AI-Generated Transcript
Good morning. Thank you for joining us today. Please welcome to the stage Sam Altman.
Good morning. Welcome to our first ever Openai Dev Day. We’re thrilled that you’re here and this energy is awesome.
And welcome to San Francisco. San Francisco has been our home since day one. The city is important to us and the tech industry in general.
We’re looking forward to continuing to grow here. So we’ve got some great stuff to announce today. But first, I’d like to take a minute to talk about some of the stuff that we’ve done over the past year.
About a year ago, November 30, we shipped Chat GPT as a low key research preview, and that went pretty well. In March, we followed that up with the launch of GPT Four, still the most capable model out in the world. And in the last few months, we launched voice and vision capabilities so that chat GPT can now see, hear and speak.
And more recently, there’s a lot you don’t have to clap each time. And more recently, we launched Dolly Three, the world’s most advanced image model. You can use it, of course, inside of chat GPT for our enterprise customers, we launched Chat GPT Enterprise, which offers enterprise grade security and privacy, higher speed GPT four, access, longer context Windows, lot more.
Today, we’ve got about 2 million developers building on our API for a wide variety of use cases doing amazing stuff. Over 92% of Fortune 500 companies building on our products, and we have about 100 million weekly active users now on chat GBT. And what’s incredible on that is we got there entirely through word of mouth.
People just find it useful and tell their friends. OpenAI is the most advanced and the most widely used AI platform in the world now. But numbers never tell the whole picture on something like this.
What’s really important is how people use the products, how people are using AI. And so I’d like to show you a quick video. I actually wanted to write something to my dad in Tagalog.
I want a non romantic way to tell my parent that I love him, and I also want to tell him that he can rely on me, but in a way that still has the respect of a child to parent relationship that you should have in Filipino culture and in Tagalog Grammar, when it’s translated into Gala, I love you very deeply and I will be with you no matter where the path leads. I see some of the possibility. I was like, whoa.
Sometimes I’m not sure about some stuff and I feel like actually Chatty could tell. Hey, this is what I’m thinking about so it kind of give me that more confidence. The first thing that blew my mind was it levels with you.
Like, that’s something that a lot of people struggle to do. It opened my mind to just what every creative could do if they just had a person helping them out who listens. So this is to represent sickling hemoglobin.
And you built that with Chad GPT. Chad GPT built it with me. I started using it for daily activities, like, hey, here’s a picture of my fridge.
Can you tell me what I’m missing? Because I’m going grocery shopping and I really need to do recipes that are following my vegan diet. As soon as we got access to code interpreter, I was like, wow, this thing is awesome. It could build spreadsheets, it could do anything.
I discovered Chatty about three months ago on my 100th birthday. Chatty is very friendly, very patient, very knowledgeable, and very quick. It’s been a wonderful thing.
I’m a 4.0 student, but I also have four children. When I started using Chat GPT, I realized I could ask Chat GPT that question, and not only does it give me an answer, but it gives me an explanation.
Didn’t need tutoring as much. It gave me a life back. It gave me time for my family and time for me.
I have chronic nerve pain on my whole left half of my body. I have nerve damage. Had, like, a spine, a brain surgery.
And so I have, like, limited use of my left hand. Now you can just have the integration of voice input and then the newest one where you can have the back and forth dialogue. That’s just like maximum depth interface for me.
It’s. Here’s so we love hearing the stories of how people are using the technology. It’s really why we do all of this.
Okay, so now onto the new stuff, and we have got a lot. First, we’re going to talk about a bunch of improvements we’ve made, and then we’ll talk about where we’re headed next. Over the last year, we spent a lot of time talking to developers around the world.
We’ve heard a lot of your feedback. It’s really informed what we have to show you today. Today we are launching a new model, GPT four Turbo.
GPT Four Turbo will address many of the things that you all have asked for. So let’s go through what’s new. We’ve got six major things to talk about for this part.
