Effective implementation of artificial intelligence differentiates competitive organizations from those that are not and/or will not be. In this article I examine five possible strategies for optimizing AI capabilities.

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Mastery with prompts helps in interaction with ia, especially mastery with the booleans. Well-structured prompts improve the quality and relevance of responses. Techniques include:

• Prompt with examples to guide learning
• Chain Prompt for logical reasoning
• Contextual prompts for specific responses

For those interested in learning more, see also this paper

With this, however, we only go so far. The fundamental concept to understand is that the more knowledge on a specific topic, the better the answer obtained. Just as a physicist will get better answers on physics topics, so a lawyer will get better answers on legal issues because of using the correct technical language. It may sound paradoxical, but the more you know about a specific topic, the more accurate answers you will get. That was already the case with Google searches, so it is with AI. I will elaborate on this later, with reference to what has been said here, and with reference instead to the use of prompts in training generic models.

Integration of extensions into LLMs. Ex. Gemini in the Google ecosystem

Another useful approach to exploiting the potential of this tool is the use of so-called "extensions" within an existing "ecosystem."

Gemini Extensions bring AI functionality to everyday tools:

• Automatic summaries of YouTube videos
• Email analysis in Gmail
• Assistance with travel planning
• Documentary summaries

Creating dynamic audience segments with AI, or why it is not necessary to read people's minds to predict or influence their behavior.

Audience segmentation with AI enables rapid feedback on marketing and content through:

• Detailed target setting
• Training with industry data
• Interface for evaluating ideas
• AI feedback analysis
• Support for creative brainstorming

The use of dedicated platforms and/or proprietary algorithms that monitor a buyer's behavior makes it possible to create a "psychological" profile of the buyer person over time, sometimes even going so far as to predict their future thoughts and buying behavior. Read more here

Building AI chatbots

The transformation of business knowledge into interactive systems requires:

• Systematic collection of sources
• IA platform selection
• Implementation of training protocols
• Constant updating of content

Implementation of AI tutors

In education, AI tutoring systems support learning through:

• Natural language communication
• Customized paths
• Integration with existing programs
• Adapting to learning styles
• Support for educators

Future prospects:

• Focus on human capacity building
• Iterate based on feedback
• Update knowledge
• Aligning AI with organizational goals
• Evaluating new applications with a strategic approach

Companies that balance technology and concrete goals gain the most benefit from these tools.