OpenAI is a popular AI research company that has created some of the most powerful general-purpose AI models. OpenAI primarily makes money via API fees. The company also makes money from token fees.
Founded in 2016 by Sam Altman and Elon Musk, OpenAI was created to further the advancement of AI research in a safe and transparent manner. During its initial stage, OpenAI only had nine researchers. In 2018, Elon Musk left the company’s board to focus on SpaceX and Tesla.
In 2019, OpenAI Five defeated the Dota 2 world champions OG who had won $15.6 million by competing against the world’s top Dota 2 teams. OpenAI released the world’s most powerful AI language model, GPT, in 2018. In 2022, OpenAI released DALL.E 2, which is an AI that generates images based on text descriptions.
What is OpenAI & How Does It Work?
OpenAI develops, trains, and maintains artificial intelligence (AI) models for general-purpose tasks such as reading, writing, coding, and image processing. The company is built around the goal of researching general-purpose AI technology that can be used for everyday tasks. It aims to create safe, innovative, and transparent solutions for improving human life.
To date, OpenAI has researched and developed several AI models. The first product made by OpenAI was Gym, a sandbox environment for experimenting with the idea of reinforcement learning. This is a subset of machine learning that deals with general decision-making and motor control within a dynamic environment.
Gym’s reinforcement learning model can be accessed through its API. This is useful for solving problems related to automation, business management, and various other scenarios. Gym comes with a set of predefined environments, each designed to simulate a specific task.
Currently, Gym’s code is available in the form of an open-source Python library. It is used by machine learning enthusiasts and researchers from all over the world for benchmarking. Shortly after releasing Gym, OpenAI released Universe which is a software platform to measure and train AIs across a wide range of tasks.
Universe is designed to simulate the action of an AI using a computer like a human. By making the AI play a variety of games through a virtual keyboard and mouse, OpenAI assesses its ability to solve various real-world problems. Universe can also be used to create new environments for Gym.
OpenAI also has an AI model that translates natural human languages into code. It is proficient in several programming languages and can carry out complex instructions that involve nested tasks. Codex can be used to create any kind of software application.
It can also be used to communicate directly with a machine or process large datasets in unique ways. Codex can mix and match multiple languages or translate instructions from one language into another. The AI model shows its best performance while working with Python.
While signing up, OpenAI asks for basic information like their name and email. Users can also mention why they want to use Codex, although this is optional. Once users have created an OpenAI account, they can go into their dashboard and view all relevant information
OpenAI users can also sign up for a paid API account to start using their AI models immediately and with fewer restrictions. The OpenAI API can be used to create any type of application.
However, OpenAI requires that users submit their application for review prior to launch. The review process takes one to three days, and 97% of applications get approved with minimal or no changes.
After making an account, users are automatically credited with $18 in funds. This credit lasts up to three months past the account creation date. Each user’s dashboard has a graph that displays API usage, in terms of date and cost. The person who creates an account is the owner and has special privileges.
Account owners can add readers who perform basic API calls and can read organizational data. Readers cannot modify billing information or grant new privileges. The dashboard also allows account owners to manage their company information and add monthly usage limits.
Each account gets an API key which is required to authenticate the calling program with OpenAI’s API. If OpenAI detects that one of its API keys has been leaked, it will automatically refresh the existing key for an account. Users can also request a new key manually.
Currently, OpenAI has four AI models, each with its own pricing tier. Usage is measured in terms of tokens. Ada costs $0.0004 per 1000 tokens and is the fastest model. In comparison, Davinci costs $0.02 and is the most powerful model offered by OpenAI.
Tokens are a measure of words, which is how the AI models are fed instructions. OpenAI provides rates based on thousands of tokens.
Ada costs $0.0004 for 1,000 tokens. That is the equivalent to roughly 750 words. Users can fine-tune OpenAI’s base models or embed models into their projects. Training an AI model costs less than using it. For example, with Ada the training cost is $0.0004 per 1,000 tokens, and the usage cost is $0.0016 per 1,000 tokens.
Initially, each paid member is offered a maximum limit on how much they can train or use each model. This usage quota is modified over time as users submit their applications for review. Users can also request a quota increase.
Business Model of OpenAI
OpenAI follows a freemium business model. Initially, users are provided with free tokens on their account, which last for up to three months and can be used to access the OpenAI API. But once they use up those tokens or exceed the free review period, a paid membership must be purchased to keep using the API.
By giving users access to most of the API features for a brief duration at the start, OpenAI generates engagement. It encourages developers to use its API for their project and provides them with the necessary management tools within its dashboard. Since they aren’t being charged during this stage, users have a high chance of going with OpenAI for their software as opposed to the AI model of a competitor.
OpenAI also operates in a market with few competitors. Most other AI companies make specialized models for specific tasks. In comparison, OpenAI researches artificial general intelligence (AGI) that can be applied to a wide spectrum of tasks.