Number one, context length. A lot of people have tasks that require a much longer context length. GPT four, supported up to eight K, and in some cases up to 32K context length.
But we know that isn’t enough for many of you and what you want to do. GPT Four turbo supports up to 128,000 tokens of context. That’s 300 pages of a standard book, 16 times longer than our eight K context.
And in addition to a longer context length, you’ll notice that the model is much more accurate over a long context. Number two, more control. We’ve heard loud and clear that developers need more control over the model’s responses and outputs.
So we’ve addressed that in a number of ways. We have a new feature called JSON mode, which ensures that the model will respond with valid JSON. This has been a huge developer request.
It’ll make calling APIs much easier. The model is also much better at function calling. You can now call many functions at once, and it’ll do better at following instructions.
In general, we’re also introducing a new feature called Reproducible outputs. You can pass a seed parameter, and it’ll make the model return consistent outputs. This, of course, gives you a higher degree of control over model behavior.
This rolls out in beta today, and in the coming weeks, we’ll roll out a feature to let you view log probes in the API. All right. Number three, better world knowledge.
You want these models to be able to access better knowledge about the world. So do we. So we’re launching retrieval in the platform.
You can bring knowledge from outside documents or databases into whatever you’re building. We’re also updating the Knowledge cutoff. We are just as annoyed as all of you, probably more that GPT Four’s knowledge about the world ended in 2021.
We will try to never let it get that out of date again. GPT Four Turbo has knowledge about the world up to April of 2023, and we will continue to improve that over time. Number four, new modalities.
Surprising no one. Dolly Three, GPT Four Turbo with Vision, and the new text to speech model are all going into the API today. We have a handful of customers that have just started using Dolly three to programmatic programmatically generate images and designs.
Today, Coke is launching a campaign that lets its customers generate Devali cards using Dolly Three. And of course, our safety systems help developers protect their applications against misuse. Those tools are available in the API.
GPT Four turbo can now accept images as inputs via the API, can generate captions, classifications, and analysis. For example, be my eyes uses this technology to help people who are blind or have low vision with their daily tasks, like identifying products in front of them. And with our new text to speech model, you’ll be able to generate incredibly natural sounding audio from text in the API with six preset voices to choose from.
I’ll play an example. Did you know that Alexander Graham Bell, the eminent inventor, was enchanted by the world of sounds? His ingenious mind led to the creation of the graphophone, which etched sounds onto wax, making voices whisper through time. This is much more natural than anything else we’ve heard out there.
Voice can make apps more natural to interact with and more accessible. It also unlocks a lot of use cases like language learning and voice assistance. Speaking of new modalities, we’re also releasing the next version of our open source speech recognition modEl, Whisper V three, today, and it’ll be coming soon to the API.
It features improved performance across many languages, and we think you’re really going to like it. Okay, number five, customization fine tuning has been working really well for GPT-3 Five since we launched it a few months ago. Starting today, we’re going to expand that to the 16K version of the model.
Also starting today, we’re inviting active fine tuning users to apply for the GPT four Fine tuning Experimental Access program. The Fine Tuning API is great for adapting our models to achieve better performance in a wide variety of applications with a relatively small amount of data. But you may want a model to learn a completely new knowledge domain or to use a lot of proprietary data.
So today we’re launching a new program called Custom Models. With custom models, our researchers will work closely with a company to help them make a great custom model, especially for them and their use case using our tools. This includes modifying every step of the model training process, doing additional domain specific pretraining, a custom RL post training process tailored for a specific domain, and whatever else.
We won’t be able to do this with many companies to start. It’ll take a lot of work, and in the interest of expectations, at least initially, it won’t be cheap. But if you’re excited to push things as far as they can currently go, please get in touch with us and we think we can do something pretty great.
Okay, and then number six, higher rate limits. We’re doubling the tokens per minute for all of our established GPT four customers so that it’s easier to do more. And you’ll be able to request changes to further rate limits and quotas directly in your API account settings.
