TII's Autonomous Robotics Research Center (ARRC) and NYU's Agile Robotics and Perception Lab have released RLtools, an open-source reinforcement learning library. RLtools achieves a 75x speed-up in training compared to existing libraries, enabling drone controller training on standard computers. It allows training on consumer-grade laptops or directly on microcontrollers, addressing resource efficiency and deployment challenges. Why it matters: This library accelerates the development and deployment of autonomous systems by reducing training time and resource requirements, making advanced AI more accessible.
The Technology Innovation Institute (TII) and NYU Abu Dhabi (NYUAD) have signed a collaboration agreement to deepen strategic collaboration in research, education, and talent development. The partnership includes a Research and Development Sponsorship Agreement and a Framework Fellowship Program Agreement. TII and NYUAD will collaborate on joint research projects across areas like AI, robotics, and quantum science, and TII will sponsor NYUAD students for research in priority technology domains. Why it matters: The partnership aims to bridge fundamental research with real-world applications, accelerate scientific discovery, and develop a pipeline of skilled researchers in Abu Dhabi.
The Technology Innovation Institute (TII) in Abu Dhabi has launched a cloud API providing access to quantum-inspired algorithms developed by its Quantum Research Center (QRC). The platform offers a testbed for partners to evaluate and build proof-of-concept applications, with the first algorithm being a quantum annealing emulator. Access is provided through two interfaces, enabling large-scale classical simulations and supporting the solution of combinatorial optimization problems. Why it matters: This initiative expands TII's quantum ecosystem and facilitates applied research and early-stage industry experimentation with advanced computational methods in the GCC region.
The Technology Innovation Institute (TII) in Abu Dhabi, in collaboration with NVIDIA, has demonstrated large-scale simulations of the adiabatic quantum annealing (QA) algorithm for problem instances involving up to 500,000 qubits. TII's simulator achieved solution quality exceeding that of all solvers evaluated from the MQLib repository, a library for combinatorial optimization benchmarking. The emulator is accessible to external users via an experimental cloud platform hosted at https://q-inspired.tii.ae. Why it matters: This collaboration expands the range of complex optimization problems that can be investigated using quantum-inspired approaches, beyond those currently achievable with near-term quantum hardware.