The big deal is speed (high) and cost (low). This week I’m messing around augmenting mouse and keyboard interactions in an application with Deepgram + System 1 (Jev).

You can talk to an application and have it respond in real time with this combo. It’s clear this kind of general purpose intelligence may be a new development primitive.

However, at this stage, it’s difficult to work with for a few reasons. It’s API only, and you have to shape calling software to the way it communicates.

It’s not clear yet if what we’re missing is a new programming language, or some kind of harness or tool over the capabilities. LLMs were like this early on as well until better harnesses came along and reduced friction in their use.

Down the road, I highly suspect we’ll see:

  - Intelligent context assembly using System 1 that summons memories as needed in LLM conversations and handles simple commands.

  - System 1 programs that run in the datacenter and reach out to the request initiator on specific instructions like a CPU that has hit a memory barrier.