In addition to these rate limits, it’s important to do everything we can do to make you successful. Building on our platform. So we’re introducing copyright Shield.
Copyright Shield means that we will step in and defend our customers and pay the costs incurred if you face legal claims around copyright infringement. And this applies both to chat GPT Enterprise and the API. And let me be clear, this is a good time to remind people we do not train on data from the API or chat GPT enterprise ever.
All right, there’s actually one more developer request that’s been even bigger than all of these, and so I’d like to talk about that now. And that’s pricing. GPT Four Turbo is the industry leading model.
It delivers a lot of improvements that we just covered, and it’s a smarter model than GPT four. We’ve heard from developers that there are a lot of things that they want to build, but GPT four just cost too much. They’ve told us that if we could decrease the cost by 2020 5%, that would be great.
A huge leap forward. I’m super excited to announce that we worked really hard on this. And GPT four Turbo, a better model, is considerably cheaper than GPT four by a factor of three X for prompt tokens and two X for completion tokens starting today.
So the new pricing is prompt tokens and completion tokens. For most customers, that will lead to a blended rate more than 2.75 times cheaper to use for GPT four Turbo than GPT four.
We worked super hard to make this happen. We hope you’re as excited about it as we are. So we decided to prioritize price first because we had to choose one or the other.
But we’re going to work on speed next. We know that speed is important too. Soon you will notice GPT four Turbo becoming a lot faster.
We’re also decreasing the cost of GPT 3.5 Turbo 16K. Also, input tokens are three X less and output tokens are two X less, which means the GPT now cheaper than the previous GPT-3 five 4K model, running a fine tuned GPT 3.5
Turbo 16K version is also cheaper than the old fine tuned 4K version. Okay, so we just covered a lot about the model itself. We hope that these changes address your feedback.
We’re really excited to bring all of these improvements to everybody. Now, in all of this, we’re lucky to have a partner who is instrumental in making it happen. So I’d like to bring on a special guest, Satya Nadella, the CEO of Microsoft.
Good to see you. Thank you so much. Thank you, Satya, thanks so much for coming here.
It’s fantastic to be here. And Sam, congrats. I mean, I’m really looking forward to Turbo and everything else that you have coming.
It’s been just fantastic partnering with you guys. Two questions won’t take too much of your time. How is Microsoft thinking about the partnership currently? Look, first, we love you guys.
Look, it’s been fantastic for us. In fact, I remember the first time, I think you reached out and said, hey, do you have some Azure credits? We’ve come a long way from there. Thank you for that.
That was great. You guys have built something magical. I mean, quite frankly, there are two things for us when it comes to the partnership.
The first is these workloads. And even when I was listening backstage to how you’re describing what’s coming even, it’s just so different and new. I’ve been in this infrastructure business for three decades.
No one has ever seen infrastructure and the workload, the pattern of the workload. These training jobs are so synchronous and so large and so data parallel. And so the first thing that we have been doing is building in partnership with you, the system, all the way from thinking from power to the DC to the rack to the accelerators to the network.
And just really the shape of Azure is drastically changed and is changing rapidly in support of these models that you’re building. And so our job number one, is to build the best systems so that you can build the best models and then make that all available to developers. And so the other thing is, we ourselves are a developer, so we’re building products.
In fact, my own conviction of this entire generation of foundation models completely changed the first time I saw GitHub Copilot on GPT. And so we want to build our copilot, GitHub Copilot all as developers on top of OpenAi APIs. And so we are very committed to that.
And what does that mean to developers? Look, I always think of Microsoft as a platform company, a developer company, and a partner company. And so we want to make, for example, we want to make GitHub copilot available as the Enterprise edition, available to all the attendees here so that they can try it out. That’s awesome.
