DeepSpeed ZeRO++ vs GPT-4

Microsoft Research has announced the development of DeepSpeed ZeRO++, a groundbreaking enhancement to the ZeRO (Zero Redundancy Optimizer) model. This advanced system introduces optimized communication strategies that drastically improve the efficiency of training large language models (LLMs) and chat models. DeepSpeed ZeRO++ achieves this by significantly reducing the amount of necessary communication, even with large batch sizes or limited cross-device bandwidth. By cutting down communication requirements by up to 4 times, researchers and developers can now train complex models more rapidly and cost-effectively.

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.