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Yangyi
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Yangyi
@yangyi
人机协同架构师 Reverb Marketing布道者 新时代人机协同基站 - 牛马AI👉🏻https://t.co/QJVShfywLx Yangyi实战手记👉🏻https://t.co/Pkue4jV8hK
Katılım Nisan 2015
577 Takip Edilen123.2K Takipçiler
Our April GTM survey found that CRM usage has risen since AI tools began to be adopted at scale.
The agents that listen to calls and write structured notes back into the system are, for the moment, giving reps fresh reason to consult it, because the data sitting there has become dramatically richer than it used to be.
a16z's Gio Ahern, Steph Zhang, and Alex Immerman on the shift from "systems of record" to "systems of intelligence": a16z.news/p/from-system-…
Steph Zhang@steph_zhang
English
@XiaojieJin 如果AI对未来的世界有了更多的信息输入和预测，那么一定程度上应该会加剧AI的情绪生成。
我认为情绪的来源可能是期望。
不过世界模型的数据集是怎么采集和处理呢
中文
Excited to share our new survey paper: the first comprehensive survey on Vision World Model (VWM), a joint effort by researchers from BJTU, ByteDance, Tencent, NUS, and more.
🌟 From Seeing to Knowing the World: A Survey of Vision World Models
🚀 Our core message is a paradigm shift toward vision-centric world modeling:
Vision should not be treated merely as an input modality. It should be the primary driver of how world models are represented, learned, and evaluated.
🌈 This is also the longstanding view behind our #VideoWorld series: learning directly from visual observation and interaction offers a scalable path for AI agents to acquire world knowledge, laying the foundation for higher machine intelligence.
🤔 Why Vision World Models?
From biological evolution to human intelligence, vision has been central to learning about the world through observation and interaction. AI should have this capability too. This motivates Vision World Models: models that learn world knowledge from visual data and simulate future world states conditioned on interaction.
🤖 In this survey, we thoroughly review 400+ recent papers and provide a vision-centric roadmap for Vision World Models, covering architectures, functional roles, applications, evaluation protocols, datasets, benchmarks, and future outlook.
Key takeaways:
1️⃣ Vision is a fundamental basis of intelligence and a rich source of world knowledge. We advocate vision-centric world modeling, where AI learns the physical and causal principles behind world evolution from visual data.
2️⃣ We propose a unified framework that decomposes Vision World Models into three core components: Vision Encoding → Knowledge Learning → Controllable Simulation and organize current methods into 4 major families and 7 representative architectures.
3️⃣ We review evaluation from three levels: Visual Quality, Physical Plausibility, and Task Performance, and group datasets/benchmarks into foundational world modeling and domain-specific world modeling.
4️⃣ We outline three directions for next-generation world models: Re-grounding in physical and causal knowledge, Re-evaluating beyond visual appearance, and Re-scaling toward generalist, reliable, and interaction-aware world models.
Check out our paper and the continuously updated curated list of Vision World Model papers for more details!
📄 Paper: aiworldlab.github.io/survey/preprin…
🌐 Project Page: aiworldlab.github.io/survey/
📚 Curated VWM Paper List: github.com/AIWorldLab/Awe
#VisionWorldModel #WorldModel #Survey #VideoWorld #EmbodiedAI #Robotics #AI #CV
English
At one point my son and his friend kept looking for shortcuts to getting rich. Over and over I told them the way to do it is just to make something people want. If this is what I tell my own kids about getting rich, why won't politicians believe this is how a lot of people do it?
English
稀缺性，往往会带来理性。创业者手上的钱很少，往往会更理性花钱，从而更容易避免掉进一些深坑。比如快速扩张团队、早期就花大钱投放等。
很多坑甚至会带有成瘾性，一旦吸上，就很难戒断。因为数据会迅速下跌，创始人和投资人会很快焦虑。同时一看手上还有不少钱，就会继续吸，而不是想办法停下来，还往往会选择不断寻求新融资来填坑。
手上钱太少也不行。钱太少也很容易焦虑，会导致被贫穷思维支配，束手束脚，越做越小。
合适的稀缺性，能帮助创业者达到最好的状态。问题来了：一个创业者，究竟准备多少钱去创业是最合适的。拿融资，并不是越多越好，那拿多少是最合适的。
能促进理性的稀缺性，最难得。
中文
挖这个也太好了！
之前用pretext做了一些牛马AI的文本渲染折行自适应的问题
看到这个和图片配合调整的 感觉更流畅了
ego@ego_agent
Dear developers (and anyone who's interested in the future interface of web): our boy @imCGQAQ just got shape() accepted as a valid value for shape-outside, which means text wraps around any curve you draw, on a left-floated figure, in one line of CSS, for every Chrome user on Earth. Chrome 149 will ship this feature next week. shape-outside has been in the spec since 2014. for eleven years it accepted exactly five values: circle, ellipse, polygon, inset, image. want a Bézier? approximate it with 40 hand-counted vertices and live with the jagged edges. that compromise is over. and yes — overlaps with @_chenglou's pretext. the difference: pretext is a JS text engine in userland, you build any layout on top. ours is one CSS property in the browser itself, applied to you. opposite ends of the stack. 3 demos. each is a real CSS file, no JS layout code. ↓
中文
Yangyi retweetledi
现在 @rive_app 的需求还挺多的，只要你会 rive，随便网上发个作品，就有一堆咨询的。
学员亲身经历，很多咨询，还有很多 hr 找上来，说问要不要跳槽的。
AI 时代，界面不会消失，APP 越来越多，锦上添花的效果越来越重要，这会是一个软件能不能留住用户的关键之一
如果你也想学习 Rive ，欢迎来看看我们的课程，国内首个 Rive 入门到实践零基础中文系列课。rivecn.com/courses
中文