Simon Willison’s Weblog

Bringing developer choice to Copilot with Anthropic’s Claude 3.5 Sonnet, Google’s Gemini 1.5 Pro, and OpenAI’s o1-preview. The big announcement from GitHub Universe: Copilot is growing support for alternative models.

GitHub Copilot predated the release of ChatGPT by more than year, and was the first widely used LLM-powered tool. This announcement includes a brief history lesson:

The first public version of Copilot was launched using Codex, an early version of OpenAI GPT-3, specifically fine-tuned for coding tasks. Copilot Chat was launched in 2023 with GPT-3.5 and later GPT-4. Since then, we have updated the base model versions multiple times, using a range from GPT 3.5-turbo to GPT 4o and 4o-mini models for different latency and quality requirements.

It's increasingly clear that any strategy that ties you to models from exclusively one provider is short-sighted. The best available model for a task can change every few months, and for something like AI code assistance model quality matters a lot. Getting stuck with a model that's no longer best in class could be a serious competitive disadvantage.

The other big announcement from the keynote was GitHub Spark, described like this:

Sparks are fully functional micro apps that can integrate AI features and external data sources without requiring any management of cloud resources.

I got to play with this at the event. It's effectively a cross between Claude Artifacts and GitHub Gists, with some very neat UI details. The features that really differentiate it from Artifacts is that Spark apps gain access to a server-side key/value store which they can use to persist JSON - and they can also access an API against which they can execute their own prompts.

The prompt integration is particularly neat because prompts used by the Spark apps are extracted into a separate UI so users can view and modify them without having to dig into the (editable) React JavaScript code.