Seed by ByteDance is a state-of-the-art generalized agentic AI model (Seed1.8) built for real-world tasks, capable of efficiently handling complex workflows across text, image, and video inputs. It excels in multimodal reasoning, GUI interaction, information retrieval, coding, and can proactively interact with real-time video, making it suitable for advanced automation, information extraction, and diverse enterprise applications.
ByteDance has created an AI data and security unit as it expands its in-house data ops for foundation model training.
ByteDance Rules Out AI Distillation ByteDance founder Zhang Yiming has told staff to stop improving the company’s AI
In recent years, research using artificial intelligence to predict material properties has advanced rapidly. Neural network quantum Monte Carlo methods have attracted attention as highly accurate simulation techniques. However, their extremely high computational cost has limited their application to small molecular systems. This study introduces a new computational method that overcomes this limitation.
The video model stands alongside Anthropic’s Claude as a compelling case for AI monetization.
SeedAudio 1.0 isn't just another voice generator — it's a unified tool for sound design that blurs the line between creation and post-production.
ByteDance has set four AI priorities for 2026: investing in world models, keeping the video model `Seedance` at top-tier performance, strengthening its coding foundation and agent capabilities, and accelerating commercialization of `Doubao` with an office-productivity focus, according to a 36Kr exclusive. Per 36Kr, Doubao's daily active users reached 200 million shortly after the 2026 Lunar New Year. The report says Seed leadership, under Wu Yonghui, set a target to release at least one world model by the end of 2026 and benchmark it against Google's `Genie 3`. 36Kr also describes a 2025 reorganization that folded ByteDance's AI Lab (led by Li Hang) and robotics team into Seed and created a small group exploring vision-language-action (VLA) approaches, while noting that progress on world models has been slower than expected.
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