OpenAI has built the foundational layer of the AI industry. With large generative models like GPT-3 and DALL-E, OpenAI offers API access to businesses that want to develop applications on top of its foundational models while being able to plug these models into their products and customize these models with proprietary data and additional AI features. On the other hand, OpenAI also released ChatGPT, developing around a freemium model. Microsoft also commercializes opener products through its commercial partnership.
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How much does OpenAI make today?
We don’t know the revenues of OpenAI, yet the company projected a billion in revenues by 2024, and according to Form 990, which is IRS’ primary tool for gathering information about tax-exempt organizations, OpenAI reported a $3.48 million in revenues in 2020.
This was the year when GPT-3 had been released, so we might assume that a good chunk of it was for the release of its APIs. It’s mostly speculation, which will need to be confirmed once/and if OpenAI LP will start releasing its financials.
Source propublica.org
OpenAI APIs
OpenAI monetized its generative models through its APIs, which can be accessed by any business to build new applications on top of these APIs.
As explained, the three layers of AI, the middle layer of AI, and the business applications layer of AI are leveraging these APIs to build verticalized engines that can perform specific functions much better than a generalized engine like GPT-3.
And on the other hand, the business applications layer can leverage the APIs to make any app smarter via AI.
Examples of how OpenAI’s APIs have been used so far at the consumer applications level comprise tools and products like GitHub Copilot and more.
ChatGPT
With the release of ChatGPT, OpenAI has expanded its consumer reach for its family of GPT models.
Indeed, pre-ChatGPT, these models could be used either via the OpenAI site or as small applications which were available through the site.
Yet, those were primarily a way to showcase the capabilities of OpenAI APIs.
With the release of ChatGPT, the whole OpenAI business model changed, and it moved from primarily B2B to a consumer-based businessmodel.
Indeed, ChatGPT has reached millions of users since its launch, and it’s now becoming a tool, like Google, that has captured the imagination of hundreds of millions of users.
ChatGPT leverages GPT underlying models, yet, it also uses InstructGPT models, as a way, via humans-in-the-loop, to fine-tune the capabilities of the conversational interface to get better at handling complex conversations and interactions.
ChatGPT is primarily available for free on the OpenAI website, and it might also be getting released as a premium version.
ChatGPT works a premium model, where the tool has been opened for paid users at a $20/mo plan.
In addition, in the future, ChatGPT might also be monetized via API access.
ChatGPT has been growing at an astounding rate.
To understand the difference between ChatGPT and GPT, you need to grasp how InstructGPT works.
InstructGPT is the successor to the GPT-3 large language model (LLM) developed by OpenAI.
ChatGPT Premium
ChatGPT is available as a premium version that can be accessed for $20/mo, enabling the user to get a faster version that performs better.
The functionalities are the same as the free version; what changes is speed, performance, and ability to have tasks completed with more tokens, compared to the free version, which might stop after a specific token request.
For instance, in the free version, if you ask ChatGPT to formulate a very long essay, that might stop at a certain point, whereas in the premium one, it should have no specific limits.
ChatGPT APIs
ChatGPT was also launched as an API endpoint.
Meaning it can be integrated via its APIs into any web application.
The ChatGPT model family we are releasing today, gpt-3.5-turbo, is the same model used in the ChatGPT product. It is priced at $0.002 per 1k tokens, which is 10x cheaper than our existing GPT-3.5 models. It’s also our best model for many non-chat use cases—we’ve seen early testers migrate from text-davinci-003 to gpt-3.5-turbo with only a small amount of adjustment needed to their prompts.
As OpenAI explains in its documentation, ChatGPT is powered by gpt-3.5-turbo, OpenAI’s most advanced language model.
Using the OpenAI API, you can build your applications with gpt-3.5-turbo to do things like:
Draft an email or other piece of writing
Write Python code
Answer questions about a set of documents
Create conversational agents
Give your software a natural language interface
Tutor in a range of subjects
Translate languages
Simulate characters for video games and much more
Foundry
OpenAI launched an enterprise service called Foundry, which is simply an expansion of the API service, but for enterprise clients to enable them to have a more solid infrastructure with a broader volume.
As explained by TechCrunch a lightweight version of GPT-3.5 will cost $78,000 for a three-month commitment or $264,000 over a one-year commitment.
OpenAI/Microsoft
OpenAI and Microsoft partnered up from a commercial standpoint. The history of the partnership started in 2016 and consolidated in 2019, with Microsoft investing a billion dollars into the partnership. It’s now taking a leap forward, with Microsoft in talks to put $10 billion into this partnership. Microsoft, through OpenAI, is developing its Azure AI Supercomputer while enhancing its Azure Enterprise Platform and integrating OpenAI’s models into its business and consumer products (GitHub, Office, Bing).
It’s now taking a leap forward, with Microsoft that put a few more billion into the partnership, with multi-year commercial agreements, where Microsoft keeps providing the infrastructure needed for OpenAI to grow while, Microsoft gets a commercial partnership to distribute and integrate OpenAI’s products!
Microsoft is the main investor in the OpenAI LP, which is a for-profit, yet capped entity, created by the OpenAI foundation to gather capital from the private sector.
In 2019, the partnership strengthened, with Microsoft putting a billion dollars into the partnership.
