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    Sara Hooker Highlights New Adaption AI Dataset

    AI researcher praises dataset that converts intent into training-ready data for models.

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    8 Sources, 27d ago, first seen 27d ago

    TLDR

    Sara Hooker, co-founder of Adaption, pointed out that data remains one of the largest gaps in AI progress. She described a dataset invented by the Adaption AI team that translates user intent into AI-ready training data. Hooker called the development an important step toward bridging that gap and offered a shoutout to her team in the announcement. The comments appear in a post linked to the company's account.

    Combined views

    119.7K

    8 Sources, first seen 27d ago

    Combined views

    119.7K

    8 Sources, first seen 27d ago

    1.1K likes
    1.1K likes
    41 comments
    883 saves
    221 reposts
    41 comments
    883 saves
    221 reposts

    Sentiment

    Positive88.9%11.1%Negative

    Summary

    Many accounts welcomed Invent a Dataset by @adaption_ai for turning prompts into custom, localized training data, while a few objected that synthetic outputs lack real-world correlation and multilingual support.

    Based on 30 sentiment-bearing replies from 27 accounts across 2 conversations.

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    Sentiment

    Positive88.9%11.1%Negative

    Summary

    Many accounts welcomed Invent a Dataset by @adaption_ai for turning prompts into custom, localized training data, while a few objected that synthetic outputs lack real-world correlation and multilingual support.

    Based on 30 sentiment-bearing replies from 27 accounts across 2 conversations.

    8 Sources

    @adaption_aiIntroducing Invent a Dataset. Describe the dataset you need. Get a structured, training-ready dataset back. No existing data needed. Dataset creation used to start with collection. Now it starts with specification.
    @AlexisGimmy@adaption_ai “Most of the world doesn't have data.” 🎯 Off-the-shelf data misses African realities (fintech, agritech, climate). Turning prompt intent into training-ready instruction sets & preference pairs directly in @adaption_ai unlocks huge potential for localized AI. 👏
    @sarahookrOne of the biggest gaps in ai progress is data. Invent a dataset allows you to translate intent into ai ready data for training. A very important step in bridging the gap. 🔥 Big shoutout to the @adaption_ai team.
    @ScobleizerRT @adaption_ai: Introducing Invent a Dataset. Describe the dataset you need. Get a structured, training-ready dataset back. No existing d…
    @hugo_larochelleRT @sarahookr: One of the biggest gaps in ai progress is data. Invent a dataset allows you to translate intent into ai ready data for trai…

    8 Sources

    @adaption_aiIntroducing Invent a Dataset. Describe the dataset you need. Get a structured, training-ready dataset back. No existing data needed. Dataset creation used to start with collection. Now it starts with specification.
    @AlexisGimmy@adaption_ai “Most of the world doesn't have data.” 🎯 Off-the-shelf data misses African realities (fintech, agritech, climate). Turning prompt intent into training-ready instruction sets & preference pairs directly in @adaption_ai unlocks huge potential for localized AI. 👏
    @sarahookrOne of the biggest gaps in ai progress is data. Invent a dataset allows you to translate intent into ai ready data for training. A very important step in bridging the gap. 🔥 Big shoutout to the @adaption_ai team.
    @ScobleizerRT @adaption_ai: Introducing Invent a Dataset. Describe the dataset you need. Get a structured, training-ready dataset back. No existing d…
    @hugo_larochelleRT @sarahookr: One of the biggest gaps in ai progress is data. Invent a dataset allows you to translate intent into ai ready data for trai…