Yeah, we’re very excited about that. And you can count on us to build the best infrastructure in Azure with your API support and bring it to all of you, and then even things like the Azure marketplace. So for developers who are building products out here to get to market rapidly.
So that’s sort of really our intent here. Great. And how do you think about the future future of the partnership or future of AI or whatever.
Yeah, anything you want. There are a couple of things for me that I think are going to be very key for us. Right.
One is I just described how the systems that are needed as you aggressively push forward on your roadmap, requires us to be on the top of our game. And we intend fully to commit ourselves deeply to making sure you all, as builders of these foundation models, have not only the best systems for training and inference, but the most compute so that you can keep pushing. We appreciate forward on the frontiers because I think that’s the way we’re going to make progress.
The second thing I think both of us care about, in fact, quite frankly, the thing that excited both sides to come together, is your mission. And our mission. Our mission is to empower every person and every organization on the planet to achieve more.
And to me, ultimately, AI is only going to be useful if it truly does empower. Right. I mean, I saw the video you played early.
I mean, that was fantastic. To hear those voices describe what AI meant for them and what they were able to achieve. So ultimately it’s about being able to get the benefits of AI broadly disseminated to everyone, I think is going to be the goal for us.
And then the last thing is, of course, we are very grounded in the fact that safety matters. And safety is not something that you’d care about later, but it’s Something we do shift left on, and we are very, very focused on that with you all. Great.
Well, I think we have the best partnership in tech. I’m excited for us to build AGI together. No, I’m really excited.
Have a fantastic. Thank you very much for coming. Thank you so much.
See ya. Okay, so we have shared a lot of great updates for developers already, and we got a lot more to come. But even though this is a developer conference, we can’t resist making some improvements to chat GPT.
So a small one. Chat GPT now uses GPT four turbo with all the latest improvements, including the latest knowledge cutoff, which we’ll continue to update. That’s all live today.
It can now browse the web when it needs to, write and run code, analyze data, take and generate images, and much more. And we heard your feedback. That model picker, extremely annoying.
That is gone. Starting today, you will not have to click around the drop down menu. All of this will just work together.
Chat GPT yeah, Chat GPT will just know what to use and when you need it. But that’s not the main thing, and neither was price actually, the main developer request, there was one that was even bigger than that. And I want to talk about where we’re headed and the main thing we’re here to talk about today.
So we believe that if you give people better tools, they will do amazing things. We know that people want AI that is smarter, more personal, more customizable, can do more on your behalf. Eventually, you’ll just ask a computer for what you need and it’ll do all of these tasks for you.
These capabilities are often talked in the AI field about as agents. The upsides of this are going to be tremendous. At OpenAI, we really believe that gradual iterative deployment is the best way to address the safety issues, the safety challenges with AI, we think it’s especially important to move carefully towards this future of agents.
It’s going to require a lot of technical work and a lot of thoughtful consideration by society. So today we’re taking our first small step that moves us towards this future. We’re thrilled to introduce GPTs.
GPTs are tailored versions of chat GPT for a specific purpose. You can build a GPT, a customized version of chat GPT for almost anything, with instructions, expanded knowledge and actions, and then you can publish it for others to use. And because they combine instructions, expanded knowledge and actions, they can be more helpful to you.
They can work better in many contexts, and they can give you better control. They’ll make it easier for you to accomplish all sorts of tasks or just have more fun. And you’ll be able to use them right within chat GPT.
You can, in effect, program a GPT with language. Just by talking to it. It’s easy to customize the behavior so that it fits what you want.
This makes building them very accessible, and it gives agency to everyone. So we’re going to show you what GPTs are, how to use them, how to build them, and then we’re going to talk about how they’ll be distributed and discovered. And then after that, for developers, we’re going to show you how to build these agentlike experiences into your own apps.
So first, let’s look at a few examples. Our [email protected] are working hard to expand computer science in schools.
