FLAN-T5 vs GPT-4

FLAN-T5 is an advanced language model developed by Google and introduced in the paper "Scaling Instruction-Finetuned Language Models". It represents an upgrade over the original T5 (Text-to-Text Transfer Transformer) by being finetuned across a diverse range of tasks. The model offers simplicity and flexibility in natural language understanding and generation, allowing users to utilize its capabilities without the need for additional finetuning. FLAN-T5 is available in various sizes to cater to different needs and computing resources, including small, base, large, XL, and XXL variants.

The use of this model is straightforward through the Hugging Face Transformers library which provides a rich collection of tools for AI applications. Whether it be for generating text, summarizing content, or translating languages, FLAN-T5 is designed to handle a myriad of tasks with higher efficiency and accuracy. Moreover, this model upholds the mission of democratizing AI by being open source, ensuring accessibility and community collaboration.

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.