tags. So:
人工智能领域的资深研究员李飞飞提出了一种新的世界模型框架，旨在让机器更深入地理解物理空间。如果这一方案成功，它将让机器人能够以当前AI在很大程度上缺乏的理解水平来导航和操控周围环境。
Next: Why world models matter
-> 世界模型为何重要
Then paragraph: "Most AI systems today see the world as flat images or abstract data. They don’t really get that a chair is something you sit on, that a wall can’t be walked through, or that a cup will fall if pushed off a table. Li’s framework tries to fix that by building what she calls a world model — an internal representation of the environment that includes geometry, physics, and the relationships between objects."
Translation: "如今大多数AI系统将世界视为平面图像或抽象数据。它们并不真正理解椅子是用来坐的，墙是无法穿过的，或者杯子如果被推下桌子会掉落。李的框架试图通过构建她所谓的“世界模型”来解决这一问题——这是一种包含几何、物理以及物体之间关系的环境内部表征。"
Note: "Li's framework" -> "李的框架" is fine, but to be consistent with previous "李飞飞", we can say "李飞飞的框架". But the original uses "Li’s framework". We'll keep "李飞飞的框架" for clarity. However, the text is already using "李飞飞" in first sentence, so subsequent "Li's" can be "李的" or "她的". I'll use "她的" for natural flow. But careful: "李飞飞的框架" is okay.
Actually, in Chinese, it's common to refer to the person by surname after introduction: "李". So "李的框架" is acceptable. I'll use "李的框架" but ensure it's clear. Alternatively, "她的" to avoid repetition. Let's keep as "李的框架" for consistency with original.
But original says "Li’s framework" so "李的框架" is fine.
Now second paragraph: "That kind of spatial intelligence is crucial for robots that have to work in homes, warehouses, or hospitals. A vacuum cleaner that doesn't understand corners bumps into them. A delivery drone that can’t predict the wind might drop a package. Li’s approach promises to move beyond these limits by letting an AI simulate possible actions before it takes them."
Translation: "这种空间智能对于需要在家庭、仓库或医院中工作的机器人至关重要。不了解角落的吸尘器会撞到墙上。无法预测风向的送货无人机可能会掉落包裹。李的方法承诺通过让AI在执行动作之前模拟可能的行动来超越这些限制。"
Next heading: From simulation to reality
-> 从模拟到现实
Paragraph: "The framework isn't just about better maps. It’s about learning how the world behaves. The model would run through hypothetical scenarios — what happens if the robot pushes a box, or if a person walks in front of it — and update its understanding based on what actually happens. That feedback loop could make robots more adaptive and safer."
Translation: "该框架不仅仅关乎更好的地图。它关乎学习世界如何运转。该模型将运行假设场景——如果机器人推一个箱子，或者一个人走到它面前会发生什么——然后根据实际发生的情况更新其理解。这种反馈循环可以让机器人更具适应性和更安全。"
Next paragraph: "Li has been working on spatial intelligence for years. Her earlier research on image recognition helped train computers to identify objects. This new effort goes a step further: not just seeing, but reasoning about space. The world model acts like a kind of internal physics engine, letting the AI predict outcomes without having to try every action in the real world."
Translation: "李多年来一直在研究空间智能。她早期在图像识别方面的研究帮助训练计算机识别物体。这项新工作更进一步：不仅仅是看，而是推理空间。世界模型就像一种内部物理引擎，让AI无需在现实世界中尝试每一个动作就能预测结果。"
Next heading: Challenges ahead
-> 前方的挑战
Paragraph: "Building a reliable world model is hard. Real environments are messy. Lighting changes, objects move, people behave unpredictably. Li’s framework will need to handle that chaos without breaking down. The computational cost is also steep — running detailed simulations for every decision takes serious processing power."
Translation: "建立一个可靠的世界模型很难。现实环境是混乱的。光线变化，物体移动，人们行为不可预测。李的框架需要在不崩溃的情况下处理这种混乱。计算成本也很高——为每个决策运行详细模拟需要强大的处理能力。"
Next paragraph: "The researcher hasn’t yet published results from a large-scale test. The framework is described in a recent paper, but the real test will be whether it works outside a lab. A robot that can build and use a world model on the fly would represent a big leap over today’s systems, which mostly rely on pre-programmed rules or massive datasets of labeled examples."
Translation: "这位研究人员尚未公布大规模测试的结果。该框架在最近的一篇论文中有所描述，但真正的考验将是它能否在实验室之外工作。一个能够即时构建和使用世界模型的机器人将代表对当前系统的一大飞跃，当前系统大多依赖预编程规则或大量标记示例的数据集。"
Next paragraph: "Other labs are pushing in similar directions. DeepMind, OpenAI, and a handful of university groups have all proposed world-model ideas. Li’s version stands out for its focus on spatial reasoning — the kind of understanding a human uses to walk through a crowded room without bumping into anyone."
Translation: "其他实验室也在朝类似方向努力。DeepMind、OpenAI以及一些大学团队都提出了世界模型的想法。李的版本因其对空间推理的关注而脱颖而出——这种推理是人类在拥挤的房间中行走而不撞到任何人所使用的理解能力。"
Last paragraph: "Whether the framework can scale beyond simulations into messy, dynamic environments is an open question. Li’s team is likely working on that now, but no timeline has been given for a working prototype."
Translation: "该框架能否从模拟扩展到混乱的动态环境中仍然是一个悬而未决的问题。李的团队可能正在努力，但尚未给出工作原型的时间表。"
Now combine all into the article HTML with tags. Ensure no extra spaces. Also note the original had tags. We need to keep the same structure. In the output, the content field should be the entire translated HTML inside tags.
Also translate meta description: "研究员李飞飞提出了一个AI世界模型的新框架，该框架可以让机器人深入理解物理空间，并重塑其与现实环境的互动。"
Now produce JSON. Use double quotes for keys and string values. Inside the content string, escape double quotes that appear in the HTML. In our translations, there are no double quotes except possibly in the simulated scenario text? In the original, there were double quotes around "what happens if the robot pushes a box, or if a person walks in front of it" but
