OpenAI is an American artificial intelligence (AI) research laboratory consisting of the non-profit OpenAI Incorporated (OpenAI Inc.) and its for-profit subsidiary corporation OpenAI Limited Partnership (OpenAI LP). OpenAI conducts AI research with the declared intention of promoting and developing a friendly AI. OpenAI systems run on the fifth most powerful supercomputer in the world.[5][6][7] The organization was founded in San Francisco in 2015 by Sam Altman, Reid Hoffman, Jessica Livingston, Elon Musk, Ilya Sutskever, Peter Thiel and others,[8][1][9] who collectively pledged US$1 billion. Musk resigned from the board in 2018 but remained a donor. Microsoft provided OpenAI LP with a $1 billion investment in 2019 and a second multi-year investment in January 2023, reported to be $10 billion.
GPT-3 Engines
The main GPT-3 models are meant to be used with the text completion endpoint. We also offer models that are specifically meant to be used with other endpoints. Our endpoints for creating embeddings and editing text use their own sets of specialized models.
- Davinci – Davinci is the most capable model family and can perform any task the other models can perform and often with less instruction. For applications requiring a lot of understanding of the content, like summarization for a specific audience and creative content generation, Davinci is going to produce the best results. These increased capabilities require more compute resources, so Davinci costs more per API call and is not as fast as the other models. Another area where Davinci shines is in understanding the intent of text. Davinci is quite good at solving many kinds of logic problems and explaining the motives of characters. Davinci has been able to solve some of the most challenging AI problems involving cause and effect.
Good at: Complex intent, cause and effect, summarization for audience
- Curie: Curie is extremely powerful, yet very fast. While Davinci is stronger when it comes to analyzing complicated text, Curie is quite capable for many nuanced tasks like sentiment classification and summarization. Curie is also quite good at answering questions and performing Q&A and as a general service chatbot.
Good at: Language translation, complex classification, text sentiment, summarization
- Babbage: Babbage can perform straightforward tasks like simple classification. It’s also quite capable when it comes to Semantic Search ranking how well documents match up with search queries.
Good at: Moderate classification, semantic search classification
- Ada: Ada is usually the fastest model and can perform tasks like parsing text, address correction and certain kinds of classification tasks that don’t require too much nuance. Ada’s performance can often be improved by providing more context.
Good at: Parsing text, simple classification, address correction, keywords
Note: Any task performed by a faster model like Ada can be performed by a more powerful model like Curie or Davinci.
OpenaAI Fund
TAU Codex Orchestrator
We plan to integrate it into our TAU Codex Orchestrator to enable Actionable Intelligence coupled with immersive video and graphics.
NI+IN UCHIL Founder, CEO & Technical Evangelist
nitin.uchil@numorpho.com