They’ve got a curriculum that is used by tens of millions of students worldwide. Code Crafted Lesson Planner GPT to help teachers provide a more engaging experience for middle schoolers. If a teacher asks it to explain for loops in a creative way, it does just that.
In this case, it’ll do it in terms of a video game character, repeatedly picking up coins, super easy to understand for an 8th grader. As you can see, this GPT brings together Code Org’s extensive curriculum and expertise and lets teachers adapt it to their needs quickly and easily. Next, Canva has built a GPT that lets you start designing by describing what you want in natural language.
If you say make a poster for a Dev Day reception this afternoon, this evening, and you give it some details, it’ll generate a few options to start with by hitting canvas APIs. Now, this concept may be familiar to some of you. We’ve evolved our plugins to be custom actions for GPTs.
You can keep chatting with this to see different iterations, and when you see one you like, you can click through to canva for the full design experience. So now we’d like to show you a GPT live. Zapier has built a GPT that lets you perform actions across 6000 applications to unlock all kinds of integration possibilities.
I’d like to introduce Jessica, one of our solutions architects who is going to drive this demo. Welcome, Jessica. Thank you.
Thank you all. Thank you all for being here. My name is Jessica Shea.
I work with partners and customers to bring their product alive. And today I can’t wait to show you how hard we’ve been working on this. So let’s get started.
So, to start, where your GPT will live is on this upper left corner. I’m going to start with clicking on the Zapier AI actions. And on the right hand side, you can see that’s my calendar for today.
So it’s quite a day. I’ve already used this before, so it’s actually already connected to my calendar. To start, I can ask what’s on my schedule for today.
We build GPTs with security in mind. So before it performs any action or share data, it will ask for your permission. So right here, I’m going to say allowed.
So GBT is designed to take in your instructions, make the decision on which capability to call to perform that action, and then execute that for you. So you can see right here, it’s already connected to my calendar. It pulls into my information and then I’ve also prompted it to identify conflicts on my calendar.
So you can see right here, it actually was able to identify that. So it looks like I have something coming up. So what if I want to let Sam know that I have to leave early? So right here, I say, let Sam know I gotta go chasing GPUs.
So with that, I’m going to swap to my conversation with Sam, and then I’m going to say, yes, please run that, Sam did you get that? I did. Awesome. So this is only a glimpse of what is possible, and I cannot wait to see what you all will build.
Thank you. And back to you, Sam. Thank you, Jessica.
So those are three great examples. In addition to these, there are many more kinds of GPTs that people are creating and many, many more that will be created soon. We know that many people who want to build the GPT don’t know how to code.
We’ve made it so that you can program a GPT just by having a conversation. We believe that natural language is going to be a big part of how people use computers in the future, and we think this is an interesting early example. So I’d like to show you how to build one.
All right. So I want to create a GPT that helps give founders and developers advice when starting new projects. I’m going to go to create a GPT here and this drops me into the GPT builder.
I worked with founders for years at YC, and still whenever I meet developers, the questions I get are always about how do I think about a business idea? Can you give me some advice? I’m going to see if I can build a GPT to help with that. So to start, GPT Builder asks me what I want to make and I’m going to say I want to help startup founders think through their business ideas and get advice. After the founder has gotten some advice, grill them on why they are not growing faster.
All right, so to start off, I just tell the GPT a little bit about what I want here and it’s going to go off and start thinking about that. And it’s going to write some detailed instructions for the GPT. It’s also going to, let’s see, ask me about a name.
How do I feel about Startup Mentor? That’s fine. That’s good. So if I didn’t like the name, of course I could call it something else.
But it’s going to try to have this conversation with me and start there. And you can see here on the right in the preview mode that it’s already starting to fill out the GPT where it says what it does. It has some ideas of additional questions that I could ask.
So it just generated a candidate. Of course, I could regenerate that or change it, but I sort of like that. So I will say, that’s great.
