#GPT4: AI que está mudando tudo
1. Introdução à GPT4
2. O que são leads orgânicos
3. Como eles diferem de leads pagos
4. Por que os leads orgânicos são importantes
5. Como gerar leads orgânicos para o seu negócio
6. Escolhendo as palavras-chave certas
7. Otimizando seu site para os mecanismos de busca
8. Criando conteúdo envolvente
9. Divulgando conteúdo nas redes sociais
10. Construindo uma lista de e-mails
11. Seguindo as métricas corretas
12. Monitorando o desempenho do seu negócio
13. Mantenha-se atualizado com as últimas tendências
14. Exemplos de sucesso no uso de leads orgânicos
15. Conclusão: Lembre-se de que o marketing de conteúdo é uma longa caminhada

FAQs
1. O que é GPT4?
2. Qual é a diferença entre leads orgânicos e leads pagos?
3. Como posso usar as redes sociais para gerar leads orgânicos?
4. Qual é a importância da escolha de palavras-chave corretas?
5. Como faço para medir o sucesso dos meus esforços de geração de leads orgânicos?

br>In this video, I’m unveiling GPT4: AI That’s Changing Everything.

GT4 is the next stage in Google’s machine learning development, and it has the potential to change the way we search online.

GT4 uses a new type of AI called a “supervised learning algorithm.” This means that the algorithm can learn from data, and improve its performance over time as it encounters more and more data.

This powerful new technology is already being used by Google to improve its search results, and it has the potential to do much more. In this video, I’ll show you how GPT4 is changing the way we search online, and how you can use it to improve your search results too! #technology #chatgpt

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gpt 4 ,

artificial intelligence,ai,machine learning ,

https://www.youtubepp.com/watch?v=P_ErB9W2q8s ,

Gpt4 the future of AI language processing we all know that the gpt3 AI engine was a significant advancement the refined model could spit out paragraphs with fluency in comparison to gpt2 the discussion of the next big thing has been relatively muted since the release of gpt3 now we have more information

About gpt4 some say that gpt4 will be disruptive and next level but what will the reality be when gpt3 was released on June 11 2020 people responded positively soon when open AI launches gpt4 the response may be even more positive Welcome to our Channel and today we’ll

Tell you about open ai’s gpt4 language model this video will take a look at the latest advancements in Ai and natural language processing and how gpt4 is about to change the game gpt4 is is a language processing model that can generate human-like text with the help of AI gpt4 employs natural language

Generation nlg and natural language processing NLP in contrast to other AI language models deep learning models and machine learning models due to the NDA the specific details of the gpt4 specifications are still in flux however gpt4 is likely to use a hundred trillion parameters the first large-scale model

With a sparse Core Design is here sparsity indicates that the compute cost is likely to be lower even at the 100t parameter space which is what it means this indicates that the final model still has a lot of active neurons it is in layman’s terms a model that can keep

A lot more choices of next word next sentence and next emotion depending on the context this basically means that it is more like real human thinking than its predecessor instead of asking Alexa to play your favorite song or have Siri type your text you could go much bigger

You can generate a hundred ideas for social media posts in less than two minutes or write an entire ebook in 10 minutes with gpt4 gpt4 is a pre-trained model which means it has been trained on a large Text data set and can perform language processing tasks more accurately it is capable of continuing

To generate text based on its previous output and can generate text based on the input it receives how it’s different from previous language models model size Altman claims that gpt4 won’t be significantly larger than gpt3 therefore similar to deepmind’s language model gopher we can assume that it will have around 175

Billion to 280 billion parameters with 530 billion parameters the large model Megatron nlg is three times larger than gpt3 but performed no better the smaller model that came after it reached higher performance levels in simple words a large size does not mean higher performance Altman stated that they are concentrating on improving the

Performance of smaller models a large data set a lot of computing power and a complicated implementation were necessary for the large language models but for a number of businesses deploying large models becomes too expensive AI alignment gpt4 will have a better alignment than the gpt3 open AI has difficulty aligning

AI they want language models to reflect our values and intention they have started by constructing instruct GPT it is a gpt3 model that has been instructed to follow instructions by humans human judges thought the model was better than gpt3 regardless of language standards multi-modality gpt4 will be a text only model

Multimodal models are the future of deep learning because we live in a multimodal world our brains are multi-sensory ai’s ability to navigate or comprehend the world is severely limited by its ability to perceive it in one mode at a time however compared to good language only or Vision only models good multimodal

