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In many generativeAI applications, a large language model (LLM) like Amazon Nova is used to respond to a user query based on the models own knowledge or context that it is provided. Instead of relying on promptengineering, tool choice forces the model to adhere to the settings in place.
The model serves as a tool for the discussion, planning, and definition of AI products by cross-disciplinary AI and product teams, as well as for alignment with the business department. It aims to bring together the perspectives of product managers, UXdesigners, data scientists, engineers, and other team members.
These might prompt us to change the output or refrain from providing it altogether and return a fail-safe message. Since AI models are probabilistic in nature having proper guardrails is a good idea in general, regardless of our stance on hallucinations. This may follow a predefined rule (e.g.,
GenerativeAI and large language models (LLMs) offer new possibilities, although some businesses might hesitate due to concerns about consistency and adherence to company guidelines. The personalized content is built using generativeAI by following human guidance and provided sources of truth.
While each of these innovations brought its distinct touch to the canvas of GenerativeAI, Midjourney, in particular, has continued its compelling journey, making noteworthy strides. The art world is certainly taking notice, with generativeAI in the art market projected to witness a staggering growth of 40.5%
By using a combination of transcript preprocessing, promptengineering, and structured LLM output, we enable the user experience shown in the following screenshot, which demonstrates the conversion of LLM-generated timestamp citations into clickable buttons (shown underlined in red) that navigate to the correct portion of the source video.
The article is written for product managers, UXdesigners and those data scientists and engineers who are at the beginning of their Text2SQL journey. For any reasonable business database, including the full information in the prompt will be extremely inefficient and most probably impossible due to prompt length limitations.
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