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  1. dataplatform.cloud.ibm.com › docs › contentPrompt Lab | IBM watsonx

    Hace 5 días · Puede utilizar Prompt Lab para diseñar solicitudes efectivas que envíe a los modelos de base desplegados para la inferencia. No utilice Prompt Lab para crear nuevos modelos base. Este vídeo proporciona un método visual para aprender los conceptos y tareas de esta documentación.

  2. dataplatform.cloud.ibm.com › docs › contentPrompt Lab | IBM watsonx

    Hace 5 días · In the Prompt Lab in IBM watsonx.ai, you can experiment with prompting different foundation models, explore sample prompts, and save and share your best prompts. You use the Prompt Lab to engineer effective prompts that you submit to deployed foundation models for inferencing.

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  4. en.wikipedia.org › wiki › IBM_WatsonIBM Watson - Wikipedia

    Hace 3 días · IBM Watson is a computer system capable of answering questions posed in natural language. It was developed as a part of IBM's DeepQA project by a research team, led by principal investigator David Ferrucci. Watson was named after IBM's founder and first CEO, industrialist Thomas J. Watson.

  5. developer.ibm.com › awb-enhancing-llm-performance-document-chunking-with-watsonxEnhance LLM performance: Document chunking with watsonx

    Hace 1 día · Step 1. Extract text and split into sentences. You begin by extracting the entire text from each document and splitting it into individual sentences. This step ensures that the text is broken down into manageable units for processing. Figure 1. Separate by document, then break down into single sentences. Step 2.

  6. jackshoot.com › blog › get-the-inside-track-what-ai-means-for-your-role-in-liveGet the inside track: What AI means for your role in live...

    Hace 5 días · IBM Watson Media . This platform leverages AI to provide advanced video analytics, automated closed captioning, and personalised content recommendations. IBM Watson Media is particularly adept at analysing viewer engagement and sentiment, helping broadcasters tailor their content in real-time to maximise audience retention and satisfaction.

  7. cloud.ibm.com › catalog › servicesWatson Machine Learning - IBM Cloud

    Hace 5 días · Watson Machine Learning features Take advantage of machine learning models management (continuous learning system) and deployment (online, batch, streaming). Select any of widely supported machine learning frameworks: TensorFlow, Keras, Caffe, PyTorch, Spark MLlib, scikit learn, xgboost and SPSS.

  8. dataplatform.cloud.ibm.com › docs › contentDeploying AI assets | IBM Cloud Pak for Data as a Service

    Hace 4 días · You can deploy and manage assets programmatically by using the watsonx.ai Python client library or Watson Machine Learning API. For additional Cloud Pak for Data as a Service APIs, see Cloud Pak for Data APIs. Managing frameworks and software specifications for deployments