Models are significantly more challenging to construct it is difficult to combine textual and visual information into a single representation we do not know how to implement invented in neural networks because we have very limited concepts of how our brains do it not that the Deep Learning Community is

Taking into account insights from the cognitive Sciences on brain structure and functionality in the Q a Altman stated that gpt4 will not be a multimodal model like dolly or mum but rather a text only model before moving on to the next generation of multimodal AI some speculate that they are

Attempting to push the boundaries of language models by adjusting factors such as model and data set size potential applications gpt3 has already been utilized in content generation chat Bots and virtual assistants among other applications additionally it has been utilized in machine learning and natural language processing research gpt4 is anticipated

To have even more applications particularly in creative writing and art additionally it is anticipated to boost the performance of current applications like chat Bots and virtual assistants gpt4 is anticipated to overcome these limitations and significantly outperform gpt3 additionally creative Fields like writing music composition and art creation could benefit from the use of

Gpt4 the Revolutionary design of gpt4 makes it easier to comprehend and replicate human behavior to put it another way it can continue to learn how to generate text that is more human-like and believable some of the uses for gpt4 are as follows answer in-depth inquiries Translate text into various languages

Summarize lengthy passages and begin from scratch the creation of long-form content such as blog posts and articles simply type natural language into the query bar to create these content types no matter how brief your prompts are the model will then transform it into text that is more comprehensive open AI

Suggests that gpt4 may be more accurate and able to follow instructions more effectively this is due to the fact that one of the most pressing issues in Ai and data science is AI alignment issues which are less prevalent in its design in addition it facilitates the use of

The human brain and inferring users intentions it is also possible to use it to describe the difficulty of creating an AI system that is compatible with relatable values desires and beliefs additionally its high power of accuracy is presumptuous according to them gpt4 will have a neural network with five

Times the capacity of other AI tools and language models what does it mean for businesses the next generation of the open AI framework gpt4 might change the face of language modeling the fact that a hundred trillion machine learning parameters are used in gpt4 versus 175 billion in the current model is the most

Obvious and astonishing difference between the two models the technology is also departing from the concept that bigger is better even though gpt4 will have significantly more parameters than gpt3 Adam Lieberman head of artificial intelligence and machine learning at finastra says that in the future he wants to see a smaller increase in model

Size and parameters according to Lieberman gpt3 demonstrated to the community that it meant business by completing the code and finding tax deductions the emergence of gpt4 will contribute to the growing awareness that AI is becoming less rigid and more empathetic we expect to see enhanced use cases utilizing the power of language

Modeling across numerous domains with a new and improved version of our GPT language model he continues we are excited to see all the new use cases that will emerge use cases in which gpt3 performed sub-optimally have a second chance at the free throw line with the introduction of gpt4 folkard anticipates

That internet users will more frequently encounter AI generated content this is already taking place but better outcomes will likely make it more widely used inevitably cyber criminals will also begin to use the technology making it more difficult to distinguish certain Communications the benefits for businesses will be less time spent on

Day-to-day content creation and the possibility of writing previously difficult or impossible content like essays and full articles here is a look at how gpt4 can potentially impact the market language processing will alter the Dynamics of marketing by automating the writing of posts about various marketing strategies by producing

Responses that are more akin to those provided by real people customer support will become more efficient and be able to provide multi-faceted services with its Advanced language learning methods gpt4 will create personalized experiences which will have a groundbreaking effect on education it will be easy to produce a lot of

Relevant business content in multiple languages the language used in gpt4 generated blogs articles social media posts and product descriptions will be exactly as it is used by humans the disadvantage is that fake news under the guise of human-like writing is likely to be produced because of this it will be

Difficult to tell fact from fiction in conclusion while gpt4 will raise the bar for automated text it is still far from achieving language comprehension comparable to that of humans however gpt4 will include a larger context window memory to make it easier to create human errors and complete difficult tasks that’s all for today

Hope this video has been quite helpful for you share your thoughts in the comments section and don’t forget to subscribe

