# GPT-4 OpenAI: o que é e como funciona
## O que são leads orgânicos e como eles diferem dos leads pagos
### Qual é a importância dos leads orgânicos em um negócio
### Como gerar leads orgânicos para seu negócio
#### Criando um site otimizado para os mecanismos de busca
##### Como a inteligência artificial pode ajudar na otimização do site
##### Dicas práticas para a otimização de SEO
#### Criando conteúdo que engaja o leitor
##### Como a inteligência artificial pode ajudar a criar conteúdo
##### Dicas práticas para criar conteúdo engajador
#### Utilização das redes sociais para gerar leads orgânicos
##### Como a inteligência artificial pode ajudar nas redes sociais
##### Dicas práticas para a utilização das redes sociais
#### Construindo uma lista de e-mails para gerar leads orgânicos
##### Como a inteligência artificial pode ajudar a construir uma lista de e-mails
##### Dicas práticas para a construção da lista de e-mails
### Por que a inteligência artificial é importante na geração de leads orgânicos
## Como a OpenAI está usando a inteligência artificial para melhorar a geração de leads orgânicos
### O que é o GPT-4 da OpenAI
### Insights da demo do GPT-4 da OpenAI
### Como o GPT-4 da OpenAI pode revolucionar a geração de leads orgânicos
## Conclusão

FAQs:

1. Qual é a diferença entre leads orgânicos e leads pagos?
2. Como a otimização do site pode ajudar na geração de leads orgânicos?
3. Qual é a importância das redes sociais na geração de leads orgânicos?
4. É possível automatizar a construção de lista de e-mails utilizando inteligência artificial?
5. Como o GPT-4 da OpenAI pode ser utilizado para gerar leads orgânicos de forma mais eficiente?

br>OpenAI demos its latest developer release of GPT-4.

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gpt 4 ,

event,livestream,live,2022,CNET Highlights ,

https://www.youtubepp.com/watch?v=hdhZwyf24mE ,

Honestly it’s kind of hard for me to believe that this day is here open AI has been building this technology really since we started the company but for the past two years we’ve been really focused on delivering gpt4 that started with rebuilding our entire training stack actually training the model

And then seeing what it was capable of trying to figure out its capabilities its risks working with Partners in order to test it in real world scenarios really tuning Its Behavior optimizing the model getting it available so that you can use it and so today our

Goal is to show you a little bit of how to make gbt04 shine how to really get the most out of it you know where it’s kind of you know weaknesses are where we’re still working on it and just how to really use it as a good tool a good partner

Um so if you’re interested in participating in the Stream uh that if you go to our Discord so it’s discord.gg openai there’s comments in there and we’ll take a couple of audience suggestions so the first thing I want to show you is the first task that gpd4 could do that

We never really got 3.5 to do and the way to think about this is all throughout training that you know you’re constantly doing all this work it’s 2 A.M the pager goes off you fix the model and you’re always wondering is it gonna work is all of this effort actually going to

Pan out and so we all had a pet task that we really liked and that we would all individually be trying to see is the model capable of it now and I’m going to show you the first one that we had a success for four but never really got there for 3.5

So I’m just going to copy the top of our blog post from today I’m going to paste it into our Playground now this is our new chat completions playground that came out two weeks ago I’m going to show you first with GPT 3.5 4 has the same

API to it the same playground the way that it works is you have a system message where you explain to the model what it’s supposed to do and we’ve made these models very steerable so you can provide it with really any instruction you want whatever you dream up and the

Model will adhere to it pretty well and in the future it will get increasingly increasingly powerful at steering the model very reliably you can then paste whatever you want as a user the model will return messages as an assistant and the way to think of it

Is that we’re moving away from sort of just raw text in raw text out where you can’t tell where different parts of the conversation come from but towards this much more structured format that gives the model the opportunity to know well this is the user asking me to do

Something that the developer didn’t attend I should listen to the developer here all right so now time to actually show you the task that I’m referring to so everyone’s familiar with summarize this let’s say article into a sentence okay getting a little more specific but where every word begins with G

