AI新人想快速成长？这份硬核路线图从数学到集群全覆盖，建议逐条对照执行，做AI开发的值得收藏。
Marc Andreessen转发了一条关于AI领域新人如何避免落后的建议。建议包括深入学习模型内部原理、线性代数、非凸优化、训练小模型和大模型、掌握vLLM和Tensor并行、手写内核、集群编排、合成数据、SFT和PPO、学习Triton、了解半导体供应链、构建大型集群、预训练800B模型并后训练、服务数百万用户、在基准测试上超越DeepSeek。这些建议强调从理论到实践的全面技能，是AI领域职业安全的关键。
The thing is, it’s actually really good advice.
The thing is, it’s actually really good advice. Jimmy Heaters @CathPoaster new grads often ask me what they should be doing so they don't fall behind in the ai space. there's a lot, but its honestly super manageable. become intimate with model internals. proof based linear algebra. non-convex optimization. this is stuff you could've done in undergrad. it definitely takes some time and work, but its doable. have taste, have opinions. train a small model, then train a big one. vLLM internals, tensor parallelism. hand roll kernels. cluster orchestration. do you have opinions on synthetic data? why don't you? SFT, PPO, you should know this. learn Triton. everyone is reproducing papers now so you need to be doing more. do you know the semi supply chain? where are the bottlenecks? hardware, man, hardware. your little gpu rig erector set in your basement isnt gonna cut it. build a cluster, a big one. pretrain a 800B model. now postrain it. serve it to millions of people. you should be able to beat deepseek on some benchmarks now. its a lot to take in but it all snowballs. this what job security looks like from now on. do you want to work in tech or not 🔗 View Quoted Tweet 💬 14 🔄 5 ❤️ 97 👀 27281 📊 22 ⚡