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Oman Plans To Have 22,000 EVs On Its Roads By 2030
The country also aims to distribute 350 chargers across busy arterial and public roads by 2026.
As Middle Eastern countries like the United Arab Emirates and Saudi Arabia invest huge sums of money into clean transport initiatives, Oman is also beginning efforts to decarbonize its roads. The ambitious plans by transport authorities hope to see an estimated 22,000 electric vehicles on the country’s roads by 2030.
According to the Minister of Transport, Communications, and Information Technology, Said Hamood al Maawali, the lofty goal will require expanding a network of 350 public chargers across the country by 2026.
“Technological advances have led to the development of dual-combustion vehicles, which have been implemented locally within the Sultanate of Oman. These breakthroughs have greatly contributed to reducing greenhouse gas emissions, estimated to have dropped by 40% from trucks and heavy equipment,” said Maawali in a recent newsletter.
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Oman’s larger sustainability and decarbonization goals aim to slash annual transport sector emissions (estimated at around 22 million tons) by 3% in 2030.
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UAE-Built Falcon-H1 Arabic Leads LLM Benchmarks
The lean Emirati-built language model beats larger global systems and puts Arabic at the center of training.
Abu Dhabi’s Technology Innovation Institute has released an Arabic-first large language model that tops global test boards, an uncommon edge for a region long served by English-centric systems.
Falcon-H1 Arabic comes in 3B, 7B and 34B versions. The flagship posts 75.36% accuracy on comprehensive Arabic tasks and ranks first on the Open Arabic LLM Leaderboard. It also outperforms Meta’s Llama-70B and Alibaba’s Qwen-72B while using less than half their parameters. The smallest model beats Microsoft’s Phi-4 Mini by ten percentage points on equivalent benchmarks.
Arabic remains hard territory for AI. Flexible word order, dense morphology and constant switching between regional dialects and Modern Standard Arabic leave many global models missing context or tone. Academic research has pointed to a shortage of annotated datasets for dialect and informal speech. The impact shows up in classrooms, call centers and government portals where Arabic chatbots lag their English counterparts.
TII trained Falcon-H1 Arabic on formal writing, dialects and culturally grounded content. Beyond scores, it handles practical use: long conversations, reasoning rather than literal translation, and inputs of up to 192,000 words — enough for medical records or legal filings.
“The aim is innovation that is accessible, relevant, and impactful,” said Faisal Al Bannai, Adviser to the UAE President and Secretary-General of the Advanced Technology Research Council.
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Arabic is spoken by more than 450 million people across over 20 countries, yet has often been treated as a secondary language for foundation models. The UAE move signals a push to flip that logic and build Arabic-native stacks rather than wait for global systems to improve.
Falcon models have led their categories since 2023. With H1 Arabic, TII is offering free access via chat.falconllm.tii.ae for developers, media, healthcare and public-sector users looking to automate in natural Arabic.
As the region continues to invest in sovereign computing and data localization, the addition of Falcon-H1 Arabic adds a powerful tool built for the native language, instead of an afterthought attached to an English-trained system.
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