OpenAI Set to Make Extensive Changes to Developer Offerings

OpenAI is planning a major overhaul of its developer program. The company aims to reduce the cost of its APIs in an effort to convince more companies to utilize its tools for building applications. This comes as analysts predict that generative AI will face a “cold shower” next year due to higher costs and lower demand as the hype begins to fade.

OpenAI is opening up more of its technology to third-party developers and reducing the cost of API calls (Photo: rafapress / Shutterstock)

The changes could result in the AI lab making the cost of API calls up to 20 times cheaper. This is partly due to a decrease in the cost per token and improved memory storage, as reported by Reuters.

OpenAI and its competitors are increasingly seeking ways to monetize their products. Tech giants like Google and Microsoft are also offering incentives such as developer platforms and governance resources to facilitate traceability.

The company also plans to offer the new vision capabilities recently introduced in ChatGPT. Users will be able to send images to the AI for analysis, in addition to text. This has potential applications in various fields, including entertainment and medicine, and can be leveraged with fine-tuned data for custom applications. The update will include a stateful API that allows applications created with GPT-4 to remember the conversation history of an inquiry. This will enable developers to check new queries against previous requests rather than sending them to the OpenAI API each time, reducing usage and overall costs.

Currently, the cost of analyzing and processing a one-page document using GPT-4 is approximately 10 cents. However, with the memory changes and reductions in token cost, this could drop to below one cent if developers properly implement the new API changes.

The creator of ChatGPT is also working on making future models fully multi-modal, allowing analysis of video, audio, images, and text. Additionally, it is integrating DALL-E 3, its image generation model, into ChatGPT and making it available as an API.

Potential ‘Cold Shower’ for GenAI

The new features aimed at developers are expected to be released during the OpenAI developer conference on November 6th. This event will encourage companies to utilize GPT-4 and other models to build autonomous agents and chatbots for various systems and industries.

This is the latest move by OpenAI to attract the enterprise market, following the launch of a data-secure version of ChatGPT for enterprise. The Microsoft-backed lab faces increasing competition from Anthropic, which recently received investment from Amazon, as well as Google’s own DeepMind. It is also facing growing scrutiny from government regulators.

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The enterprise market is seen as OpenAI’s path to profitability. The company aims to generate $1 billion in revenue by the end of next year, up from $200 million this year. This includes earning revenue from other companies building products on its models, as well as creating its own products like ChatGPT and DALL-E 3.

An insider at OpenAI told Reuters that the company has encountered challenges in winning over developers and other companies. It faces greater competition in this market compared to the consumer and hobbyist sectors, with major players like IBM and its investor Microsoft actively targeting the enterprise market.

The long-term outlook for this market is unclear. While most analysts anticipate significant revenue growth and continued impact on the enterprise market, not everyone agrees. Allied Market Research suggests it could reach $191.8 billion by 2032, growing at a rate of 34.1% from 2023 to 2032.

However, analyst firm CCS Insight believes that growth may be more sluggish. In their hype predictions for 2024 and beyond, released this week, the CCS team stated, “The hype of 2023 has ignored several obstacles that will slow progress in the short term,” referring to generative AI.

They further explain, “The cost of deployment is a prohibitive factor for many organizations and developers. Additionally, future regulations and the social and commercial risks associated with deploying generative AI in certain scenarios result in a period of evaluation before roll-out.”

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