# GPT-4 Visual ChatGPT: A GPT-4 “Preview”?

## Introdução

## O que é um ChatGPT?

## Como a tecnologia AI pode ajudar em chatbots?

## Explorando o GPT-4 Visual ChatGPT

## Como Funciona o GPT-4 Visual ChatGPT

## Como o GPT-4 Visual ChatGPT faz a diferença em relação aos chatbots existentes

## Flexibilidade do GPT-4 Visual ChatGPT

## Como as empresas podem implementar o GPT-4 Visual ChatGPT

## Precificação do GPT-4 Visual ChatGPT

## Perguntas Comuns sobre o GPT-4 Visual ChatGPT

### O GPT-4 Visual ChatGPT pode ser facilmente integrado em diferentes plataformas?

### Qual é a validade do GPT-4 Visual ChatGPT?

### Quais são as principais características do GPT-4 Visual ChatGPT?

### Como o GPT-4 Visual ChatGPT pode ajudar a minha empresa?

### Em que cenários o GPT-4 Visual ChatGPT pode ser mais eficiente do que outros chatbots?

## Como a tecnologia AI está mudando a maneira como criamos chatbots

## Conclusão

## FAQs

* O que é um ChatGPT?
* Como a tecnologia AI pode ajudar em chatbots?
* Explorando o GPT-4 Visual ChatGPT
* Como o GPT-4 Visual ChatGPT faz a diferença em relação aos chatbots existentes
* Como as empresas podem implementar o GPT-4 Visual ChatGPT

br>Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation Models
[Paper]
[Code]
[My Windows Installation GitHub Tutorial]

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[Music] Taken from Slip Stream
[Profile & Banner Art]
[Video Editor] @Askejm

Este vídeo foi indexado através do Youtube link da fonte
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https://www.youtubepp.com/watch?v=0UfXlFUwLms ,

As the German CTO of Microsoft confirmed the existence of gpt4 rumors began to circulate that it will be a multimodal language model unlike its predecessor GPT 3.5 and Chachi BT which are purely text based then Microsoft announced visual chat GPT which may provide a preview of what large multimodal

Language models like gbt4 could look like while there may be no direct connection between the two visual charge PPT has opened up interesting possibilities for chaturbate-based image editing and understanding providing insight into what gpt4 might look like firstly it is intriguing how efficient communication of image information has

Been achieved with the visual chat GPT although chat gbt has limited ability to process visual information it’s the prompt manager which was proposed in visual attachivity organizes up to 22 visual Foundation models which includes texture image control net and pixel pix functionalities together and converts all visual signals of an image into

Language that has EBT can comprehend while this may seem like a force to work around where chat activity is still using text to understand things The Prompt manager performs various tasks to convert non-language information into something chat gbt can understand for instance when uploading images The Prompt manager synthesizes an internal

Chat history that includes the image file name so that chat gbt can refer to it accurately additionally it enables chaining operations where multiple processes can be ordered and organized by The Prompt manager allowing for object changes in the scene while simultaneously altering its style using different visual Foundation models the

Name of the image would act as an operation history which is an interesting way of saving information not gonna lie also a hard-coded questions will be added as inner thoughts such as asking do I need to use this tool for chat gbt to call the correct vfm operation in the best case

Scenario multiple rounds of dialogues between Visual attractivity and the user are possible enabling visual chat gbt to understand human intents support language and image inputs and accomplish complex visual tasks such as generation questioning and editing however challenges such as naming the right file distinguishing the right file name

Calling the right functions chaining the right vfm communicating with chat GPT correctly may still appear while we know that chatgpt sometimes is really bad at following or generating very strict and Specific Instructions anyway so your expectation of visual chat GT shouldn’t be higher than that contrarily watching

Its demo can make you interpret much more than what it actually can do though AKA Cherry Picked results which is sometimes a bad thing but they are still capable of doing what they are shown or do they while I asked for a cake it generated me a character sheet so that

Was a lie so I got it working on Windows machine and interestingly to be able to handle of the 22 vfm functions you will need an a100 to do that because it requires insane amount of GPU RAM and I got it working by only running 4 out of the 22 functions which includes

Textual image image to Kenny Edge image captioning and bullet for image description Generations you can refer to this table for how much vram each vfm functions uses after testing a few times I realized that I cannot replicate what the demo video did and the results I got

Were pretty bad I even thought it might be because they are using stable diffusion 1.5 so I switched them manually to stable diffusion 2.1 as the model and the quality didn’t change that much either I tried asking about the image Samplers or CFG values and it seems that it doesn’t really understand

What those values are and when I specify the Samplers or the CFG values I doubt that it really considers them when used generating what’s even worse is that since it uses chatgpt and it requires its API which costs money it didn’t even take 30 dialogues that generate around

20 images to cost me one dollar just exactly how many API calls is it doing so it’s a bit too expensive for its quality in my humble opinion but chaining operations did work and it was pretty neat but another downside is that unlike the demo the whole dialogue

Doesn’t display the image images for some reason so you will need to have your file explorer at the site to view your results in the meantime and yeah that’s it about visual chat gbt the whole workflow management by the prom manager is pretty impressive and I feel

Like this is something I would see in the startup company however I definitely feel the over hype about this project because I saw a lot of people praising how cold this is and it got like 6K stars in two days but the researchers still made an amazing work and I cannot

Undermine that I would definitely clickbait this as GPT 4 preview though since it is also published by Microsoft so sorry not sorry thank you guys for watching a big shout out to Andrew lascellias Chris LeDoux Alex Maurice and many others that support me through patreon or YouTube follow my Twitter for

