Prof_YZ @APGASU , RTesearching AI/CV/GenAI @SCAI_ASU ; Amazon Scholar @PrimeVideo ; PhD @umdcs; BA @ZJU_China 奇共赏 疑与析 修栈道 渡陈仓 🤠

Phoenix, AZ
Joined February 2018
May 2026 @ApgAsu ers at #taroko sports.
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'YZ' Yezhou Yang (杨叶舟) retweeted
Scientific terms should have precision. If we use the terms VLM, VLA, WAM in an indiscriminate fashion, as is becoming common in robotics, we are not helping clarity in communication. Let's keep the historical origins of these terms in mind. VLMs arose as multimodal extensions of LLMs-the training was for tasks like VQA (VIsual Question Answering). These capture the static semantics of the scene behind an image. No dynamics. World Models (e.g. @ylecun , Ha & Schmidhuber 2018) on the other hand are primarily dynamics models, which go back to control theory -1960 (Bellman, Kalman etc.) This makes them natural for robotics planning / policies- I am in a state s, what action a should I perform to get to state s'. In classical control, these models were written down a priori by modeling the physics of the system; today we think of them as learned neural networks trained from temporal data e.g. video, robot trajectories. But the concept is the same. We shouldn't mix this concept with VLMs.
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So, we understand then generate, and/or, generate then understand?
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Quality or quantity? 🤔
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As one can probably tell, I am not a big fan of alphabetical ordering... -- YZ 🤠
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Active Perception Group @ApgAsu fellows (left) and almost all ASU sun devils (right) at #CVPR 2026. @SCAI_ASU #AI #CV #Denver
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From the America's friendliest airport (Phoenix sky harbor) to Denver for #CVPR 🤠
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Data Structures & Algorithms has traditionally been a gatekeeper course in Computer Science, I am seriously considering the following paper-only in-class rules as the original generations of programmers did 👇
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• Bring a notebook and a pen/pencil to every class. • During class activities, use paper only unless explicitly asked to use laptops, phones, tablets, or AI tools. • At the end of the course, the notebook would be used as a reference for final grades.
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The course is fundamentally about developing algorithmic thinking. Class time should be dedicated to building that reasoning process. Curious to hear perspectives from fellow educators, technologists, and tech hiring managers: what role should #AI play in foundational CS courses?
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So called intelligence, it is not intelligence, but named as intelligence. 🙏
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An extremely talented mechanical engineer and a painting artist. The world is cruel ~~~
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AI-generated images are getting harder to spot and scams are rising. In #SCAI, researcher @prof_yz is helping set global standards to detect synthetic media and even teach AI to forget harmful content, building a more trustworthy digital future. news.engineering.asu.edu/202…
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The world model is still a model, not a world.
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'YZ' Yezhou Yang (杨叶舟) retweeted
Anyone who claims to be interested in Intelligence should know optimal control theory developed in 1960s, or even cybernetics, as early as in 1940s... My new book was trying to set straight the related history and concepts...
Replying to @ronbrachman
The basic idea of world models is very old. Optimal control folks were using model-based planning in the 1960s (using the "adjoint state" methods, which deep learning people would now call "backprop through time"). But the real question is what you do with this idea and how you reduce it to practice.
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'YZ' Yezhou Yang (杨叶舟) retweeted
I think it’s pretty clear that simulation is the next frontier for AI. The most impressive feats of AI to date are when we have a clear environment + reward, whether it be beating Le Sedol at Go, winning an IMO gold medal, or writing entire apps from scratch. In these cases, the RL algorithm can try different actions, and observe the well-defined consequences in the safety of a docker container. But what about messy real-world situations involving people? The rewards are unclear, the stakes are high, and you can’t experiment in the real world. But these situations are precisely where the next big opportunity in AI is. To crack this, we need to *simulate* society (“put society into a docker container”). Concretely, this means building a model that can predict what will happen in any given situation (real or hypothetical). If we can do this, we are only limited by our imagination: predict the future, optimize for better outcomes, answer hypothetical (“what if”) questions. Ultimately, this goes beyond making better decisions, but it’s about giving us a better understanding of ourselves and the world. Simulation is the whole enchilada. And this is exactly the research that @simile_ai is working on. Read more here: simile.ai/blog/simulation-ne…
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If an inquiry now starts with a customer service line asking, “Are you a real person?”, something has clearly gone awry. 😆 I just did that this morning...
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I think the next single person tech unicorn could just be hatched from a local Fedex store... These places have everything one needs...
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👇 this is kind of author-reviewer exchange should be. Authors gain suggestions and perspectives from others, and give out their own to another group of authors as reviewers. #Walk_For_Peace
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'YZ' Yezhou Yang (杨叶舟) retweeted
OpenReview is a pillar of progress in the AI research community. Now it needs our support. Along with several of my colleagues, I have pledged to help, and I encourage anyone who can to do the same. openreview.net/donate
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