,00:00 gpt4 the future of AI language
00:03 processing we all know that the gpt3 AI
00:07 engine was a significant advancement the
00:10 refined model could spit out paragraphs
00:12 with fluency in comparison to gpt2 the
00:16 discussion of the next big thing has
00:18 been relatively muted since the release
00:20 of gpt3 now we have more information
00:23 about gpt4 some say that gpt4 will be
00:28 disruptive and next level but what will
00:30 the reality be when gpt3 was released on
00:34 June 11 2020 people responded positively
00:37 soon when open AI launches gpt4 the
00:41 response may be even more positive
00:43 Welcome to our Channel and today we’ll
00:46 tell you about open ai’s gpt4 language
00:49 model this video will take a look at the
00:51 latest advancements in Ai and natural
00:54 language processing and how gpt4 is
00:57 about to change the game gpt4 is is a
01:00 language processing model that can
01:02 generate human-like text with the help
01:04 of AI gpt4 employs natural language
01:07 generation nlg and natural language
01:10 processing NLP in contrast to other AI
01:14 language models deep learning models and
01:17 machine learning models due to the NDA
01:20 the specific details of the gpt4
01:22 specifications are still in flux however
01:25 gpt4 is likely to use a hundred trillion
01:28 parameters the first large-scale model
01:31 with a sparse Core Design is here
01:33 sparsity indicates that the compute cost
01:36 is likely to be lower even at the 100t
01:39 parameter space which is what it means
01:41 this indicates that the final model
01:43 still has a lot of active neurons it is
01:46 in layman’s terms a model that can keep
01:48 a lot more choices of next word next
01:51 sentence and next emotion depending on
01:54 the context this basically means that it
01:56 is more like real human thinking than
01:58 its predecessor instead of asking Alexa
02:01 to play your favorite song or have Siri
02:03 type your text you could go much bigger
02:06 you can generate a hundred ideas for
02:08 social media posts in less than two
02:10 minutes or write an entire ebook in 10
02:13 minutes with gpt4 gpt4 is a pre-trained
02:17 model which means it has been trained on
02:19 a large Text data set and can perform
02:21 language processing tasks more
02:24 accurately it is capable of continuing
02:26 to generate text based on its previous
02:28 output and can generate text based on
02:31 the input it receives
02:33 how it’s different from previous
02:34 language models model size Altman claims
02:38 that gpt4 won’t be significantly larger
02:41 than gpt3 therefore similar to
02:44 deepmind’s language model gopher we can
02:46 assume that it will have around 175
02:49 billion to 280 billion parameters with
02:52 530 billion parameters the large model
02:55 Megatron nlg is three times larger than
02:58 gpt3 but performed no better the smaller
03:02 model that came after it reached higher
03:04 performance levels in simple words a
03:06 large size does not mean higher
03:08 performance Altman stated that they are
03:11 concentrating on improving the
03:12 performance of smaller models a large
03:15 data set a lot of computing power and a
03:17 complicated implementation were
03:19 necessary for the large language models
03:21 but for a number of businesses deploying
03:24 large models becomes too expensive
03:26 AI alignment
03:29 gpt4 will have a better alignment than
03:31 the gpt3 open AI has difficulty aligning
03:35 AI they want language models to reflect
03:37 our values and intention they have
03:40 started by constructing instruct GPT it
03:43 is a gpt3 model that has been instructed
03:46 to follow instructions by humans human
03:48 judges thought the model was better than
03:50 gpt3 regardless of language standards
03:54 multi-modality gpt4 will be a text only
03:58 model
03:59 multimodal models are the future of deep
04:01 learning because we live in a multimodal
04:04 world our brains are multi-sensory ai’s
04:07 ability to navigate or comprehend the
04:09 world is severely limited by its ability
04:11 to perceive it in one mode at a time
04:14 however compared to good language only
04:16 or Vision only models good multimodal
04:19 models are significantly more
04:21 challenging to construct it is difficult
04:23 to combine textual and visual
04:25 information into a single representation
04:27 we do not know how to implement invented
04:29 in neural networks because we have very
04:31 limited concepts of how our brains do it
04:34 not that the Deep Learning Community is
04:36 taking into account insights from the
04:38 cognitive Sciences on brain structure
04:40 and functionality in the Q a Altman
04:43 stated that gpt4 will not be a
04:45 multimodal model like dolly or mum but
04:48 rather a text only model before moving
04:51 on to the next generation of multimodal
04:53 AI some speculate that they are
04:55 attempting to push the boundaries of
04:56 language models by adjusting factors
04:58 such as model and data set size
05:02 potential applications
05:04 gpt3 has already been utilized in
05:07 content generation chat Bots and virtual
05:10 assistants among other applications
05:12 additionally it has been utilized in
05:14 machine learning and natural language
05:16 processing research gpt4 is anticipated
05:19 to have even more applications
