT child gbt said look I work for Elon
2:44
Musk but I haven't been doing much for
2:46
the last week so I need you to write me
2:48
10 bullet points about what I probably
2:50
would have done as a
2:52
as a engineer at Twitter what 10 things
2:55
did I do last week that were productive
2:57
and valuable and oh if you don't mind
2:59
write me the accompanying computer code
3:01
that goes with each project
3:03
and it did that too three seconds and
3:05
the computer code works right and so
3:07
okay so that's that's already there so
3:09
then a university Professor did this he
3:11
thought oh that's interesting any
3:13
student will be able to write any essay
3:15
on any topic with chat gbt someone gave
3:17
it an s.a.t by the way and it scored
3:19
about as well as the average student in
3:22
a well-functioning public university so
3:24
that's how smart it is so that's
3:26
basically an IQ test he said write me an
3:30
essay gave it a topic wrote the S he
3:32
said now grade it said if we can
3:34
automate the students we should be able
3:35
to automate the professors too
3:37
and so it provided a complete
3:39
comprehensive analysis of its own Essay
3:42
with grade write the screenplay and
3:44
describe the characters for the next 900
3:46
million dollar Hollywood Blockbuster
3:48
it's like bang plot characterizations
3:52
then someone else took the descriptions
3:53
of the actors and said generate computer
3:57
photorealistic computer images for each
3:59
actor and all the AI systems could do
4:00
that so I'm going to tell you what's
4:02
going to happen next this is going to
4:03
happen this year so get ready okay so
4:07
now we have an AI model that can extract
4:09
a model of the world from the entire
4:10
Corpus of language
4:12
all right and it's
4:14
it's smarter than you and it's going to
4:17
be a hell of a lot smarter than you in
4:19
two years so you can get ready for that
4:21
too but it's not that smart yet because
4:23
it's just a Humanities professor at the
4:26
moment that's what a scientist does
4:28
right you come up with a theory that's
4:29
linguistically predicated and then you
4:31
throw it against the world and see if it
4:33
sticks and then the world tells you
4:35
whether or not you're linguistic
4:37
construction is valid
4:39
but the new AI systems will be able to
4:42
extract out patterns from the world
4:45
itself from images and so forth and then
4:47
be able to test their linguistic
4:49
constructions against the world and so
4:51
they'll practice just like scientists
4:53
and the most advanced models are going
4:56
to use text and image and action as well
5:00
because they'll build a mortal Human
5:01
Action and so and all of that's going to
5:05
come down the pipes
5:06
within the next year so hang on to your
5:09
hats ladies and gentlemen because one of
5:13
my friend Jonathan pajo say Giants are
5:15
going to walk the earth once more
5:17
and we're going to live through that
5:19
maybe I mean Elon Musk one of the things
5:22
he's working on see he he thinks that
5:24
the world will be controlled by whoever
5:26
produces the most functional AI system
5:29
the fastest because there'll be a first
5:31
a first
5:33
mover advantage and one of the things
5:36
musk has been working on for a long time
5:38
are distributed AI systems so that
5:40
you'll have your own artificial
5:41
intelligence to protect you against well
5:44
let's say against Google's artificial
5:46
intelligence for starters yeah or or the
5:49
ccp's artificial intelligence because
5:51
you can bet your hat they're working on
5:54
that about as fast as they possibly can
5:55
but let me ask you about the uh aspects
5:59
of the internet you despite the
6:01
persecution you've endured you've had an
6:04
enormous internet following you went
6:06
viral a long time ago and have stayed
6:08
there and yeah I'm worse than the
6:10
pandemic we touched upon this earlier
6:13
didn't it we have this unusual situation
6:15
where we have contemplated legislation
6:18
or regulatory changes in this country
6:21
where the government the federal
6:23
government thinks it can
6:25
have a form of registration of content
6:28
providers and I I suspect what they're
6:31
doing is trying to catch the coattails
6:33
of this reaction in the United States to
6:37
the revelations which are no great
6:38
surprise to anyone who followed it of
6:40
the extreme partisanship and
6:42
professional dishonesty of the major
6:45
major social media platforms and
6:47
political terms but what are we what is
6:51
your advice to this
6:53
to this country into this group about
6:56
preservation of uh
6:59
freedom of expression in the internet I
7:01
mean you you have been a great
7:03
benefactor to all of us but in in your
7:07
chosen Mission a beneficiary of a
7:10
relatively free access expressed concern
7:12
that a poll had revealed that 75 percent
7:16
of Canadians would cheerfully and
7:18
uncomplainingly go back to wearing masks
7:20
and a shutdown if they were told by the
7:23
ostensible authorities to do so even
7:25
though we now know that all of these
7:28
people all of fauci's local emulators
7:30
though there are all they all
7:32
self-identify as Dr Frankenstein's
7:35
monsters and my but my question of you
7:39
is
7:40
can we preserve freedom on the internet
7:43
well I think we have a blessing in
7:46
disguise in the liberal government
7:47
because they're too incompetent to be as
7:49
tyrannical as they want to be I'd
7:51
probably match your typical dim-witted
7:54
gaming 13 year old boy against Trudeau's
7:57
best bureaucrats on the tech front any
7:59
day and so
8:01
so it's not going to be that easy to
8:03
lock down the net and the other thing
8:04
that'll happen too and and perhaps you
8:07
should get prepared for this is that
8:08
anybody in Canada who's got a creative
8:10
bone in their body once they're subject
8:12
to the kind of limitations that the
8:14
Trudeau government is trying to put on
8:16
content providers
8:18
which is anyone by the way you're a
8:21
content provider man if you post on
8:23
Facebook and some of you probably do
8:25
even though maybe you shouldn't
8:27
um
8:28
all they'll do is all the creative
8:29
people just leave
English (auto-generated)
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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 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? 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? 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.
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.
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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