Benefits for Enterprises
Modern companies face ever-increasing volumes of data while competitive pressure demands faster decision-making. In this context, Generative Artificial Intelligence (Generative AI or GenAI) represents a strategic lever: it not only processes and analyzes vast amounts of information but is also capable of creating new content, insights, and solutions. When correctly integrated into business processes, Generative AI becomes a driver of efficiency and competitive differentiation, opening new opportunities for growth.
Blue BI places innovation at the heart of its strategy, developing Generative AI solutions to guide companies through the adoption of this emerging technology.
Foundation Models
Generative AI is based on Foundation Models (in the case of Natural Language Processing, these are specifically referred to as Large Language Models or LLMs): mathematical Machine Learning models capable of generating content nearly identical to that created by humans. These models have become increasingly efficient and powerful, but they are also expensive to train and maintain, requiring specific technical expertise, massive amounts of data, and complex, costly server management.
Generative AI as-a-service
For most companies, adopting a proprietary Foundation Model (FM) is an unfeasible option due to high costs and associated risks. This has led to the rise of GenAI-as-a-Service cloud offerings, such as Amazon Bedrock, Azure OpenAI, and Google Vertex AI. These services provide programmatic access (via API) to pre-trained, ready-to-use Foundation Models, allowing users to pay only for the actual requests made to the model. Thanks to this strategy, the cost and complexity of creating and maintaining models are shifted to the Cloud Provider, minimizing risks for the user. Furthermore, all these services guarantee data privacy, ensuring that user data is not used to train other models or sold to third parties.
Amazon Bedrock: an introduction
Amazon Bedrock is the Amazon Web Services (AWS) suite service dedicated to Generative AI. It allows access to a range of pre-trained models via API, enabling users to customize requests and pay on a “pay-as-you-go” basis, depending on the number and size of requests (measured in tokens/words). While some models are proprietary to Amazon, others belong to third-party providers such as Anthropic (Claude), AI21 Labs (Jurassic), or Meta (Llama). These models perform various functions, including:
- Text-embedding: converting text into a mathematical representation so it can be processed by other models or search services.
- Text-to-text: generating a textual response to a prompt or question.
- Text-to-image: creating an image based on a description.
Amazon Bedrock: customization
Foundation Models are typically trained on a vast amount of information and can perform many tasks with a broad baseline of knowledge. However, it is often necessary to customize a model’s responses by adding specific context, external documentation, or a particular format and tone. The most common strategies for customizing a model are:
- Prompt Engineering: adding context to the “prompt” (the question asked to the model) and specifying the desired output format or tone. This is the simplest and most cost-effective strategy.
- Retrieval Augmented Generation (RAG): this technique enriches the user’s prompt through a pipeline that retrieves external information from a document database. Amazon Bedrock facilitates this through its Knowledge Base service, which natively integrates a Foundation Model with Amazon OpenSearch.
- Fine-Tuning: the most complex strategy, as it involves training the model on new data. Amazon Bedrock offers options like “Continuous Fine-Tuning,” which creates a copy of the model trained with the user’s specific data. This is a higher-cost solution, as the user must then manage and maintain the new model.
Gen-AI Powered Business Intelligence
For Business Intelligence, the next step following “traditional” AI is the adoption of Generative AI, which unlocks new possibilities for optimization, personalization, and competitive advantage:
- Advanced Data Analytics: analyzing the content of reports, meetings, and more to create concise summaries.
- Sentiment Analysis: analyzing text/voice feedback to understand user needs and improve products or processes.
- Enhanced Data Exploration: interacting with complex databases and datasets using natural language queries.
- Automated Reporting and Visualization: automatically generating BI reports, code, charts, and dashboards.
Contact the experts at Blue BI to learn how to enhance your business strategy through Generative Artificial Intelligence.
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