So this is 3.5 let’s see what it does yeah it kind of didn’t even try just gave up on the task this is pretty typical for 3.5 trying to do this particular kind of task if it’s you know sort of a very kind of stilted article or something like that maybe it can

Succeed but for the most part 3.5 just gives up but let’s try the exact same prompt the exact same system message in gpt4 so kind of borderline whether you want to count AI or not but so let’s say AI doesn’t count that’s cheating so fair enough the model happily accepts my feedback

So now to make sure it’s not just good for G’s I’d like to turn this over to the audience I’ll take a suggestion on what letter to try next in the meanwhile while I’m waiting for our moderators to pick the the lucky lucky letter uh I will give a try with a

Um but in this case I’ll say gpd4 is fine why not also pretty good summary so I’ll hop over to our Discord all right wow if people are are being a little ambitious here I’m really trying to put the model through the paces we’re going

To try Q uh which if you think about this for a moment I want the audience to really think about how would you do a summary of this article that all starts with Q it’s not easy it’s pretty good that’s pretty good all right so I’ve shown you summarizing

An existing article I want to show you how you can flexibly combine ideas between different articles so I’m going to take this article that was on Hacker News yesterday copy paste it into the same conversation so it has all the context of what we’re just doing I’m

Going to say find one common theme between this article and the gpd4 blog so this is an article about Pinecone which is a python web app development framework and it’s making the technology more accessible user friendly if you don’t think that was insightful enough you can always give some feedback and

Say that was not insightful enough please no I’ll just even just leave it there leave it up to the model to decide so Bridging the Gap between powerful technology and practical applications seems not bad and of course you can ask for any other kind of task you want using its flexible language

Understanding and synthesis you can ask for something like now turn the GT4 blog post into a rhyming poem picked up on open AI evalues open source for all helping to guide answering the call which by the way if you’d like to contribute to this model please give us

Evals we have an open source evaluation framework that will help us guide and all of our users understand what the model is capable of and to take it to the next level so there we go this is consuming existing content using gpt4 with with a little bit of creativity on top

,00:00 honestly it’s kind of hard for me to
00:01 believe that this day is here open AI
00:03 has been building this technology really
00:06 since we started the company but for the
00:07 past two years we’ve been really focused
00:09 on delivering gpt4 that started with
00:12 rebuilding our entire training stack
00:14 actually training the model
00:16 and then seeing what it was capable of
00:18 trying to figure out its capabilities
00:20 its risks working with Partners in order
00:22 to test it in real world scenarios
00:24 really tuning Its Behavior optimizing
00:27 the model getting it available
00:28 so that you can use it and so today our
00:31 goal is to show you a little bit of how
00:34 to make gbt04 shine how to really get
00:36 the most out of it you know where it’s
00:38 kind of you know weaknesses are where
00:40 we’re still working on it and just how
00:41 to really use it as a good tool a good
00:43 partner
00:44 um so if you’re interested in
00:46 participating in the Stream uh that if
00:48 you go to our Discord so it’s discord.gg
00:50 openai there’s comments in there and
00:52 we’ll take a couple of audience
00:53 suggestions
00:55 so the first thing I want to show you is
00:58 the first task that gpd4 could do that
01:01 we never really got 3.5 to do
01:03 and the way to think about this is all
01:05 throughout training that you know you’re
01:06 constantly doing all this work it’s 2
01:08 A.M the pager goes off you fix the model
01:11 and you’re always wondering is it gonna
01:13 work
01:14 is all of this effort actually going to
01:16 pan out and so we all had a pet task
01:19 that we really liked and that we would
01:20 all individually be trying to see is the
01:23 model capable of it now and I’m going to
01:25 show you the first one
01:27 that we had a success for four but never
01:29 really got there for 3.5
01:31 so I’m just going to copy the top of our
01:32 blog post from today I’m going to paste
01:34 it into our Playground now this is our
01:38 new chat completions playground that
01:40 came out two weeks ago I’m going to show
01:42 you first with GPT 3.5 4 has the same
01:45 API to it the same playground the way
01:47 that it works is you have a system
01:48 message where you explain to the model
01:50 what it’s supposed to do and we’ve made
01:53 these models very steerable so you can
01:55 provide it with really any instruction
01:56 you want whatever you dream up and the
01:58 model will adhere to it pretty well and
02:00 in the future it will get increasingly
02:02 increasingly powerful at steering the
02:04 model very reliably
02:07 you can then paste whatever you want as
02:09 a user the model will return messages as
02:11 an assistant and the way to think of it
02:13 is that we’re moving away from sort of
02:15 just raw text in raw text out where you
02:17 can’t tell where different parts of the
02:19 conversation come from but towards this
02:20 much more structured format that gives
02:22 the model the opportunity to know well
02:24 this is the user asking me to do
02:25 something that the developer didn’t
02:27 attend I should listen to the developer
02:28 here
02:30 all right so now time to actually show
02:32 you the task that I’m referring to so
02:34 everyone’s familiar with summarize
02:36 this let’s say article into a sentence
02:39 okay getting a little more specific but
02:42 where every word begins with G
02:45 so this is 3.5 let’s see what it does
02:49 yeah it kind of didn’t even try
02:52 just gave up on the task this is pretty
02:54 typical for 3.5 trying to do this
02:56 particular kind of task if it’s you know
02:58 sort of a very kind of stilted article
03:01 or something like that maybe it can
03:03 succeed but for the most part 3.5 just
03:05 gives up
03:07 but let’s try the exact same prompt
03:10 the exact same system message
03:13 in gpt4
03:17 so kind of borderline whether you want
03:18 to count AI or not but so let’s say AI
03:22 doesn’t count
03:24 that’s cheating
03:29 so fair enough the model happily accepts
03:31 my feedback
03:32 so now to make sure it’s not just good
03:34 for G’s I’d like to turn this over to
03:35 the audience I’ll take a suggestion on
03:37 what letter to try next in the meanwhile
03:39 while I’m waiting for our moderators to
03:41 pick the the lucky lucky letter uh I
03:43 will give a try with a
03:50 um but in this case I’ll say gpd4 is
03:51 fine
03:52 why not
03:55 also pretty good summary
03:57 so I’ll hop over to our Discord
03:59 all right
04:01 wow if people are are being a little
04:03 ambitious here I’m really trying to put
04:05 the model through the paces we’re going
04:06 to try Q uh which if you think about
04:08 this for a moment I want the audience to
04:10 really think about how would you do a
04:11 summary of this article that all starts
04:14 with Q it’s not easy
04:24 it’s pretty good that’s pretty good
04:27 all right so I’ve shown you summarizing
04:31 an existing article I want to show you
04:33 how you can flexibly combine ideas
04:35 between different articles so I’m going
04:38 to take this article that was on Hacker
04:40 News yesterday
04:42 copy paste it
04:44 into the same conversation so it has all
04:46 the context of what we’re just doing I’m
04:48 going to say find one common theme
04:51 between this article and the gpd4 blog
04:58 so this is an article about Pinecone
05:00 which is a python web app development
05:02 framework and it’s making the technology
05:04 more accessible user friendly if you
05:06 don’t think that was insightful enough
05:07 you can always give some feedback and
05:08 say that was not insightful
05:12 enough
05:14 please no I’ll just even just leave it
05:16 there leave it up to the model to decide
05:18 so Bridging the Gap between powerful
05:19 technology and practical applications
05:21 seems not bad and of course you can ask
05:24 for any other kind of task you want
05:26 using its flexible language
05:27 understanding and synthesis you can ask
05:30 for something like
05:31 now turn the GT4 blog post into a
05:35 rhyming poem
05:45 picked up on open AI evalues open source
05:48 for all helping to guide answering the
05:49 call which by the way if you’d like to
05:51 contribute to this model please give us
05:53 evals we have an open source evaluation
05:55 framework that will help us guide and
05:57 all of our users understand what the
05:59 model is capable of and to take it to
06:01 the next level
06:02 so there we go this is consuming
06:04 existing content using gpt4 with with a
06:07 little bit of creativity on top
, , , #OpenAI #Reveals #GPT4 #Demo #Watch , [agora]