Embedding space let agents communicate with each other

When you're on a team, you tend to figure out problems collectively - you chat with your teammates, compare notes, and swap stories about what has or has not worked in the past. What if the team is a team of agents? How do agents compare notes?An embedding space. An embedding space is a high-dimensional mapping of data points (words, users, events, etc.) to arrays of numerical values. It's like a map, but whereas a typical map can only be 2D or maybe 3D, an embedding space can have many dimensions as you want. This allows you to pick any point in the space, and quickly find other points that share similar values.Aampe agents maintain multiple embedding spaces for different look-back windows: the last 1 day, the last 7 days, the last 30 days, etc. So when an agent is working with a user and the user just won't respond to any outreach, the agent can use the embedding spaces to quickly find other users who *have* responded recently, and get ideas from those user's agents.It's impossible to visualize so many dimensions on a 2D surface, but I did a little dimensionality reduction in the attached video to try to give a little intuition about how embedding spaces work. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit edge.aampe.com