And you see now that the GPT is being built out a little bit more as we go. Now what I want this to do, how it can interact with users, I could talk about style here. But what I’m going to say is I am going to upload transcripts of some lectures about startups I have given.
Please give advice based off of those. All right, so now, good morning. Thank you for joining us today.
Please welcome to the stage Sam Altman. Good morning. Welcome to our first ever OpenAI Dev Day.
We’re thrilled that you’re here and this energy is awesome. And welcome to San Francisco. San Francisco has been our home since day one.
The city is important to us and to the tech industry in general. We’re looking forward to continuing to grow here. So we’ve got some great stuff to announce today.
But first, I’d like to take a minute to talk about some of the stuff that we’ve done over the past year. About a year ago, November 30, we shipped Chat GPT as a low key research preview, and that went pretty well. In March, we followed that up with the launch of GPT Four, still the most capable model out in the world.
And in the last few months, we launched voice and vision capabilities so that chat GPT can now see, hear and speak. And more recently, there’s a lot you don’t have to clap each time. And more recently, we launched Dolly Three, the world’s most advanced image model.
You can use it, of course, inside of chat GPT for our enterprise customers, we launched Chat GPT Enterprise, which offers enterprise grade security and privacy, higher speed GPT four, access, longer context Windows, lot more. Today we’ve got about 2 million developers building on our API for a wide variety of use cases doing amazing stuff. Over 92% of Fortune 500 companies building on our products and we have about 100 million weekly active users now on chat GBT.
And what’s incredible on that is we got there entirely through word of mouth. People just find it useful and tell their friends. OpenAI is the most advanced and the most widely used AI platform in the world now, but numbers never tell the whole picture on something like this.
What’s really important is how people use the products, how people are using AI. And so I’d like to show you a quick video. I actually wanted to write something to my dad in Tagalog.
I want a non romantic way to tell my parent that I love him, and I also want to tell him that he can rely on me, but in a way that still has the respect of a child to parent relationship that you should have in Filipino culture and in Tagalog grammar when it’s translated into Gala, I love you very deeply and I will be with you no matter where the path leads, I see some of the possibility. I was like, whoa. Sometimes I’m not sure about some stuff and I feel like actually chat if you tell, hey, this is what I’m thinking about.
So it kind of give you that more confidence. The first thing that blew my mind was it levels with you. That’s something that a lot of people struggle to do.
It opened my mind to just what every creative could do if they just had a person helping them out who listens. So this is to represent sickling hemoglobin. And you built that with Chad GPT.
Chad GPT built it with me. I started using it for daily activities like, hey, here’s a picture of my fridge. Can you tell me what I’m missing? Because I’m going grocery shopping and I really need to do recipes that are following my vegan diet.
As soon as we got access to code interpreter, I was like, wow, this thing is awesome. It could build spreadsheets, it could do anything. I discovered Chatty about three months ago on my 100th birthday.
Chatty is very friendly, very patient, very knowledgeable, and very quick. It’s been a wonderful thing. I’m a 4.0
student, but I also have four children. When I started using Chat GPT, I realized I could ask Chat GPT that question, and not only does it give me an answer, but it gives me an explanation. Didn’t need tutoring as much.
It gave me a life back. It gave me time for my family and time for me. I have chronic nerve pain on My whole left half of my body of nerve damage had, like, a spine brain surgery.
And so I have, like, limited use of my left hand. Now you can just have the integration of voice input and then the newest one where you can have the back and forth dialogue. That’s just like maximum depth interface for me.
It’s. Here’s so we love hearing the stories of how people are using the technology. It’s really why we do all of this.
Okay, so now onto the new stuff, and we have got a lot. First we’re going to talk about a bunch of improvements we’ve made, and then we’ll talk about where we’re headed next. Over the last year, we spent a lot of time talking to developers around the world.
We’ve heard a lot of your feedback. It’s really informed what we have to show you today. Today we are launching a new model, GPT four turbo.
