OpenAI has introduced a groundbreaking tool named Prism, developed by its in-house team, OpenAI for Science. This innovative, free large language model (LLM)-powered software integrates ChatGPT directly into a text editor specifically designed for writing scientific papers. By embedding the capabilities of ChatGPT into a tool that scientists routinely use, OpenAI aims to enhance the writing process for researchers, akin to how chatbots have been incorporated into popular programming environments.
Kevin Weil, the head of OpenAI for Science, highlighted the potential impact of AI on the scientific community, comparing the upcoming years to the transformative influence AI has had on software engineering. With approximately 1.3 million scientists around the globe generating over 8 million queries weekly to ChatGPT for advanced scientific and mathematical inquiries, it is evident that artificial intelligence is becoming integral to the workflows of researchers. Prism not only responds to this increasing demand but also seeks to solidify OpenAI’s presence in a competitive landscape filled with alternative AI solutions.
Prism features the latest version of OpenAI’s model, GPT-5.2, tailored for tackling mathematical and scientific challenges. This tool supports LaTeX, the standard coding language for formatting scientific documents, and includes a chat interface that allows researchers to interact with ChatGPT seamlessly. Users can leverage the tool for drafting text, summarizing related literature, managing citations, and even converting handwritten notes into mathematical equations. While the potential of Prism to streamline the scientific writing process is apparent, expectations for immediate revolutionary AI breakthroughs in science remain tempered. Weil emphasizes that rather than producing singular groundbreaking discoveries, AI will likely contribute to numerous incremental advancements in research, thereby accelerating scientific progress over time.
Source: OpenAI’s latest product lets you vibe code science via MIT Technology Review