05:21 particularly in creative writing and art
05:24 additionally it is anticipated to boost
05:26 the performance of current applications
05:28 like chat Bots and virtual assistants
05:31 gpt4 is anticipated to overcome these
05:34 limitations and significantly outperform
05:37 gpt3 additionally creative Fields like
05:40 writing music composition and art
05:42 creation could benefit from the use of
05:44 gpt4 the Revolutionary design of gpt4
05:48 makes it easier to comprehend and
05:50 replicate human behavior to put it
05:52 another way it can continue to learn how
05:55 to generate text that is more human-like
05:57 and believable some of the uses for gpt4
06:00 are as follows answer in-depth inquiries
06:03 Translate text into various languages
06:06 summarize lengthy passages and begin
06:09 from scratch the creation of long-form
06:11 content such as blog posts and articles
06:13 simply type natural language into the
06:16 query bar to create these content types
06:18 no matter how brief your prompts are the
06:21 model will then transform it into text
06:23 that is more comprehensive open AI
06:26 suggests that gpt4 may be more accurate
06:29 and able to follow instructions more
06:31 effectively this is due to the fact that
06:34 one of the most pressing issues in Ai
06:36 and data science is AI alignment issues
06:39 which are less prevalent in its design
06:41 in addition it facilitates the use of
06:43 the human brain and inferring users
06:46 intentions it is also possible to use it
06:48 to describe the difficulty of creating
06:50 an AI system that is compatible with
06:53 relatable values desires and beliefs
06:55 additionally its high power of accuracy
06:58 is presumptuous according to them gpt4
07:01 will have a neural network with five
07:03 times the capacity of other AI tools and
07:06 language models what does it mean for
07:08 businesses the next generation of the
07:11 open AI framework gpt4 might change the
07:14 face of language modeling the fact that
07:17 a hundred trillion machine learning
07:18 parameters are used in gpt4 versus 175
07:22 billion in the current model is the most
07:24 obvious and astonishing difference
07:26 between the two models the technology is
07:29 also departing from the concept that
07:31 bigger is better even though gpt4 will
07:34 have significantly more parameters than
07:36 gpt3 Adam Lieberman head of artificial
07:39 intelligence and machine learning at
07:41 finastra says that in the future he
07:43 wants to see a smaller increase in model
07:45 size and parameters according to
07:48 Lieberman gpt3 demonstrated to the
07:51 community that it meant business by
07:53 completing the code and finding tax
07:55 deductions the emergence of gpt4 will
07:58 contribute to the growing awareness that
08:00 AI is becoming less rigid and more
08:03 empathetic we expect to see enhanced use
08:06 cases utilizing the power of language
08:08 modeling across numerous domains with a
08:10 new and improved version of our GPT
08:12 language model he continues we are
08:15 excited to see all the new use cases
08:17 that will emerge use cases in which gpt3
08:20 performed sub-optimally have a second
08:23 chance at the free throw line with the
08:25 introduction of gpt4 folkard anticipates
08:28 that internet users will more frequently
08:30 encounter AI generated content this is
08:33 already taking place but better outcomes
08:36 will likely make it more widely used
08:38 inevitably cyber criminals will also
08:40 begin to use the technology making it
08:43 more difficult to distinguish certain
08:44 Communications the benefits for
08:47 businesses will be less time spent on
08:49 day-to-day content creation and the
08:51 possibility of writing previously
08:52 difficult or impossible content like
08:55 essays and full articles here is a look
08:58 at how gpt4 can potentially impact the
09:01 market language processing will alter
09:04 the Dynamics of marketing by automating
09:06 the writing of posts about various
09:08 marketing strategies by producing
09:10 responses that are more akin to those
09:12 provided by real people customer support
09:14 will become more efficient and be able
09:16 to provide multi-faceted services with
09:19 its Advanced language learning methods
09:21 gpt4 will create personalized
09:23 experiences which will have a
09:25 groundbreaking effect on education it
09:28 will be easy to produce a lot of
09:30 relevant business content in multiple
09:32 languages the language used in gpt4
09:34 generated blogs articles social media
09:37 posts and product descriptions will be
09:39 exactly as it is used by humans the
09:42 disadvantage is that fake news under the
09:45 guise of human-like writing is likely to
09:47 be produced because of this it will be
09:49 difficult to tell fact from fiction in
09:52 conclusion while gpt4 will raise the bar
09:55 for automated text it is still far from
09:58 achieving language comprehension
09:59 comparable to that of humans however
10:02 gpt4 will include a larger context
10:05 window memory to make it easier to
10:07 create human errors and complete
10:09 difficult tasks that’s all for today
10:12 hope this video has been quite helpful
10:14 for you share your thoughts in the
10:16 comments section and don’t forget to
10:18 subscribe
, , , #Unveiling #GPT #Changing , [agora]