GPT-4 in 10 Keys

First impressions

Midjourney

GPT-4 is here. The long-awaited and most-anticipated AI model from OpenAI was announced and launched as a product yesterday, March 14 (confirming the rumors first reported by Heise). People are already talking a lot about GPT-4, but I’ve yet to see a succinct overview of its ability, significance, uniqueness — and disappointments — in one place.

That’s what this is: everything you need to know about GPT-4 in ten keys. Most of the citations are from the technical report, the research blog post, or the product blog post (there’s a lot of info overlapping so don’t worry about reading them in-depth). Also, I’ll write follow-up articles for TAB if I see fit as new info or stories come out.

1. Multimodality: The first good multimodal large language model
2. Availability: ChatGPT+ and API
3. Pricing and enlarged context window
4. High performance on human exams and language/vision benchmarks
5. Predictive scaling: what will future models be capable of?
6. Improved steerability to control GPT-4 better
7. Limitations and risks (and modest improvements)
8. A super-closed release: bad news for the AI community
9. Microsoft has revealed that Bing Chat was GPT-4 all along
10. A short compilation of what GPT-4 can do

This article is a selection from The Algorithmic Bridge, an educational newsletter whose purpose is to bridge the gap between AI, algorithms, and people. It will help you understand the impact AI has in your life and develop the tools to better navigate the future.

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1. Multimodality: The first good multimodal large language model

The most salient feature that differentiates GPT-4 from its kin is that, in contrast to GPT-3 and ChatGPT, it’s multimodal — it accepts prompts consisting of text, images, or both interlaced “arbitrarily” and emits…