GPT Four turbo will address many of the things that you all have asked for. So let’s go through what’s new we’ve got six major things to talk about for this part. Number one, context length.
A lot of people have tasks that require a much longer context length. GPT Four supported up to eight K, and in some cases up to 32K context length. But we know that isn’t enough for many of you and what you want to do.
GPT Four turbo supports up to 128,000 tokens of context. That’s 300 pages of a standard book, 16 times longer than our eight K context. And in addition to a longer context length, you’ll notice that the model is much more accurate over a long context.
Number two, more control. We’ve heard loud and clear that developers need more control over the model’s responses and outputs. So we’ve addressed that in a number of ways.
We have a new feature called JSON mode, which ensures that the model will respond with valid JSON. This has been a huge developer request. It’ll make calling APIs much easier.
The model is also much better at function calling. You can now call many functions at once, and it’ll do better at following instructions. In general, we’re also introducing a new feature called Reproducible OutpuTS.
You can pass a seed parameter, and it’ll make the model return consistent outputs. This, of course, gives you a higher degree of control over model behavior. This rolls out in beta today, and in the coming weeks, we’ll roll out a feature to let you view log probes in the API.
All right. Number three, better World Knowledge. You want these models to be able to access better knowledge about the world.
So do we. So we’re launching retrieval in the platform. You can bring knowledge from outside documents or databases into whatever you’re building.
We’re also updating the Knowledge cutoff. We are just as annoyed as all of you, probably more, that GPT Four’s knowledge about the world ended in 2021. We will try to never let it get that out of date again.
GPT Four Turbo has knowledge about the world up to April of 2023, and we will continue to improve that over time. Number four, new modalities. Surprising no one.
Dolly Three, GPT Four Turbo with Vision, and the new text to speech model are all going into the API. Today, we have a handful of customers that have just started using Dolly Three to programmatic. Programmatically generate images and designs.
Today, Coke is launching a campaign that lets its customers generate Devali cards using Dolly three. And of course, our safety systems help developers protect their applications against misuse. Those tools are available in the API.
GPT Four Turbo can now accept images as inputs via the API can generate captions, classifications, and analysis. For example, be my eyes uses this technology to help people who are blind or have low vision with their daily tasks like identifying products in front of them. And with our new text to speech model, you’ll be able to generate incredibly natural sounding audio from text in the API with six preset voices to choose from.
I’ll play an example. Did you know that Alexander Graham Bell, the eminent inventor, was enchanted by the world of sounds? His ingenious mind led to the creation of the graphophone, which etched sounds onto wax, making voices whisper through time. This is much more natural than anything else we’ve heard out there.
Voice can make apps more natural to interact with and more accessible. It also unlocks a lot of use cases like language learning and voice assistance. Speaking of new modalities, we’re also releasing the next version of our open source speech recognition model, Whisper V three, today, and it’ll be coming soon to the API.
It features improved performance across many languages, and we think you’re really going to like it. Okay, number five, customization Fine tuning has been working really well for GPT 3.5 since we launched it a few months ago.
Starting today, we’re going to expand that to the 16K version of the model. Also starting today, we’re inviting active fine tuning users to apply for the GPT four fine tuning Experimental Access program. The Fine tuning API is great for adapting our models to achieve better performance in a wide variety of applications with a relatively small amount of data.
But you may want a model to learn a completely new knowledge domain, or to use a lot of proprietary data. So today we’re launching a new program called Custom Models. With custom models, our researchers will work closely with a company to help them make a great custom model, especially for them and their use case using our tools.
This includes modifying every step of the model training process, doing additional domain specific pretraining, a custom RL post training process tailored for a specific domain, and whatever else. We won’t be able to do this with many companies to start. It’ll take a lot of work, and in the interest of expectations, at least initially, it won’t be cheap, but if you’re excited to push things as far as they can currently go, please get in touch with us and we think we can do something pretty great.
