AI agents are becoming more advanced and capable of handling complex tasks across different platforms. Websites and desktop applications are intended for human use, which demands knowledge of visual arrangements, interactive components, and time-based behavior. Handling such systems requires monitoring user actions, from clicks to sophisticated drag-and-drop actions. Such challenges are difficult for AI to… →

Speech generation technology has advanced considerably in recent years, yet there remain significant challenges. Traditional text-to-speech systems often rely on datasets derived from audiobooks. While these recordings provide high-quality audio, they typically capture formal, read-aloud styles rather than the rich, varied speech patterns of everyday conversation. Real-world speech is naturally spontaneous and filled with nuances—overlapping… →

Reinforcement learning (RL) has been a core component in training large language models (LLMs) to perform tasks that involve reasoning, particularly mathematical problem-solving. A considerable inefficiency occurs during training, including a situation where many questions are always answered or left unsolved. The lack of variability in success rates is to blame for inefficient learning results… →

For many years, organizations in the MENA region have encountered difficulties when integrating AI solutions that truly understand the Arabic language. Traditional models have often been developed with a focus on languages like English, leaving gaps in their ability to grasp the nuances and cultural context inherent in Arabic. This limitation has affected not only… →