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Min Lin

AMI Labs
@mavenlin
Singapore
linmin.me
Joined April 2015
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  • user avatar
    Min Lin
    AMI Labs
    @mavenlin
    Mar 10
    The most exciting breakthroughs in intelligence are yet to come. I’m super excited to start this journey with mes amis to make them happen together.
    user avatar
    AMI Labs
    @amilabs
    Mar 10
    Advanced Machine Intelligence (AMI) is building a new breed of AI systems that understand the world, have persistent memory, can reason and plan, and are controllable and safe. We’ve raised a $1.03B (~€890M) round from global investors who believe in our vision of universally
    Photographer: Yann LeCun IC1340 / NGC 6992 / Eastern Veil nebula 20210628-ic1340-rasa-2600mc-lext Scope: Celestron RASA 11" Camera: ZWO ASI2600MC Filter: Radian Triad quad narrow band. Subs: 65 @300 seconds.
  • user avatar
    Min Lin
    AMI Labs
    @mavenlin
    Feb 4
    More accurately "online learning". Continual learning can go anywhere by redefining its meaning.
    user avatar
    Min Lin
    AMI Labs
    @mavenlin
    Feb 4
    Continual learning is a "learning" problem, innovating on model architecture but still relying on sgd to do the learning is leading to nowhere.
  • user avatar
    Min Lin
    AMI Labs
    @mavenlin
    Nov 27, 2025
    I was debating with @ducx_du in the past few days on a few points, sharing them to provide some more food for discussion. There can be two interpretations, 1. DLLM is fitting a loose elbo with uniform posterior distribution over the order. 2. It is fitting n! number of models
    user avatar
    Cunxiao Du
    @ducx_du
    Nov 25, 2025
    Diffusion LLMs (DLLM) can do “any-order” generation, in principle, more flexible than left-to-right (L2R) LLM. Our main finding is uncomfortable: ➡️ In real language, this flexibility backfires: DLLMs become worse probabilistic models than the L2R / R2L AR LMs. This