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    Discovered Materials Launches AI Scientists for Semiconductor Chips

    Co-founder announces launch of AI tools to discover semiconductor materials and releases initial dataset with benchmark.

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    5 Sources, ,

    TLDR

    Advaith Sridhar, co-founder of Discovered Materials, introduced the company on X. It develops AI scientists that discover new materials for semiconductor chips. The initial release includes hundreds of materials found using frontier AI models and Material Discovery Bench, a benchmark for tracking progress in the field. Y Combinator retweeted the announcement. Garry Tan noted the focus on hard tech, and Paul Graham commented on the company name.

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    5 Sources, first seen 51d ago

    Combined views

    639.3K

    5 Sources, first seen 51d ago

    2.8K likes
    51d ago
    first seen 51d ago
    2.8K likes
    169 comments
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    213 reposts

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    Featured Source
    169 comments
    680 saves
    213 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

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    5 Sources

    @advaith_sridharToday, we're introducing @discoveredmat . We build AI scientists that discover new materials for semiconductor chips. We’re starting by releasing our work - hundreds of new materials discovered using frontier AI models, along with our benchmark for tracking progress in this domain, Material Discovery Bench. To pursue our mission, we have raised $9 million from @LightspeedIndia (lead investor) , @ycombinator , @peakxvpartners , @paulg , @gokulr , @trq212 and many others. 🧵
    @ycombinatorRT @advaith_sridhar: Today, we're introducing @discoveredmat . We build AI scientists that discover new materials for semiconductor chips.…
    @gokulrAI's progress is bottlenecked by heat. Semiconductor chips are limited by it, and better materials would change chip performance dramatically. One example: new thermally conductive dielectric materials would make chips 10x more energy efficient by enabling 3D packaging of logic and memory. The substrates, the interconnects, the transistor itself: each needs new materials to keep pushing performance. That's why I invested in @discoveredmat, launching today. @advaith_sridhar, @Akash__Ramdas and the team build AI scientists that discover new materials for semiconductor chips. They're starting by releasing their work: hundreds of new materials discovered using frontier AI models. They also released Material Discovery Bench, a benchmark for tracking progress in this domain. The design is powerful. Models get an open-ended problem: find new dielectrics for chips. They get the toolkit a competent PhD student would have: atomistic simulation software, a coding environment, property prediction models, and web search. Each run is long-horizon (100M tokens!), with unlimited submissions along the way. Most agent benchmarks test tasks that resolve in minutes. Material Discovery Bench treats the model like a researcher: long stretches of work, dead ends included, and judged on what it actually finds. This is where I think the most interesting AI companies are heading: pointing frontier models at open-ended problems where nobody has the answer key, and where the output gets judged by physics. Material discovery is exactly that shape. Excited for Advaith, Akash and the Discovered Materials team to revolutionize how semiconductor chips are built!
    @paulgI love the name Discovered Materials. IIRC the domain name was untaken, so they didn't have to pay anything for it.
    @garrytanYC is the YC for hard tech

    5 Sources

    @advaith_sridharToday, we're introducing @discoveredmat . We build AI scientists that discover new materials for semiconductor chips. We’re starting by releasing our work - hundreds of new materials discovered using frontier AI models, along with our benchmark for tracking progress in this domain, Material Discovery Bench. To pursue our mission, we have raised $9 million from @LightspeedIndia (lead investor) , @ycombinator , @peakxvpartners , @paulg , @gokulr , @trq212 and many others. 🧵
    @ycombinatorRT @advaith_sridhar: Today, we're introducing @discoveredmat . We build AI scientists that discover new materials for semiconductor chips.…
    @gokulrAI's progress is bottlenecked by heat. Semiconductor chips are limited by it, and better materials would change chip performance dramatically. One example: new thermally conductive dielectric materials would make chips 10x more energy efficient by enabling 3D packaging of logic and memory. The substrates, the interconnects, the transistor itself: each needs new materials to keep pushing performance. That's why I invested in @discoveredmat, launching today. @advaith_sridhar, @Akash__Ramdas and the team build AI scientists that discover new materials for semiconductor chips. They're starting by releasing their work: hundreds of new materials discovered using frontier AI models. They also released Material Discovery Bench, a benchmark for tracking progress in this domain. The design is powerful. Models get an open-ended problem: find new dielectrics for chips. They get the toolkit a competent PhD student would have: atomistic simulation software, a coding environment, property prediction models, and web search. Each run is long-horizon (100M tokens!), with unlimited submissions along the way. Most agent benchmarks test tasks that resolve in minutes. Material Discovery Bench treats the model like a researcher: long stretches of work, dead ends included, and judged on what it actually finds. This is where I think the most interesting AI companies are heading: pointing frontier models at open-ended problems where nobody has the answer key, and where the output gets judged by physics. Material discovery is exactly that shape. Excited for Advaith, Akash and the Discovered Materials team to revolutionize how semiconductor chips are built!
    @paulgI love the name Discovered Materials. IIRC the domain name was untaken, so they didn't have to pay anything for it.
    @garrytanYC is the YC for hard tech