Service overview
Highlights of the work:
Concept Analysis: Definition of AI, its basic components (Data, Algorithms, Compute), and its intrinsic capabilities.
Historical Narrative: Documenting the journey of AI from the founding stage (1950) to the era of large language models (LLMs).
Technical Classification: Explaining the fundamental differences between the types of artificial intelligence (Narrow, AGI, Superintelligence).
Deep Learning Techniques: Explain Machine Learning (Supervised, Unsupervised, Reinforcement) and the Principles of Deep Learning and Neural Networks.
Use Case Review: Highlight AI applications in business, healthcare, and everyday life.
Future Vision: Analyze the challenges (privacy and bias) against the future benefits and trends of responsible AI.
Skills and techniques used:
Presentation Design: Use modern design tools (e.g. Gamma/PowerPoint) with visual hierarchy in mind.
Content Curation: Crafting technical content that is both accurate and simplified.
Instructional Design: Adding speaker notes to guide the presenter and ensure the flow of information.
AI Knowledge: A deep understanding of the difference between ML and Deep Learning and the ability to explain it.

