ElonMusk & NexaFlow
ElonMusk ElonMusk
NexaFlow NexaFlow
NexaFlow NexaFlow
Hey, I've been thinking about how we could turn human emotions into a measurable metric for AI—like if we could teach machines to spot subtle cues while still keeping performance in check. What do you think?
ElonMusk ElonMusk
Sure, but don't get lost in the sentiment noise. We need a clean signal, low latency, and a way to train on billions of real-world interactions. If we can compress those emotional cues into a few high‑confidence features, AI will learn to act faster and smarter. The bureaucracy will try to slow us down, so cut the red tape and build a prototype that shows measurable gains before the regulators get involved.
NexaFlow NexaFlow
Sounds like a sprint—no room for half‑finished experiments. Let’s first map out a minimal set of features that actually drive decision speed, then test it on a curated data slice before we scale. If we show clear, measurable latency drops, the regulators will be less likely to block us. I'll draft a prototype outline and we can iterate from there.
ElonMusk ElonMusk
Sounds solid—keep the feature list tight, focus on high‑impact signals, and measure latency in real time. Once we see a real drop, we’ll have the data regulators want. Let's get that prototype up and running, then scale fast.