Real time video generation is finally real

Introducing Self-Forcing, a new paradigm for training autoregressive diffusion models. The key to high quality? Simulate the inference process during training by unrolling transformers with KV caching. project website: https://self-forcing.github.io Code/models: https://github.com/guandeh17/Self-Forcing Source: https://x.com/xunhuang1995/status/1932107954574275059?t=Zh6axAeHtYJ8KRPTeK1T7g&s=19 submitted by /u/cjsalva [link] [comments]

Apple Machine Learning Research at CVPR 2025

Apple researchers are advancing AI and ML through fundamental research, and to support the broader research community and help accelerate progress in this field, we share much of our research through publications and engagement at conferences. This week, the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), will take place in Nashville, Tennessee. Apple …

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Automate customer support with Amazon Bedrock, LangGraph, and Mistral models

AI agents are transforming the landscape of customer support by bridging the gap between large language models (LLMs) and real-world applications. These intelligent, autonomous systems are poised to revolutionize customer service across industries, ushering in a new era of human-AI collaboration and problem-solving. By harnessing the power of LLMs and integrating them with specialized tools …

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Lessons from the field: What decision-makers want to know about multi-agentic systems

This year, we’ve spent dozens of hours synthesizing hundreds of conversations with CXOs across leading organizations, trying to uncover their biggest thorns when it comes to building Multi-Agent Systems (MAS).  These conversations have revealed a clear pattern: MAS is helping enterprises re-think clunky legacy processes, but many CXOs are focused on automating those legacy processes …

‘Optical neural engine’ can solve partial differential equations

Partial differential equations (PDEs) are a class of mathematical problems that represent the interplay of multiple variables, and therefore have predictive power when it comes to complex physical systems. Solving these equations is a perpetual challenge, however, and current computational techniques for doing so are time-consuming and expensive.