Data and AI on Power

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  • I'm sorry, I was advised that the recording has expired and been taken down since the webinar is over a year old. If I'm able to find the original MP4 and/or charts I will post them here. In the meantime, we held another webinar last July you may find ...

  • Hi, Linda, there is still nothing on the recording link , could you help ? really looking forward to watching it. Thanks. @Linda Alkire ------------------------------ XIN LIU ------------------------------

  • Hi Dahraneesh - I'm looking into this. Will respond asap. Thanks! ------------------------------ Linda Alkire IBM Minneapolis MN ------------------------------

Latest Blogs

  • Introduction Large Language Models (LLMs) are revolutionizing various fields, and vLLM emerges as a powerful library for LLM inference and serving. Great news for users with ppc64le hardware! Recent developments ( https://github.com/vllm-project/vllm/pull/5652 ...

    1 person likes this.
  • This blog outlines the process for building and running InstructLab on IBM Power10 systems. Note that this tutorial focuses on building ilab on bare metal. See Marvin Gießing's blog for instructions on running InstructLab via a prebuilt podman container. ...

    1 person likes this.
  • InstructLab on IBM Power Servers Introduction InstructLab, an open-source project developed by IBM and Red Hat, enhances large language models (LLMs) for generative AI applications. It offers a cost-effective solution for aligning LLMs with business ...

    1 person likes this.
  • Co-author: Ashwin Srinivas This is a foundational blog that serves as a building block for setting up an AI environment on IBM Power10. It can be used to build high-level generative AI (gen AI) use cases on IBM Power servers with the help of IBM ...

    2 people like this.
  • There is a LOT of buzz right now regarding Artificial Intelligence (AI), in particular, generative AI. Generative AI refers to deep-learning models that can generate high-quality text, images, and other content based on the data they were trained on. ...

    1 person likes this.

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