Okay, and then number six, higher rate limits. We’re doubling the tokens per minute for all of our established GPT four customers so that it’s easier to do more and you’ll be able to request changes to further rate limits and quotas directly in your API account settings. In addition to these rate limits, it’s important to do everything we can do to make you successful building on our platform.
So we’re introducing Copyright Shield. Copyright Shield means that we will step in and defend our customers and pay the costs incurred if you face legal claims around copyright infringement. And this applies both to chat GPT Enterprise and the API.
And let me be clear, this is a good time to remind people we do not train on data from the API or chat GPT Enterprise ever. All right, there’s actually one more developer request that’s been even bigger than all of these, and so I’d like to talk about that now. And that’s pricing.
GPT Four Turbo is the industry leading model. It delivers a lot of improvements that we just covered, and it’s a smarter model than GPT four. We’ve heard from developers that there are a lot of things that they want to build, but GPT four just costs too much.
They’ve told us that if we could decrease the cost by 2020 5%, that would be great. A huge leap forward. I’m super excited to announce that we worked really hard on this.
And GPT four Turbo, a better model, is considerably cheaper than GPT four by a factor of three X for prompt tokens and two X for completion tokens starting today. So the new pricing is prompt tokens and completion tokens. For most customers.
That will lead to a blended rate more than 2.75 times cheaper to use for GPT four Turbo than GPT four. We worked super hard to make this happen.
We hope you’re as excited about it as we are you. So we decided to prioritize price first because we had to choose one or the other. But we’re going to work on speed next.
We know that speed is important too. Soon you will notice GPT four turbo becoming a lot faster. We’re also decreasing the cost of GPT 3.5
Turbo 16K. Also, input tokens are three X less and output tokens are two X less, which means the GPT now cheaper than the previous GPT 3.54K model running a fine tuned GPT 3.5
Turbo 16K version is also cheaper than the old fine tuned 4K version. Okay, so we just covered a lot about the model itself. We hope that these changes address your feedback.
We’re really excited to bring all of these improvements to everybody. Now, in all of this, we’re lucky to have a partner who is instrumental in making it happen. So I’d like to bring on a special guest, Satya Nadella, the CEO of Microsoft.
Good to see you. Thank you so much. Thank you.
Satya, thanks so much for coming here. It’s fantastic to be here. And Sam, congrats.
I mean, I’m really looking forward to Turbo and everything else that you have coming. It’s been just fantastic partnering with you guys. Two questions won’t take too much of your time.
How is Microsoft thinking about the partnership currently? Look, first, we love you guys. Look, it’s been fantastic for us. In fact, I remember the first time, I think you reached out and said, hey, do you have some Azure credits? We’ve come a long way from there.
Thank you for that. That was great. You guys have built something magical.
I mean, quite frankly, there are two things for us when it comes to the partnership. The first is these workloads. And even when I was listening backstage to how you’re describing what’s coming, even, it’s just so different and new.
I’ve been in this infrastructure business for three decades. No one has ever seen infrastructure and the workload, the pattern of the workload. These training jobs are so synchronous and so large and so data parallel.
And so the first thing that we have been doing is building in partnership with you, the system, all the way from thinking from power to the DC to the rack to the accelerators to the network. And just really the shape of Azure is drastically changed and is changing rapidly in support of these models that you’re building. And so our job number one, is to build the best systems so that you can build the best models and then make that all available to developers.
And so the other thing is, we ourselves are a developer, so we’re building products. In fact, my own conviction of this entire generation of foundation models completely changed the first time I saw GitHub Copilot on GPT. And so we want to build our Copilot, GitHub Copilot, all as developers on top of OpenAI APIs.
And so we are very committed to that. And what does that mean to developers? Look, I always think of Microsoft as a platform company, a developer company, and a partner company. And so we want to make, for example, we want to make GitHub Copilot available as the Enterprise edition, available to all the attendees here.