Today, Azure is among the top players in the cloud industry, together with Amazon AWS.
In the last decade, cloud providers have enabled hundreds of startups. It’s not a secret that AWS, by the early 2010s, empowered a class of startups that later became prominent tech companies (Netflix, Uber, Slack and many others).
Yet, from the 2020s, in the future, the cloud industry playfield has changed, and it’s skewed toward AI.
In other words, large generative models, like GPT-3 and forward, to be released in the first place, need a huge amount of computational power, which today can be provided only by a few players.
Differentiating a cloud business to become the underlying infrastructure for AI is a critical component to ensure the cloud offering doesn’t get commoditized over time.
In fact, cloud players like Microsoft and Amazon have enjoyed high-profit margins in the last years, thanks to the lack of competition and their massive infrastructure.
Yet, in the next decade, with AI models taking over the world, cloud computing might get commoditized.
Unless you develop it around AI. Which is what Microsoft is doing via its Azure AI Supercomputing technology.
In other words, the partnership between OpenAI and Microsoft, since 2016, has given Microsoft Azure’s team an important sight into how to build supercomputers that could help AI companies to build custom AI models.
This is the first key strategic advantage that Microsoft has gained from its partnership with OpenAI.
The development of its cloud AI infrastructure.
Microsoft Azure Enterprise Platform
In addition to that, Microsoft Azure is integrating all OpenAI’s products within its business and enterprise platform.
This integration enables Azure to become the go-to enterpriseplatform for the development of custom AI models, which can be integrated into the workflow of any business.
Integration into Microsoft Business And Consumer Applications
Another key benefit of the partnership between Microsoft and OpenAI is the integration of these AI models within Microsoft’s business and consumer applications products.
Some examples comprise the release of GitHub Copilot, an AI-based tool to write code much faster by leveraging GPT-3.
Or the fact that Microsoft is looking into ways to integrate these AI models within its other products, like Bing and Office.
Another large bet Microsoft might make is about integrating these AI models within its AR interfaces (HoloLens) as general-purpose assistants that can make those devices much more valuable.
The AI App Store?
By combining AI as an interface with a hardware device like HoloLens, and an operating system, like Windows Holographic OS, Microsoft and OpenAI might come up with the next App Store for AR?
How does OpenAI corporate and organizational structure work?
OpenAI is an artificial intelligence research laboratory that transitioned into a for-profit organization in 2019. The corporate structure is organized around two entities: OpenAI, Inc., which is a single-member Delaware LLC controlled by OpenAI non-profit, And OpenAI LP, which is a capped, for-profit organization. The OpenAI LP is governed by the board of OpenAI, Inc (the foundation), which acts as a General Partner. At the same time, Limited Partners comprise employees of the LP, some of the board members, and other investors like Reid Hoffman’s charitable foundation, Khosla Ventures, and Microsoft, the leading investor in the LP.
Key Highlights
OpenAI’s Foundational Role in AI Industry:
OpenAI has developed large generative models like GPT-3 and DALL-E.
These models are made accessible through APIs, enabling businesses to build applications on top of them.
OpenAI allows customization of these models with proprietary data and additional AI features.
Large language models (LLMs) are AI tools that can read, summarize, and translate text. This enables them to predict words and craft sentences that reflect how humans write and speak.
Prompt engineering is a natural language processing (NLP) concept that involves discovering inputs that yield desirable or useful results.
Like most processes, the quality of the inputs determines the quality of the outputs in prompt engineering. Designing effective prompts increases the likelihood that the model will return a response that is both favorable and contextual.
Developed by OpenAI, the CLIP (Contrastive Language-Image Pre-training) model is an example of a model that utilizes prompts to classify images and captions from over 400 million image-caption pairs.
OpenAI has built the foundational layer of the AI industry. With large generative models like GPT-3 and DALL-E, OpenAI offers API access to businesses that want to develop applications on top of its foundational models while being able to plug these models into their products and customize these models with proprietary data and additional AI features. On the other hand, OpenAI also released ChatGPT, developing around a freemium model. Microsoft also commercializes opener products through its commercial partnership.
OpenAI and Microsoft partnered up from a commercial standpoint. The history of the partnership started in 2016 and consolidated in 2019, with Microsoft investing a billion dollars into the partnership. It’s now taking a leap forward, with Microsoft in talks to put $10 billion into this partnership. Microsoft, through OpenAI, is developing its Azure AI Supercomputer while enhancing its Azure Enterprise Platform and integrating OpenAI’s models into its business and consumer products (GitHub, Office, Bing).
Stability AI is the entity behind Stable Diffusion. Stability makes money from our AI products and from providing AI consulting services to businesses. Stability AI monetizes Stable Diffusion via DreamStudio’s APIs. While it also releases it open-source for anyone to download and use. Stability AI also makes money via enterprise services, where its core development team offers the chance to enterprise customers to service, scale, and customize Stable Diffusion or other large generative models to their needs.
Gennaro is the creator of FourWeekMBA, which reached about four million business people, comprising C-level executives, investors, analysts, product managers, and aspiring digital entrepreneurs in 2022 alone | He is also Director of Sales for a high-tech scaleup in the AI Industry | In 2012, Gennaro earned an International MBA with emphasis on Corporate Finance and Business Strategy.
