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Re: OpenAI News & Discussions

Posted: Thu Apr 07, 2022 3:47 am
by R8Z
Yuli Ban wrote: Thu Apr 07, 2022 3:21 am
Yuli Ban wrote: Wed Apr 06, 2022 5:06 pm
What gets me is not even the period-correct computers but that it even has that 80s photo grain. It understands filters better than actual image filters. Crazy.
We're getting there. This is only the beggining.


Re: OpenAI News & Discussions

Posted: Mon May 02, 2022 12:02 am
by Yuli Ban

Re: OpenAI News & Discussions

Posted: Mon May 02, 2022 7:04 pm
by peekpok
Sam Altman is one of the few tech bros that I actually like (for now at least). It's nice to see an influential person expression optimism for once, who isn't also mired in controversy.

Re: OpenAI News & Discussions

Posted: Sat May 07, 2022 3:58 am
by Yuli Ban

Re: OpenAI News & Discussions

Posted: Thu Jun 23, 2022 6:40 pm
by Yuli Ban

Re: OpenAI News & Discussions

Posted: Fri Jun 24, 2022 6:23 am
by Yuli Ban

Re: OpenAI News & Discussions

Posted: Fri Jun 24, 2022 6:33 am
by Yuli Ban
Learning to Play Minecraft with Video PreTraining (VPT)
We trained a neural network to play Minecraft by Video PreTraining (VPT) on a massive unlabeled video dataset of human Minecraft play, while using only a small amount of labeled contractor data. With fine-tuning, our model can learn to craft diamond tools, a task that usually takes proficient humans over 20 minutes (24,000 actions). Our model uses the native human interface of keypresses and mouse movements, making it quite general, and represents a step towards general computer-using agents.

Re: OpenAI News & Discussions

Posted: Mon Jul 25, 2022 11:59 pm
by Yuli Ban

Re: OpenAI News & Discussions

Posted: Tue Jul 26, 2022 8:27 pm
by wjfox

Re: OpenAI News & Discussions

Posted: Wed Sep 21, 2022 6:46 pm
by Yuli Ban
Whisper: Human-level speech-recognition model
Whisper is an automatic speech recognition (ASR) system trained on 680,000 hours of multilingual and multitask supervised data collected from the web. We show that the use of such a large and diverse dataset leads to improved robustness to accents, background noise and technical language. Moreover, it enables transcription in multiple languages, as well as translation from those languages into English. We are open-sourcing models and inference code to serve as a foundation for building useful applications and for further research on robust speech processing.
Unbelievable!