Galactica vs GPT-4

Galactica is an advanced large language model specifically designed to handle the complexities of scientific knowledge. Its ability to store, combine, and reason about vast amounts of scientific information makes it an invaluable resource to overcome the challenges of information overload in the science community. Developed by a team led by Ross Taylor, Marcin Kardas, and several other contributors, Galactica stands out with its superior performance on a variety of scientific tasks.

By outperforming existing models such as GPT-3 on technical knowledge probes and Chinchilla on mathematical MMLU, Galactica has shown potential to serve as a potent new interface for scientific exploration and discovery. Notably, Galactica has achieved state-of-the-art results on downstream tasks such as PubMedQA and MedMCQA dev, substantiating its value addition to the scientific community. The model is open-sourced, encouraging broad usage and contribution among researchers and institutions globally.

GPT-4 is the latest milestone in OpenAI’s effort in scaling up deep learning.

GPT-4 is a large multimodal model (accepting image and text inputs, emitting text outputs) that, while less capable than humans in many real-world scenarios, exhibits human-level performance on various professional and academic benchmarks. For example, it passes a simulated bar exam with a score around the top 10% of test takers; in contrast, GPT-3.5’s score was around the bottom 10%. We’ve spent 6 months iteratively aligning GPT-4 using lessons from our adversarial testing program as well as ChatGPT, resulting in our best-ever results (though far from perfect) on factuality, steerability, and refusing to go outside of guardrails.

GPT-4 is more creative and collaborative than ever before. It can generate, edit, and iterate with users on creative and technical writing tasks, such as composing songs, writing screenplays, or learning a user’s writing style.