Webinar - Software Engineering for AI: The New Interdisciplinary Paradigm for Innovation

Register for my upcoming free webinar about:

"Software Engineering for AI: The New Interdisciplinary Paradigm for Innovation." planned on December 3, 2024, at https://bit.ly/SWEngineering4AIWebinar

(Speech: in Arabic & Slides: in English)

Using Generative AI, and AI in general, to supercharge the software engineering cycle has been debated over the past one and a half years, with most software experts as advocates. However, what hasn’t yet been discussed enough is vice-versa, which is how the software engineering discipline can shape/reshape the development of AI systems.

Currently, it is a hot topic discussing how the well-known and well-tried "Software Engineering Processes" can produce "Continuously Ready-to-Use and Fit-for-Purpose Machine Learning Models, Deep Learning Models," and even "Generative AI Modes." it can easily imagined that the nature of needed software engineering processes and practices to support and facilitate the production of the "Complete Single or Multi-Model AI Systems" is broadly so different from typical software systems.

As explained in the 64th edition of this newsletter with the same title, "Software Engineering for AI: The New Interdisciplinary Paradigm for Innovation," so many technological trends are pushing enterprises in this direction, which is an entirely brand-new "Interdisciplinary Software Engineering for AI." The first trend is the dramatic increase in the "AI Systems Complexity," mainly due to the Generative AI wave. The second trend is the domination of the "Data-Centric AI" wave as a replacement for the old model-centric AI school of thinking. Finally, the appearance of many "AI Legalization Frameworks," such as the European Union AI-ACT, requires strict and fully transparent software engineering practices to help enterprises become in complete control over the production cycle of the AI systems to detect issues as early as possible (e.g., the shift level approach).

For example, imagine an AI system with a supervised learning ML-classifier model, an unsupervised learning ML-clustering model, a deep-learning image detection model, and an open-source foundation model for language understanding and generation that cooperate to streamline complex enterprise operations. These four models form a complex data-centric AI system that should adhere to AI legalizations.

The domination of and the interaction between these current three major AI trends forces enterprises to examine the power of software engineering for AI. This webinar will investigate this new interdisciplinary approach toward AI innovation, providing strategic insight to move forward into 2025 with a better-informed competitive enterprise AI strategy.

Register at: https://bit.ly/SWEngineering4AIWebinar

(Speech: in Arabic & Slides: in English)