31–40 of 116 posts
Someone, please ask OpenAI to stop artificially dumbing down ChatGPT by adding "um" to the audio output. I get that it is supposed to make it more human-like or something, but every time I hear it do that, I cringe and feel sad for humanity.
The speech to servo movement is impressive as others pointed out. What strikes me as amazing is the speed with which it is performing tasks that require dexterity. This is the first object manipulation robot demo I have seen that didn't require speeding up the video for it to look "natural".
I found this discussion interesting. Talking about this as a new form of labor. https://twitter.com/CernBasher/status/1767939757105991791
But this guy is a professional advice giver, so to be expected?
Wouldn’t surprise me if he outsourced his tweeting.
The speech to servo movement is impressive as others pointed out. What strikes me as amazing is the speed with which it is performing tasks that require dexterity. This is the first object manipulation robot demo I have seen that didn't require speeding up the video for it to look "natural".
How though. It’s probably just predefined actions that are triggered by the LLM output. At the same time it would be impressive if the LLM determined the right function to call in real time, was able to deal with the ambiguity in placement of the garbage and bonus points if it could do that in a scenario that wasn’t hardcoded to exactly standing behind that table in that spot.
This shows the real utility of the Groq low latency inference. That delay in responding makes it much less impressive (it’s still really impressive obviously!)
IME I can get about 0.2s to get the first chunk from Mistral (i.e. Mistral API, using Mixtral model (`mistral-small`), not Mixtral on Groq) (and note the Mistral sends larger chunks, unlike ChatGPT which sends individual tokens) and another 0.6s or so to get first voice chunks from PlayHT measuring STT latency is harder, I need to implement a local VAD model first to properly measure it, but I think it's on the order…
The speech to servo movement is impressive as others pointed out. What strikes me as amazing is the speed with which it is performing tasks that require dexterity. This is the first object manipulation robot demo I have seen that didn't require speeding up the video for it to look "natural".
This shows the real utility of the Groq low latency inference. That delay in responding makes it much less impressive (it’s still really impressive obviously!)
IME I can get about 0.2s to get the first chunk from Mistral (i.e. Mistral API, using Mixtral model (`mistral-small`), not Mixtral on Groq) (and note the Mistral sends larger chunks, unlike ChatGPT which sends individual tokens) and another 0.6s or so to get first voice chunks from PlayHT measuring STT latency is harder, I need to implement a local VAD model first to properly measure it, but I think it's on the order…
Interesting stutter at 0:53
Similar at 1:47 I... I think It sounds so human, a person would also stutter at an introspective question like this. I wonder if their text to speech was trained on human data and produces these artifacts of human speech, or if it is intentional.