Introducing new task-optimized summarization capabilities powered by fine-tuned large-language model
Published Nov 15 2023 08:55 AM 4,318 Views
Microsoft

For years, developers around the world have relied on pre-built AI capabilities offered through Azure AI Language, ranging from analyzing sentiment, extracting information, mining opinions and much more. Such pre-built capabilities have accelerated AI building efforts for enterprises looking to support users across geographies. Summarization is one such capability, with many customers using it to optimize their AI workflows. For instance, Beiersdorf uses document summarization and key phrase extraction to power an advanced AI platform that harnesses their resources and condensing essential knowledge around cutting-edge skin care solutions (Customer Story HERE). Arthur D Little, similarly uses abstract summarization to unlock the teams’ collective intelligence (Customer Story HERE) .

 

Today we are thrilled to announce new capabilities that are designed to accelerate customers’ AI workflows allowing them to build summarization use-cases faster than ever before. We are expanding our utilization of LLMs to GPT-3.5 Turbo, along with our proprietary z-Code++ models to offer task-optimized summarization using a balance of output accuracy and cost.

 

Here are some of the highlights. All the new public previews are available under api-version 2023-11-15-preview.

  • [in public preview] More out-of-the-box conversation summarization capabilities, e.g. meeting recap and follow-up tasks, in addition to existing capabilities -- narrative, chapter title, issue and resolution. The “recap” aspect condenses a lengthy meeting or conversation into a concise one-paragraph summary to provide a quick overview, and the “follow-up tasks” aspect summarizes out action items and tasks that arise during a meeting.
  • [in public preview] Support the native documents formats, including Word, PDF, PowerPoint in addition to plain text. Customers can now input documents directly without the need for conversion. Please read this post for more.
  • [in public preview] Summarize articles and reports for a specific point of interest, as opposed to a general summarization that is currently available. For example, to get targeted summaries for this news about Microsoft merging Activision Blizzard , you can specify “Activision Blizzard” or “Early Settlement Date” or other queries as your point of interests. The summary generated will then focus more on these points of interest rather than a general summarization.
  • [in public preview] 8 new languages for conversation summarization (namely French, German, Italian, Japanese, Korean, Chinese, Portuguese, Spanish) in addition to English, 2 more languages (namely Hebrew and Polish) for document summarization in addition to those supported with conversations summarization.
  • [in public preview] Container solutions with options for connected as well as disconnected, allowing customers to use summarization in more regions and countries beyond what is supported by the cloud offering. For information about container solution, please check on the Summarization Container Blog
  • [in public preview] Document Analysis sample flow in Prompt Flow for quick start. In the sample flow we have integrated all building tools for a document analytics use cases where you can translate, PII redact, summarize, extract entities, etc. You can also tailor the flow for your own needs by drag and drop the building tools, even add your own tools if necessary. For more information and getting started, please visit Document Analysis Prompt Flow README.
  • Commitment tier pricing making it a cost-effective choice for long-term usage.
  • [in public preview] One preview region, Sweden Central, are added for showcasing our latest and continually evolving LLM finetuning techniques, where all summarization capabilities are available. We welcome customers to try it out by creating a resource in this preview region. Your valuable feedback is vital to our continuous enhancement.

Document summarization (pre-prompt-engineered, 2 styles, query-focused, length control, 11 Languages, 125K chars, ~ 60 pages, in Prompt Flow, in container)

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Conversation summarization (pre-prompt-engineered, 6 aspects, 9 languages, 125K chars, ~3 hours, in container)

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We can’t wait to see developers use these new capabilities and remain committed to delivering innovative solutions that enable our customers to achieve their goals. Thank you for your continued trust in our products, and we welcome your feedback as we strive to continuously improve our services.

For more details and resources, please explore the following links:

 

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