News
Apple Close To Adding Diabetic Glucose-Tracking To Watches
The Cupertino company has been trialing the technology for a decade, and it now looks like diabetes sufferers will soon be able to monitor glucose using their Apple watch.
The Apple Watch has become a popular health and fitness monitoring tool in recent years, with features including a heart rate monitor, body temperature sensor, blood oxygen monitoring, and women’s health tracking. However, despite a growing feature set, the watch does have one notable omission: blood glucose monitoring.
According to data from the World Health Organization, around 422 million people worldwide have diabetes. Currently, the disease is monitored using a finger-prick test to measure glucose levels or by attaching patches to the skin.
Apple is now reportedly close to adding a non-invasive glucose monitoring solution to its watches after testing various technologies for the best part of a decade. However, it could still be a few years before the device is ready for mass-market application.
If Apple’s monitoring sensors get the green light from medical professionals, its smartwatches could also be used to screen users for pre-diabetic indicators, as well as help long-term sufferers to manage their condition without the pain and inconvenience of skin-prick testing.
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Apple will use a chip-based solution called “silicon photonics” to measure glucose levels, combined with absorption spectroscopy, which measures reflected light to gauge insulin. Although the technology hasn’t yet been peer-reviewed by scientists, the Cupertino company is thought to be deep into the proof-of-concept stage of testing.
Once Apple’s technology has been evaluated by researchers, the company will have to work on reducing the size of the chips, as experts believe that early prototypes are still too large to fit into the compact frame of a smartwatch.
News
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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