Exploring the World of AI: Traditional vs. Generative

Artificial intelligence (AI) has transformed how we work, learn, and create. However, not all AI is the same. Two major branches stand out for their methodologies and applications: traditional AI and generative AI. Join us on this journey to better understand these technologies and how they can benefit you.

What is Traditional AI?

Traditional AI focuses on data analysis, prediction, and decision-making based on statistical models or predefined rules. These systems, created with tools like Scikit-learn, TensorFlow, or Keras, learn from structured data to identify patterns and make predictions. Some examples include:

• Fraud detection: Classifying suspicious transactions to prevent losses.
• Medical diagnosis: Assisting healthcare professionals in identifying diseases.
• Product recommendations: Enhancing the shopping experience for users.

Key Characteristics:

• Based on predefined algorithms that follow explicit instructions.
• Primarily employs supervised learning with labeled data.
• Utilizes discriminative models to classify data into specific categories.

Generative AI: The New Frontier of Creativity

Generative AI, on the other hand, is known for its ability to create new content from learned patterns. Tools like GPT-4, DALL-E, and Midjourney allow the generation of text, images, music, and more. This branch of AI is revolutionizing entire industries, from art and design to the generation of synthetic data for computer vision applications.

Key Characteristics:

• Based on generative models that learn from large datasets.
• Can use both supervised and unsupervised learning.
• Exhibits creativity and adaptability, generating innovative content and adapting to changes in input data.

GenAI and the Business World

The unique aspect of generative artificial intelligence (GenAI) lies in the fact that large language models are primarily trained on public internet data. This means that while they are less specific for a particular business use, they can boost productivity in various fields. Currently, GenAI is mainly used to accelerate internal use cases such as content generation and data synthesis.

Companies are combining Retrieval-Augmented Generation (RAG) with GenAI, integrating private information through services like Amazon Bedrock or Amazon SageMaker JumpStart. This allows the models to generate natural language responses and search for more detailed answers through conversational interfaces.

For example, this technology can help an account executive draft a message in response to a proposal for a client based on the company's internal documentation. The key to success with these models lies in blending the optimal amount of specific adjustments without completely retraining them.

Which AI is Right for You?

Understanding the difference between traditional and generative AI is crucial to determining the perfect tool for your needs. Generative AI, with its ability to produce creative and innovative content, explore endless possibilities, and manage uncertainties, offers new industrial applications and transforms the creative arts and media.

If you still have doubts about which type of AI is best suited for your company, don't hesitate to request a consultation with experts who will guide you towards the perfect solution for your specifications and needs. Together, we will find the ideal tool to take your business to the next level!