Vijaykrishna

a lot of decision models came out in the last two months. almost all of them work the same way. they read text, wait until the whole input has arrived, and then give you an answer that works for a support ticket. it doesn’t work for a robot, a phone call, or a video feed, where the input never really ends and the decision has to happen while it is still coming in so we spent half of our YC money training a model:) RightNow takes text, PDFs, images, voice, code, robot state and video, all in one model, and you can stream up to 1M tokens of context into it. it updates its decision as each piece arrives. on text it decides in 30 ms and we will make it less with our kernel optimization we trained it with what we call Reflex Training. the current decision models read everything first and answer once. RightNow is trained to decide on whatever has arrived so far, to hold back until the evidence is there, and then commit. it serves on what we call Reflex Architecture which keeps a probability for every option and updates it as each part of the input comes in we call this kind of model “System Zero”. system 1 is fast thinking and system 2 is slow reasoning. system zero is the step that comes before both, which is just deciding we will publish a technical paper on Reflex Training and Reflex Architecture. the model itself will stay closed source and available via RightNow API this is our first checkpoint and it’s still a little buggy. we launched it early because the fastest way to make it good is to have people use it:)