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  1. artefacts.aiArtefacts.AI

    Artefacts is a 3D AI toolkit that enables users to effortlessly transform text or 2D images into 3D assets. Unleash your creativity with Artefacts - the future of 3D content creation.

  2. app.artefacts.aiArtefacts.AI

    Artefacts.AI. Log in to Artefacts.AI to continue. Forgot password? Continue. Need an account? Sign Up. Other Log-in Methods. Having trouble logging in? Contact us!

  3. prototypr.io › post › claude-artifacts-ai-app-generatorClaude Artifacts: From Conversational AI to App Workspace (a no...

    Jul 18, 2024 · AI generated apps with Claude Artifacts. This overview explores Artifacts' capabilities in generating web tools, games, and visualizations, comparing it to traditional coding and tools like ChatGPT.

  4. artifacts.aiARTiFACTS - Protecting the Global Drug Supply Chain from...

    Artifacts VERIFY is a post-market surveillance system using chemical analysis, AI, and blockchain to detect and report counterfeit medicines.

  5. support.anthropic.com › en › articlesWhat are Artifacts and how do I use them? | Anthropic Help Center

    Artifacts allow Claude to share substantial, standalone content with you in a dedicated window separate from the main conversation. Artifacts make it easy to work with significant pieces of content that you may want to modify, build upon, or reference later.

  6. h2o.ai › wiki › artifactsWhat is an Artifact in Machine Learning? - H2O

    An artifact is a machine learning term that is used to describe the output created by the training process. Output could be a fully trained model, a model checkpoint, or a file created during the training process. AI Artifacts describe all digital products that are used in an AI Tool.

  7. censius.ai › wiki › ai-artifactsWhat is AI Artifacts - Machine Learning | MLOps Wiki - Censius

    What are AI Artifacts? Artifact term denotes the output generated by the training process. These can be a fully trained model, a model checkpoint, or a file created during training. AI artifacts are generated at various stages and used across the ML project lifecycle.