World's largest open-source multimodal dataset delivers 17x training efficiency, unlocking enterprise AI that connects documents, audio and video

AI models are only as good as the data they're trained on. That data generally needs to be labeled, curated and organized before models can learn from it in an effective way. One of the big missing links in the AI ecosystem has been the availability of a large high-quality open-source multimodal dataset. That changes…

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Why AI smart home assistants aren’t good enough

Large language models are currently everyone’s solution to everything. The technology’s versatility is part of its appeal: the use cases for generative AI seem both huge and endless. But then you use the stuff, and not enough of it works very well. And you wonder what we’re really accomplishing here. On this episode of The…

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ACE prevents context collapse with ‘evolving playbooks’ for self-improving AI agents

A new framework from Stanford University and SambaNova addresses a critical challenge in building robust AI agents: context engineering. Called Agentic Context Engineering (ACE), the framework automatically populates and modifies the context window of large language model (LLM) applications by treating it as an “evolving playbook” that creates and refines strategies as the agent gains…

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