The latest post and I’ll see you in the next one

,00:00 as the German CTO of Microsoft confirmed
00:02 the existence of gpt4 rumors began to
00:05 circulate that it will be a multimodal
00:07 language model unlike its predecessor
00:09 GPT 3.5 and Chachi BT which are purely
00:11 text based then Microsoft announced
00:14 visual chat GPT which may provide a
00:15 preview of what large multimodal
00:17 language models like gbt4 could look
00:19 like while there may be no direct
00:21 connection between the two visual charge
00:23 PPT has opened up interesting
00:25 possibilities for chaturbate-based image
00:27 editing and understanding providing
00:29 insight into what gpt4 might look like
00:31 firstly it is intriguing how efficient
00:34 communication of image information has
00:36 been achieved with the visual chat GPT
00:37 although chat gbt has limited ability to
00:40 process visual information it’s the
00:42 prompt manager which was proposed in
00:43 visual attachivity organizes up to 22
00:46 visual Foundation models which includes
00:48 texture image control net and pixel pix
00:51 functionalities together and converts
00:53 all visual signals of an image into
00:55 language that has EBT can comprehend
00:57 while this may seem like a force to work
00:59 around where chat activity is still
01:01 using text to understand things The
01:03 Prompt manager performs various tasks to
01:05 convert non-language information into
01:07 something chat gbt can understand for
01:09 instance when uploading images The
01:11 Prompt manager synthesizes an internal
01:13 chat history that includes the image
01:15 file name so that chat gbt can refer to
01:17 it accurately additionally it enables
01:20 chaining operations where multiple
01:21 processes can be ordered and organized
01:23 by The Prompt manager allowing for
01:25 object changes in the scene while
01:27 simultaneously altering its style using
01:29 different visual Foundation models the
01:31 name of the image would act as an
01:32 operation history which is an
01:34 interesting way of saving information
01:35 not gonna lie also a hard-coded
01:38 questions will be added as inner
01:39 thoughts such as asking do I need to use
01:42 this tool for chat gbt to call the
01:44 correct vfm operation in the best case
01:46 scenario multiple rounds of dialogues
01:48 between Visual attractivity and the user
01:50 are possible enabling visual chat gbt to
01:52 understand human intents support
01:54 language and image inputs and accomplish
01:57 complex visual tasks such as generation
01:59 questioning and editing however
02:01 challenges such as naming the right file
02:03 distinguishing the right file name
02:05 calling the right functions chaining the
02:07 right vfm communicating with chat GPT
02:09 correctly may still appear while we know
02:12 that chatgpt sometimes is really bad at
02:14 following or generating very strict and
02:16 Specific Instructions anyway so your
02:18 expectation of visual chat GT shouldn’t
02:20 be higher than that contrarily watching
02:22 its demo can make you interpret much
02:24 more than what it actually can do though
02:26 AKA Cherry Picked results which is
02:28 sometimes a bad thing but they are still
02:31 capable of doing what they are shown or
02:33 do they while I asked for a cake it
02:37 generated me a character sheet so that
02:39 was a lie so I got it working on
02:41 Windows machine and interestingly to be
02:43 able to handle of the 22 vfm functions
02:46 you will need an a100 to do that because
02:48 it requires insane amount of GPU RAM and
02:52 I got it working by only running 4 out
02:54 of the 22 functions which includes
02:55 textual image image to Kenny Edge image
02:58 captioning and bullet for image
03:00 description Generations you can refer to
03:02 this table for how much vram each vfm
03:04 functions uses after testing a few times
03:07 I realized that I cannot replicate what
03:09 the demo video did and the results I got
03:11 were pretty bad I even thought it might
03:14 be because they are using stable
03:15 diffusion 1.5 so I switched them
03:17 manually to stable diffusion 2.1 as the
03:19 model and the quality didn’t change that
03:22 much either I tried asking about the
03:24 image Samplers or CFG values and it
03:26 seems that it doesn’t really understand
03:27 what those values are and when I specify
03:30 the Samplers or the CFG values I doubt
03:33 that it really considers them when used
03:34 generating what’s even worse is that
03:36 since it uses chatgpt and it requires
03:39 its API which costs money it didn’t even
03:41 take 30 dialogues that generate around
03:43 20 images to cost me one dollar just
03:46 exactly how many API calls is it doing
03:48 so it’s a bit too expensive for its
03:51 quality in my humble opinion but
03:53 chaining operations did work and it was
03:55 pretty neat but another downside is that
03:57 unlike the demo the whole dialogue
03:58 doesn’t display the image images for
04:00 some reason so you will need to have
04:01 your file explorer at the site to view
04:03 your results in the meantime and yeah
04:05 that’s it about visual chat gbt the
04:07 whole workflow management by the prom
04:08 manager is pretty impressive and I feel
04:10 like this is something I would see in
04:12 the startup company however I definitely
04:14 feel the over hype about this project
04:16 because I saw a lot of people praising
04:18 how cold this is and it got like 6K
04:20 stars in two days but the researchers
04:22 still made an amazing work and I cannot
04:24 undermine that I would definitely
04:26 clickbait this as GPT 4 preview though
04:28 since it is also published by Microsoft
04:31 so sorry not sorry thank you guys for
04:33 watching a big shout out to Andrew
04:34 lascellias Chris LeDoux Alex Maurice and
04:39 many others that support me through
04:40 patreon or YouTube follow my Twitter for
04:42 the latest post and I’ll see you in
04:44 the next one
, , , #Visual #ChatGPT #GPT4 #Preview , [agora]