Explore how generative AI reshapes children's storytelling, boosting creativity and inclusivity, while addressing ethical and data security concerns. Understand the impact of AI tools like OpenAI's GPT-4, Midjourney-Storybird, and Replika, and uncover the future of AI in education.
In this podcast episode, I discuss Polygon as a unique psychology practice that provides online support for individuals with dyslexia, ADHD, and other learning differences. I share my personal journey, business scale-up plans, importance of data security, and the promising role of AI in healthcare.
At IBM's Code in Cloud conference, I highlighted the crucial role of developers in shaping digital transformation. The discussion emphasized their influence on open-source technologies, cloud computing, and their ability to discern trends amidst overwhelming information.
During a project at Politecnico, Quentin Biabaud recounted my leadership journey, as a French engineer made entrepreneur.
📑 Innovative Leadership StoryUnravel complex concepts like fluid and crystallized intelligence, the Cattell-Horn-Carroll theory, and the working memory theory. I delve into the criticisms of traditional models, the Flynn effect, and the potential of new research for a clearer understanding of intelligence and its impact on education.
This article takes an intricate journey through the use of machine learning in classifying sleep stages. Delving into the handling of EEG data, feature engineering, model building, and prediction smoothing, it reveals how modern techniques can revolutionize our understanding of sleep health and improve everyday lives.
This article discusses the application of Topological Data Analysis (TDA) in clustering through the ToMATo algorithm. This novel approach helps identify the number of data clusters and gathers data into distinct sets. I share here insights on the ToMATo algorithm, providing a proof-of-concept code and real-world examples, and discusses its potential implications.
Dive into the revolutionary field of Topological Data Analysis (TDA) and its role in shaping the future of machine learning and deep learning. Understand core concepts like persistence homology, Betti curves, persistence landscapes, and more, along with their practical applications and significance in data analysis.