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一篇论文要上顶刊、顶会，需要经历三个阶段： 1）首先是产出 preprint 初稿，初稿完成后发布到 arXiv 或 openReview 等平台，主动获得快速曝光，以吸引潜在的审稿人注意； 2）紧接着是向对应的期刊或会议投稿，会经历初审、正式审核、问题澄清等过程，顶会的拒稿率在 80% 左右； 3）最后完成修订和补充后才会被正式收录，整个流程通常持续半年甚至一年以上。 顶刊顶会只占论文总量的不到 10%，却贡献了超过 50% 的引用量；剩下的 90% 虽然很多是增量性研究或局部实验，没有里程碑式的突破，但也为后续研究提供了大量数据、方法和对比基线，价值同样不可忽视。 那“论文”到底是什么？从顶会顶刊的分类来看，它本质上是人类知识的一种系统化表达形式。以计算机科学为例，NeurIPS 偏重机器学习和人工智能基础理论，CVPR 聚焦计算机视觉，ICML 和 ICLR 涵盖模型架构、训练方法、优化算法等方向，SIGGRAPH 专注图形学与交互，而 Nature、Science 等综合性期刊则跨越学科边界，关注具有颠覆性意义的研究成果。可以说，论文汇聚了人类在 算法、模型、系统、工具、应用 等不同维度上的思考与探索。 我比较推荐开发者去多关注一些前沿、偏工程性的 Agent 论文，它们里面往往埋藏着大量新颖的思路和独到的启发，这些思路本质上就是为了解决工业界里那些“又难又深”的问题而提出的。

Our WeatherNext 2 AI model from @GoogleDeepMind and @GoogleResearch can predict tropical cyclones with an extra day of lead time. Now, we’re open sourcing the model. Published in @Nature, Google researchers demonstrate how it delivers roughly a decade's worth of weather forecasting progress in a single jump. Here's how it works:

Predicting cyclones accurately can help save lives - and every hour of lead time counts. Published in @Nature, our AI model WeatherNext achieves state-of-the-art accuracy in forecasting a storm’s track and intensity, giving us a critical extra 24 hours to prepare on average. 🧵

Here is my AI investing guide. Sitting here August 2026, my current best thoughts are as follows: 1. LPS (Land Power Shell) is still the most obvious and fastest path to cash on cash returns. Lots of value can be assembled and traded quickly at this layer. And as data centers get more pushback, energized land can explode in value. Very bullish here. I’ve stepped into this layer very aggressively. My partner @anitavlallian and I have acquired almost 6GW coming online in a ramp from today thru 2029 of grid power and behind the meter. 2. Silicon - I helped get @GroqInc off the ground in 2015 and we licensed it to @nvidia for $20B Dec2025. I won’t invest or incubate anything in this layer now. The perf demands of the chips are too high, manufacturing precision is too complex and supply chain influence to get adjacent components like memory isn’t possible for a startup anymore. Lots of capital will be wasted here chasing Groq and Cerebras’ success. Note that both startups made sense a decade ago when these constraints were much more modest. 3. Clouds - Clouds are very very lucrative but very hard to build and very expensive and technically complicated to maintain. And as alignment becomes a more important issue, I expect the clouds will be asked to build robust KYC and attest to it. This makes the risk:reward ratio skewed. I don’t want to be responsible when the USG says a cloud allowed a bad actor to do something bad because of poor KYC. 4. Models are complicated. The big open question is how much of the revenue being generated by them today is because of tokenmaxxing and poor model behavior. If it’s a lot, then the annualized revenues will diminish meaningfully even as token consumption inflects upwards. This is the big economic question at this layer. 5. Harnesses are where the action is and why I started @8090solutions two years ago. In a nutshell, the harness helps enterprises owns their proprietary context (what Alex Karp calls their ‘alpha’). This is an enterprise’s data, workflows, evals, and business rules. A harness that gives this to an enterprise is what creates very low model-agnostic switching costs, which further reinforces my views of #4# above. 6. Applications will be another long term winner along with harnesses. This is where the differentiation between “off the shelf” and “custom time and materials” melts away. Every company, with the right harness, can now imbue their alpha into the software that runs their company. I expect this to mean that “off the shelf” is largely replaced with custom software creating a huge opportunity to write these solutions for companies. Build once and sell repeatedly is a laggard GTM motion for a SaaS world that isn’t needed here. Think custom by design, alpha embedded, proprietary by nature. Fin. Good luck to all the players!

It’s not that Zhangjiajie is out of reach, but Xia‑Tian‑Xia Gorge in Guangdong offers better value‑for‑money. Only a 2‑hour‑drive from Guangzhou, you get to witness nature’s magnificent craftsmanship.

What would a Chinese ink painting look like if it were shaped by nature? Just outside Lanzhou, capital city of northwest China's Gansu Province, layers of red, gold and gray stretch across the mountains, creating a landscape known as the Shuimo (Ink-Wash) Danxia. Come with us as we step into a landscape painted by earth, wind and time. #ShuimoDanxia# #Gansu# #SilkRoad# #TravelChina#

We have multiple reasons for wanting to believe nurture is more important than nature and none for wanting to believe the opposite (unless we = the far right, which we ≠), so it's not surprising we overestimate its effect. But man are kids' personalities inborn.