*Civilization* players react to Seedance 2.0: This time, Wang Xingxing really wasn’t exaggerating

When I judge whether a technology really has substance, I usually start with one question: is it driven by concepts first, or can it already be applied to actual production processes? It’s like playing a strategy board game: no matter how loudly you boast in the opening, if you can’t follow through with resources and execution in the midgame, then it’s a classic waste. Judging from Wang Xingxing’s remarks at the 2026 Yabuli Forum Annual Conference, his praise for ByteDance’s Seedance 2.0 was not just polite applause—it pointed directly to the most critical move in China’s AI game: video generation is shifting from demonstrating capability to delivering practical utility.

According to Sina Tech, the 2026 Yabuli Forum Annual Conference was held in Yabuli, Heilongjiang, from March 17 to 19. Wang Xingxing, founder of Unitree Robotics, said on site that very clear technological progress has already emerged in China’s AI field. The case that impressed him most was Seedance 2.0, launched by ByteDance in January this year. His judgment was very straightforward: he believes this video generation software is currently in a leading position worldwide.

What makes this interesting is that Wang Xingxing did not keep the discussion at the vague level of “a stronger model.” Seedance 2.0 has a very clear positioning: it is an AI video generation model capable of producing cinematic-quality videos from text or images. More importantly, it already maps onto clear application scenarios such as AI animated series, short drama production, e-commerce advertising, and pre-shooting. In terms of strategic depth, this is like in Total War when you don’t just gain one powerful card, but your entire logistics line, unit composition, and battlefield tempo all begin to take shape—that’s what real sophistication looks like.

From a systems design perspective, what truly gives video generation AI value is not how stunning a one-off demo can be, but whether it can compress the time and cost embedded in the production pipeline. AI animated series, short dramas, e-commerce ads, and pre-shooting all share one thing in common: they require high-frequency output, rapid trial and error, and extensive iterative refinement. In the past, this part of the workflow consumed a great deal of manpower. Now, if the model’s stability and controllability are high enough, then it is no longer just “fun to play with”—it begins to rewrite the industry’s workflow.

But the issue is that Wang Xingxing’s judgment was not unreserved optimism all the way through. He also mentioned that embodied intelligence software will see obvious technological progress over the next few years, but that it is still “not quite there yet.” I strongly agree with that assessment. Video generation is more like setting up long-range firepower from the rear, with tangible results already visible; embodied intelligence, by contrast, is like a heavily armored frontline unit, involving a closed loop of perception, decision-making, execution, and real-world feedback. If any one link is unstable, the entire experience falls apart.

Looking at the trend, the significance of products like Seedance 2.0 is not just that Chinese AI companies have come up with another strong card, but that domestic model competition is beginning to move beyond parameters and rankings toward concrete industry penetration. For people working in the content industry, the key thing to watch next is not “whether it will replace everyone,” but who can be the first to treat it as a production tool and use it to reorganize team collaboration and content output. Get this step right, and what follows is a snowball effect; get it wrong, and even the strongest model will end up as nothing more than a display piece in the demo hall.