Join Technovation Girls and learn how to use technology like mobile apps and AI to solve a community problem YOU care about. You'll work as part of a team of girls like you and get support from a mentor who will help keep you motivated and on track.
הילמ"ה- הייטק למען החברה, היא חברה לתועלת הציבור וללא מטרות רווח, שהוקמה ב-2018 על ידי בכירים בעולם ההיי-טק הישראלי, המבקשים להפוך את ישראל למובילה עולמית בתחום חדשנות האימפקט,
על מנת לתת מענה לאתגרים ציבוריים וחברתיים.
הילמ"ה הוקמה בהשראת יחידת 8200 הצה"לית, והיא מכשירה דור של צעירות וצעירים מוכשרים ושאפתנים לפיתוח פתרונות טכנולוגיים-חברתיים פורצי דרך לתועלת החברה.
הפתרונות של הילמ"ה מתוכננים בהתאמה מלאה לצורכי החינוך, הרווחה והבריאות, ומתקבלים באהדה רבה על ידי לקוחות, קולגות ושותפים לדרך.
In the Developmental Intelligence Laboratory, we are interested in understanding fundamental cognitive mechanisms of human intelligence, human learning, and human interaction and communication in everyday activities. To do so, we collect and analyze micro-level multimodal behavioral data using state-of-the-art sensing and computational techniques. One of our primary research aims is to understand human learning and early development. How do young children acquire fundamental knowledge of the world? How do they select and process the information around them and learn from scratch? How do they learn to move their bodies and to communicate and interact with others? Learning this kind of knowledge and skills is the core of human intelligence. To understand how human learners achieve the learning goal, the primary approach in our research is to attach GoPro-like cameras on the head of young children to record egocentric video from their point of view. Using this innovative approach, we've been collecting video data of children’s everyday activities, such as playing with their parents and their peers, reading books with parents and caregivers, and playing outside. We've been using state-of-the-art machine learning and data mining approaches to analyze high-density behavioral data. This research line will ultimately solve the mystery on why human children are such efficient learners. Moreover, the findings from our research will be used to help improve learning of children with developmental deficits. A complimentary research line is to explore how human learning can teach us about how machines can learn. Can we model and simulate how a human child learns and develops? To this end, our research aims at bridging and connecting developmental science in psychology and machine learning and computer vision in computer science.
D. Persico, C. Milligan, and A. Littlejohn. Procedia - Social and Behavioral Sciences, (2015)The Proceedings of 6th World Conference on educational Sciences.