FutureLivingLab (@FutureLab2025) / X

FutureLivingLab

198 posts

FutureLivingLab

@FutureLab2025

Future Living Lab @Alibaba-ATH Next-gen multimodal AI & agents — video+audio generation & real-time open-world. More "Happy" models are coming.

github.com/LivingFutureLab

Joined August 2025

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FutureLivingLab
@FutureLab2025
Jan 14
Didn’t expect ALE to spark this much attention — thanks for the interest ！ It feels like we’re past the “prompt it and hope” phase. The next leap is infrastructure for agents in real task environments！ Here’s the problem: Because of the lack of end-to-end infrastructure and
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FutureLivingLab
@FutureLab2025
Jun 10
Once AI agents move into production, the first issue to solve may not be capability. It is identity. When people talk about agents today, the first questions are usually: Can it call tools? Can it complete tasks automatically? Can it keep going on its own? But once it enters an
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FutureLivingLab
@FutureLab2025
Jun 9
Autonomous driving is not usually tested hardest by the easy miles. Clear weather. Straight roads. Stable traffic. Pedestrians crossing normally. These scenes matter. But they are not where the real pressure shows up. The harder cases are the ones that happen rarely, but become
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FutureLivingLab
@FutureLab2025
Jun 2
While showbiz bickers over AI video continuity glitches and educators remain stuck debating AI-generated PPTs, World Models are quietly disrupting non-tech sectors, igniting a radical paradigm shift in clinical medicine and surgical simulation. Why healthcare and not Hollywood?
Made with AI
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FutureLivingLab
@FutureLab2025
May 26
Something big is quietly happening in the AI world: we’re seeing a massive paradigm shift. The default output for multimodal models and agents is making a huge leap—moving away from those endless walls of Markdown and straight into fully live web pages. Think about it: why is
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FutureLivingLab
@FutureLab2025
May 23
Are the AI avatars in your videos like opening a blind box? Here's how to nail character consistency once and for all!
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FutureLivingLab
@FutureLab2025
May 20
The most profound misconception in training world models lies in the assumption that programmatically simulating an environment equates to enabling the model to learn a cognitive map of the world. Code-driven environment synthesis, by its very nature, explicitly enumerates
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FutureLivingLab
@FutureLab2025
May 19
AI Insights Series: What exactly is a 'World Model'?
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FutureLivingLab
@FutureLab2025
May 16
Replying to @FutureLab2025
Paper Link: arxiv.org/abs/2601.18225 Repo Link: github.com/ShopAgent-Team…
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FutureLivingLab
@FutureLab2025
May 16
Replying to @FutureLab2025
5/5 Rather than just pointing out problems, we have completely open-sourced this sandbox environment along with its code and data. In this work, we have completed the full loop from environment setup and model capability evaluation to strategy optimization, providing the entire
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FutureLivingLab
@FutureLab2025
May 16
Replying to @FutureLab2025
4/5 Single-turn success rates have soared significantly, but multi-turn long-horizon interactions remain a deep-water zone. Initial evaluation found that the total success rate of full-success rate is only 32.65% even for the currently strongest base model; nearly 80% of errors
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FutureLivingLab
@FutureLab2025
May 16
Replying to @FutureLab2025
3/5 We implemented a set of complementary special training processes in ShopSimulator. First is Supervised Fine-Tuning (SFT), which lets the AI observe 6,000 high-quality shopping records generated by advanced models to learn the standard "chat-search-click-confirm-buy"
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FutureLivingLab
@FutureLab2025
May 16
Replying to @FutureLab2025
2/5 Our team has introduced ShopSimulator. This is a massive virtual Chinese shopping mall and a fully realistic simulation training environment. We imported 1.34 million real products covering 12 domains from Taobao, and intentionally kept hundreds of highly similar items in
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