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    Announcement

    Ocular raises $2 million to build an applied AI data research lab

    Ocular says it will combine domain experts with datasets and benchmarks for voice and audiovisual AI.

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    TLDR

    Ocular announced $2 million in pre-seed funding to build an Applied AI Data Research Lab, with backing from Drive Capital, Y Combinator and others. It says its work includes datasets and evaluations for AI that can listen and speak at the same time, as well as models that interpret speech, facial expressions and gestures together.

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    2 Sources

    @SonofMushabatiToday, we’re excited to announce that @OcularHQ has raised $2M in pre-seed funding to build an Applied AI Data Research Lab that brings human expertise to frontier AI. In just the past few months, we’ve delivered datasets and evaluations to some of the biggest frontier AI labs and Fortune 100 enterprises on the planet — and grown demand and revenue very rapidly! This round is backed by @drivecapital, @ycombinator, @alumniventures, Orange Collective, 1745 Ventures, MyAsiaVC, and angel investors. AI is moving from models you type at to models you can talk with—and that can see and hear the world around them. We’re working toward a future where people interact with AI as naturally as they do with one another. Many models excel on existing benchmarks yet struggle with the complexity of real-world conversations: accents, interruptions, overlapping speech, and the visual cues that give words meaning. We’re building the data infrastructure, evaluations, and benchmarks to close that gap and make AI work in the real world. We combine thousands of vetted domain experts with research and data infrastructure to capture the complexity of how people actually interact. Our work spans full-duplex voice, where models listen and speak at the same time, and audiovisual AI, where models interpret speech, facial expressions, and gestures together. We build high-fidelity datasets to train these capabilities, alongside evaluations and benchmarks that reveal where models still fall short. We’re a lean team from Microsoft and Google building toward that future. We're just getting started! Let's go! 🚀 🚀1h
    @ycombinatorRT @SonofMushabati: Today, we’re excited to announce that @OcularHQ has raised $2M in pre-seed funding to build an Applied AI Data Research…1h

    2 Sources

    @SonofMushabatiToday, we’re excited to announce that @OcularHQ has raised $2M in pre-seed funding to build an Applied AI Data Research Lab that brings human expertise to frontier AI. In just the past few months, we’ve delivered datasets and evaluations to some of the biggest frontier AI labs and Fortune 100 enterprises on the planet — and grown demand and revenue very rapidly! This round is backed by @drivecapital, @ycombinator, @alumniventures, Orange Collective, 1745 Ventures, MyAsiaVC, and angel investors. AI is moving from models you type at to models you can talk with—and that can see and hear the world around them. We’re working toward a future where people interact with AI as naturally as they do with one another. Many models excel on existing benchmarks yet struggle with the complexity of real-world conversations: accents, interruptions, overlapping speech, and the visual cues that give words meaning. We’re building the data infrastructure, evaluations, and benchmarks to close that gap and make AI work in the real world. We combine thousands of vetted domain experts with research and data infrastructure to capture the complexity of how people actually interact. Our work spans full-duplex voice, where models listen and speak at the same time, and audiovisual AI, where models interpret speech, facial expressions, and gestures together. We build high-fidelity datasets to train these capabilities, alongside evaluations and benchmarks that reveal where models still fall short. We’re a lean team from Microsoft and Google building toward that future. We're just getting started! Let's go! 🚀 🚀1h
    @ycombinatorRT @SonofMushabati: Today, we’re excited to announce that @OcularHQ has raised $2M in pre-seed funding to build an Applied AI Data Research…1h