LLMs - Transformers for Actions can be the way to Autonomy.

Today companies are training bigger and bigger Transformers, with the dream of eventually building one general model to power all ML use cases but there was a clear limitation: models trained on text can write great prose, but they can't take actions in the digital world. You can't ask GPT-3 to book you a flight, cut a check to a vendor, or conduct a scientific experiment.

True general intelligence requires models that can not only read and write, but act in a way that is helpful to users. That's why we're starting Unpod Super Pilot: we're training a neural network to use every software tool and API in the world, building on the vast amount of existing capabilities that people have already created.

In practice, we're building a general system that helps people get things done in front of their computer: a universal collaborator for every knowledge worker. Think of it as an overlay within your computer that works hand-in-hand with you, using the same tools that you do. We all have parts of our job that energize us more than others with Unpod SuperPilot, you'll be able to focus on the work you most enjoy and ask our model to take on other tasks. For example, you could ask our model to generate our monthly compliance report or draw stairs between these two points in this blueprint all using existing software like Airtable, Photoshop, an ATS, Tableau, Twilio to get the job done together. We expect the collaborator to be a good student and highly coachable, becoming more helpful and aligned with every human interaction.

This product vision excites us not only because of how immediately useful it could be to everyone who works in front of a computer, but because we believe this is actually the most practical and safest path to general intelligence. Unlike giant models that generate language or make decisions on their own, ours are much narrower in scope we're an interface to existing software tools, making it easier to mitigate issues with bias. And critical to our company is how our product can be a vehicle to learn people's preferences and integrate human feedback every step of the way.