The paper introduces Sparse-Quantized Representation (SpQR), a new compression format and quantization technique for large language models (LLMs). SpQR identifies outlier weights and stores them in higher precision while compressing the remaining weights to 3-4 bits. The method achieves less than 1% accuracy loss in perplexity for LLaMA and Falcon LLMs and enables a 33B parameter LLM to run on a single 24GB consumer GPU. Why it matters: This enables near-lossless compression of LLMs, making powerful models accessible on resource-constrained devices and accelerating inference without significant accuracy degradation.
QRC has developed Qibo, a Python library enabling classical simulation of quantum algorithms with double precision. Qibo leverages hardware accelerators like GPUs and CPUs with multi-threading. It incorporates a multi-GPU distributed approach for circuit simulation. Why it matters: This framework allows researchers and developers in the region to explore and prototype quantum algorithms using existing classical computing infrastructure, fostering innovation in quantum computing research and applications.
Communications Physics journal has a focus collection on space quantum communications. The collection covers supporting technologies, new quantum protocols, inter-satellite QKD, constellations of satellites, and quantum inspired technologies and protocols for space based communication. Contributions are welcome from October 20, 2020 to April 30, 2021, and accepted papers are published on a rolling basis. Why it matters: Space-based quantum communication is a critical area for developing secure, global quantum networks, and this collection could highlight relevant research for the GCC region as it invests in advanced technologies.
The Quantum Research Centre (QRC) at the Technology Innovation Institute (TII) in Abu Dhabi has expanded its team. The center recently added two Senior Researchers, four Young Researchers, and one Visiting Research Professor. TII aims to advance knowledge through scientific research and technological innovation. Why it matters: This expansion indicates continued investment in quantum computing research and development within the UAE, potentially fostering advancements in the field.
The National Institute of Standards and Technology (NIST) has been evaluating Post-Quantum Cryptography proposals since 2017. Lattice-based schemes have emerged as efficient candidates for Key Encapsulation Mechanisms (KEM) and Digital Signatures. This talk will cover the core operations within lattice-based schemes and efficient implementation strategies. Why it matters: As quantum computing advances, exploring and standardizing post-quantum cryptography is crucial for maintaining secure communication and data protection in the future.
Professor Konrad Banaszek from the University of Warsaw will present a seminar at the Technology Innovation Institute (TII) in Abu Dhabi on February 11, 2026. The seminar is part of the Quantum Research Center (QRC) seminar series. The TII is described as a global research center focused on discovery science and transformative technologies. Why it matters: This event facilitates knowledge sharing and collaboration in quantum technologies, a strategic area of research for the UAE.
Conor McMenamin from Universitat Pompeu Fabra presented a seminar on State Machine Replication (SMR) without honest participants. The talk covered the limitations of current SMR protocols and introduced the ByRa model, a framework for player characterization free of honest participants. He then described FAIRSICAL, a sandbox SMR protocol, and discussed how the ideas could be extended to real-world protocols, with a focus on blockchains and cryptocurrencies. Why it matters: This research on SMR protocols and their incentive compatibility could lead to more robust and secure blockchain technologies in the region.
Qatar Computing Research Institute (QCRI) has developed NatiQ, an end-to-end text-to-speech (TTS) system for Arabic utilizing encoder-decoder architectures. The system employs Tacotron-based models and Transformer models to generate mel-spectrograms, which are then synthesized into waveforms using vocoders like WaveRNN, WaveGlow, and Parallel WaveGAN. Trained on in-house speech data featuring a neutral male voice (Hamza) and an expressive female voice (Amina), NatiQ achieves a Mean Opinion Score (MOS) of 4.21 and 4.40, respectively. Why it matters: This research advances Arabic language technology, providing high-quality TTS synthesis that can enhance accessibility and usability of digital content for Arabic speakers.