However, most of the world's languages, often referred to as "low-resource languages", still remain either not supported or insufficiently supported due to the limited availability of data and language resources, and market, economic, and global inequality factors. Mali, a multilingual country with 13 official languages, including Bamanankan (Bambara), Bomu, Bozo, Dɔgɔsɔ (Dogon), Fulfulde (Fula), Hassaniya Arabic, Mamara (Minyanka), Maninka, Soninke, Sɔõɔy (Songhay), Senara, Tàmàsàyt (Tamasheq) and Xaasongaxanno (Kassonke), faces severe challenges in digital inclusion limiting economic development, educational advancement, and preservation of cultural heritage (Bird, 2020; Nekoto et al., 2020). These languages share in common a penury of language resources needed to train AI and NLP systems which could play a role in lessening the digital divide (Hammarström et al., 2018). This penury extends from severe in the case of a language like Bambara which has very limited resources to catastrophic for languages like Bomu and Bozo with an almost complete absence of language resources. The need for innovative methods for low-resource languages has spawned varied strategies, such as transfer learning, zero-shot learning, and pre-trained models in related languages (Ruder, 2021; Adelani et al., 2022).

You would think that Arm, which arguably has been the vanguard in the smartphone and PC industry push for improved power efficiency, would double down on that strategy in its plans for 2025. PCWorld sat down at CES 2025 with Chris Bergey, senior vice president and general manager for Arm's client line of business. Bergey is responsible for both the smartphone as well as the laptop and tablet business, where Arm's designs are licensed by companies like Qualcomm and Apple, who tweak and eventually manufacture them as finished goods. Arm provides multiple types of licenses, but the two most common types are a core license, where a customer will buy a verified core that includes an Arm Cortex CPU, Mali GPU, or other intellectual property. Arm also sells architectural licenses to companies like Apple, which gives them the freedom to design their own cores from scratch, though they must be fully compatible with the Arm architecture.

If you're dreading the long winter nights, the Kinhank Super Console X2 Pro is here to save the season--and your sanity. With over 70,000 pre-loaded retro games, this gaming emulator console brings back the joy of childhood classics while offering all the modern conveniences you'd expect today. From Pac-Man and Sonic to Dark Souls and Rocket League, you'll find titles spanning generations and genres. It all runs smoothly thanks to the powerful S905X2 chip and the Mali-G31MP2 GPU, delivering stunning 4K UHD visuals for a truly immersive experience. Powered by dual systems, Android 9.0 for streaming and apps, and EmuELEC 4.5 for gaming, the Super Console X2 gives you versatility at your fingertips.

At least 21 people, including 11 children, have been killed in drone attacks in the town of Tinzaouaten in northern Mali. A spokesperson for the coalition of Tuareg-majority groups fighting for independence in northern Mali said on Monday that the drones hit a pharmacy and a group of people, leaving dozens wounded. Mali's army confirmed the drone attacks on national television, saying the "precision strikes targeted terrorists". Tinzaouaten has witnessed air attacks before and as recently as July when the Tuareg-led groups claimed to have killed a large number of Malian soldiers and Russian Wagner Group mercenaries. The separatists said they killed at least 47 soldiers and 84 Wagner mercenaries in the July attacks, but the army did not confirm that death toll.

Various macroeconomic and institutional factors hinder FDI inflows, including corruption, trade openness, access to finance, and political instability. Existing research mostly focuses on country-level data, with limited exploration of firm-level data, especially in developing countries. Recognizing this gap, recent calls for research emphasize the need for qualitative data analysis to delve into FDI determinants, particularly at the regional level. This paper proposes a novel methodology, based on text mining and social network analysis, to get information from more than 167,000 online news articles to quantify regional-level (sub-national) attributes affecting FDI ownership in African companies. Our analysis extends information on obstacles to industrial development as mapped by the World Bank Enterprise Surveys. Findings suggest that regional (sub-national) structural and institutional characteristics can play an important role in determining foreign ownership.

In work presented at the 32nd International Joint Conference on Artificial Intelligence (IJCAI 2023), Kshitiz, Sonu Shreshtha, Ramy Mounir, Mayank Vatsa, Richa Singh, Saket Anand, Sudeep Sarkar and Sevaram Mali Parihar investigate using computer vision techniques to monitor large flocks of birds. In this interview, Kshitiz tells us more about this research. In our work, Long-term Monitoring of Bird Flocks in the Wild, published in IJCAI 2023, we delve into developing and applying computer vision techniques and datasets tailored for non-invasive monitoring and analysis of migratory bird flocks in their natural habitats. The aim is to understand the behavior and ecology of migratory birds through automated video analysis with minimal human intervention, thereby bolstering conservation initiatives. The core technical challenges associated with wildlife monitoring arise from the uncontrolled, outdoor nature of the imagery (both images and videos) capturing large flocks of migratory birds over several months.

Emerging applications such as Deep Learning are often data-driven, thus traditional approaches based on auto-tuners are not performance effective across the wide range of inputs used in practice. In the present paper, we start an investigation of predictive models based on machine learning techniques in order to optimize Convolution Neural Networks (CNNs). As a use-case, we focus on the ARM Compute Library which provides three different implementations of the convolution operator at different numeric precision. Starting from a collation of benchmarks, we build and validate models learned by Decision Tree and naive Bayesian classifier. Preliminary experiments on Midgard-based ARM Mali GPU show that our predictive model outperforms all the convolution operators manually selected by the library.

Important From release 22.05: 'master' branch has been replaced with'main' following our inclusive language update, more information here. Important From release 22.08: armv7a with Android build will no longer be tested or maintained. The Compute Library is a collection of low-level machine learning functions optimized for Arm Cortex -A, Arm Neoverse and Arm Mali GPUs architectures. The library provides superior performance to other open source alternatives and immediate support for new Arm technologies e.g. Note: The documentation includes the reference API, changelogs, build guide, contribution guide, errata, etc.

The paper aims to develop a framework for coalgebraic fuzzy geometric logic by adding modalities to the language of fuzzy geometric logic. Using the methods of coalgebra, the modal operators are introduced in the language of fuzzy geometric logic. To define the modal operators, we introduce a notion of fuzzy-open predicate lifting. Based on coalgebras for an endofunctor $T$ on the category $\textbf{Fuzzy-Top}$ of fuzzy topological spaces and fuzzy continuous maps, we build models for the coalgebraic fuzzy geometric logic. Bisimulations for the defined models are discussed in this work.

Atmospheric pollution remains one of the major public health threat worldwide with an estimated 7 millions deaths annually. In Africa, rapid urbanization and poor transport infrastructure are worsening the problem. In this paper, we have analysed spatio-temporal variations of PM2.5 across different geographical regions in Africa. The West African region remains the most affected by the high levels of pollution with a daily average of 40.856 $\mu g/m^3$ in some cities like Lagos, Abuja and Bamako. In East Africa, Uganda is reporting the highest pollution level with a daily average concentration of 56.14 $\mu g/m^3$ and 38.65 $\mu g/m^3$ for Kigali. In countries located in the central region of Africa, the highest daily average concentration of PM2.5 of 90.075 $\mu g/m^3$ was recorded in N'Djamena. We compare three data driven models in predicting future trends of pollution levels. Neural network is outperforming Gaussian processes and ARIMA models.