When tracing LLM quality, don't expect users to hand you feedback. 👍👎 ratings don't cut it.
Evaluation should be implicitly embedded by design, ie. detecting when outputs diverge from what users actually do. That's how you get real quality feedback.
It's interesting how Visa was created with decentralist ideals so similar to those that gave rise to modern DAOs, and yet today many of us perceive it as extractive and/or oppressive.
Certainly some good insights to learn from there.
It's interesting how Visa was created with decentralist ideals so similar to those that gave rise to modern DAOs, and yet today many of us perceive it as extractive and/or oppressive.
Certainly some good insights to learn from there.
So everyone nowadays uses speech-to-text through installed apps to input text for messaging, coding, tweets, and more. But wouldn’t it make more sense to have this as a native, embedded feature in user interfaces?
Patient: What can I do to be healthier?
Doctor: Eat less and exercise more.
Patient: Er, is there anything else?
Would-be Founder: What should I do if I want to start a startup?
Me: Learn to program.
Would-be Founder: Er, is there anything else?
I can’t overemphasize how good the new realtime speech2speech model is at function calling. It is fast and accurate with native audio input. It exceeded expectations from myself and posttraining researchers.
This one —
gpt-4o-realtime-preview-2025-06-03
Zoom into the Pillars of Creations with a combination of ground based telescopes and Hubble.
These columns of gas and dust that span roughly 4 to 5 light-years are sculpted and eroded by stellar winds from the nearby massive stars.
📽: NASA, ESA/Hubble
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