Products like DALL.E provide unique opportunities for creative professionals and amateurs alike to experiment with the OpenAI ecosystem. Even though it isn’t a core revenue generator, DALL.E helps promote the OpenAI brand and drives user engagement. OpenAI’s DALL.E generates images in exchange for tokens used by a user and additional tokens can be purchased with money.
OpenAI isn’t entirely open source, but it is a lot more transparent than any other AI research organization. As a result, it fosters greater levels of trust within the community. Since OpenAI’s models can by anyone who pays for API access, a lot more people use them compared to AI models from other companies.
The company’s AI research and training require incredible amounts of raw computing power, which is often provided by Google and Amazon through their networks. For reference, the GPT-3 AI model reportedly cost OpenAI $12 million for a single training run. The OpenAI Five Dota 2 AI required 256 P100 GPUs and 128,000 CPU cores.
OpenAI’s initial non-profit approach wasn’t suitable for growth, which is why it created a limited-profit company called OpenAI LP. However, this pivot towards a commercialized structure raised doubts in the minds of existing OpenAI users and open-source contributors.
Because OpenAI has such intensive computational requirements, the company often relies on third-party providers for infrastructure. Its existing revenue streams may not be enough to create a cloud computing network of suitable scale to support the company’s long-term goals. Hence, OpenAI is reliant on venture capital funding at the moment.
OpenAI’s biggest rival is DeepMind, as they work on similar projects. DeepMind is an older company with more data and experience. It was also acquired by Google in 2014, which gives the company access to a larger resource pool in terms of capital and infrastructure.
However, DeepMind’s priorities are very different from that of OpenAI. OpenAI is focused on using AI to solve general problems. While DeepMind is interested in developing specialized solutions for science and industry.
OpenAI is also a more transparent company. It publishes more of its research data and training models compared to DeepMind. One of the company’s goals is to “democratize” AI, by giving everyone access to this technology.
There is no data on the financials of OpenAI, as it is a private company. It is hard to speculate on OpenAI’s operating costs.
OpenAI is estimated to have an annual revenue of $59.6 million per year, but it also has considerable expenses. These include things like infrastructure costs, research costs, staffing costs, and network costs.
Due to the lack of data on OpenAI’s financials, it is unclear how profitable the company’s business model is.
How Does OpenAI Make Money?
OpenAI makes money from two different revenue streams. These are API fees and token fees.
As OpenAI is a private company, details about how much revenue they generate from these different revenue streams aren’t public.
Whenever a user signs up on OpenAI’s website and creates an account, they are provided with $18 of free tokens that are valid for up to three months. If the tokens expire or get used up, new tokens must be purchased. Currently, OpenAI follows a pay as you go system.
Users are charged various rates for accessing OpenAI’s models. Ada costs $0.0004 to train and $0.0016 to use. These rates are calculated on the basis of 1,000 tokens, which roughly amount to 750 words.
Each user is provided with a quota. Usage quotas are adjusted once the user creates an application and submits it for review. Users can also request a quota increase.
To use OpenAI’s DALL.E text-to-image converter, users need tokens. Each user is given 50 credits during their first month, and 15 free credits for each month after that. One credit can be used for one prompt, to generate four images.
Additional credits cost money. OpenAI provides 115 credits for $15, which can be used to generate 460 images. Professionals and enthusiasts use more tokens as they often create variations from the default results by reinputting them into the system.
OpenAI Funding, Valuation & Revenue
OpenAI is currently a private company, and its financials aren’t available to the public. Right now, it is unclear what the company is valued at.
However, OpenAI raised $1 billion in funding over three rounds between 2016 and 2019. Notable investors include Microsoft, Khosla Ventures, Reid Hoffman Foundation, and Y Combinator. The company’s latest funding round was a corporate round in July 2019 led by Microsoft, which raised $1 billion.
Since 2019, the company hasn’t had any more funding rounds. That indicates that it has sufficient capital to continue operations and growth in the near future.
Annual revenue for OpenAI is estimated to be around $59.6 million, but there is no official report to verify this. In 2017, the company reported $33.2 million in total revenue with expenses of $28.6 million.
Is OpenAI Profitable?
OpenAI is likely not profitable. It relies heavily on venture capital funding from its investment partners to continue operations and invest in new infrastructure. OpenAI’s internal revenue streams don’t generate sufficient revenue to sustain long-term growth at a rate that is competitive with other AI giants in the industry.
However, the company’s models are considered some of the best available, and they continue to grow their business and revenue streams. There is a good chance that OpenAI will be profitable in the future.
So there you have it, a brief overview of how OpenAI makes money. OpenAI’s business model is fairly simple, but it’s also very effective.
If you’ve been following the news about AI, you’ll know that OpenAI is one of the most important companies in the space right now, and it’s going to be interesting to see how they continue to grow in the coming years.
It’s clear that this company is doing something right: not only is it growing rapidly, but it’s also making huge strides in the field of AI research and deployment. If they continue this trajectory and grow their user base, they could become one of the biggest names in AI development and deployment in no time at all!
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