Navigating unfamiliar territories is a challenging task for robotic systems. Practice can also occur on bodily, real-world data collected from recordings made by people, although this is rare and expensive to obtain. While digital simulations offer a rapid and scalable means to retrain robots for new tasks, the machines often falter when transferred from virtual environments to real-world settings, requiring identical duties.
There’s undeniably a heightened potentiality: a novel framework combining generative AI models with a physics simulator to create virtual training environments that more accurately replicate the physical realm, thereby enabling trainers and trainees alike to hone their skills in an increasingly lifelike setting? In real-world tests, robots trained via this approach outperformed those schooled using more traditional methods in terms of success rate.
Researchers employed LucidSim, a novel system, to train a robotic dog in parkour, successfully guiding it to navigate obstacles like a field and stairs without ever being exposed to real-world visual data. The approach showcases the potential of generative AI in enabling robots to tackle complex tasks effectively. Can these skills actually come to fruition in immersive virtual environments? .
After discussing the global race for artificial intelligence supremacy, the conversation usually centres on the escalating competition between the United States and China, as well as European endeavours to regulate this burgeoning technology? It’s long overdue that we discuss another player: Africa.
African artificial intelligence researchers are blazing a trail of innovation, developing tools tailored to meet the distinct needs and linguistic diversity of African communities. On the African continent, a narrative unfolds that transcends mere perseverance and ingenuity, instead highlighting the crucial effort to safeguard cultural heritage and shape the utilization of AI technologies within its own borders. Nonetheless, they face many boundaries. .
