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    OpenAI Leaders Backed Full-Duplex GPT-Live Models

    OpenAI researcher shares experience of sustained support for voice models despite initial skepticism.

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    2 Sources, 38d ago, first seen 38d ago

    TLDR

    OpenAI researcher Kundan Kumar posted that leadership backed full-duplex GPT-Live models for his 14 months at the company even when success looked deeply improbable. He called the approach typical for research projects there and noted few environments would sustain such bets. Greg Brockman quoted the post and said OpenAI has built the muscle of making long-term research bets. Replies on X praised the sustained conviction and rare willingness to back uncertain high-reward work.

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    2 Sources, first seen 38d ago

    Combined views

    673.3K

    2 Sources, first seen 38d ago

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    149 comments
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    113 reposts

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    149 comments
    559 saves
    113 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

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    2 Sources

    @kundan2510In my ~14 months at @OpenAI, one of the most surprising and genuinely wonderful things about it, has been the full leadership support for full-duplex models (gpt-live series), even when it seemed deeply improbable that they would work. And yet, if they did work, it was obvious how magical they could be. I am quite sure this is not an exception but a general rule for research projects at @OpenAI. There were so many moments when the problem felt impossibly hard. But one thing kept being true: it was never clear why it shouldn’t work. And almost every time we understood the problem a little better, it became a little easier to solve. I’m pretty sure there are very few environments in the world where a bet like this could have been made and sustained. So grateful to be part of this wonderful place.
    @gdbOpenAI has built the muscle of making long-term research bets:

    2 Sources

    @kundan2510In my ~14 months at @OpenAI, one of the most surprising and genuinely wonderful things about it, has been the full leadership support for full-duplex models (gpt-live series), even when it seemed deeply improbable that they would work. And yet, if they did work, it was obvious how magical they could be. I am quite sure this is not an exception but a general rule for research projects at @OpenAI. There were so many moments when the problem felt impossibly hard. But one thing kept being true: it was never clear why it shouldn’t work. And almost every time we understood the problem a little better, it became a little easier to solve. I’m pretty sure there are very few environments in the world where a bet like this could have been made and sustained. So grateful to be part of this wonderful place.
    @gdbOpenAI has built the muscle of making long-term research bets: