#Edtech

In the digital age, Thai parents are bombarded with advice about using parental controls, but new research and expert consensus confirm an unsettling truth: no matter how diligent parents are, technology’s current safeguards fall short of genuinely protecting children online. This reality, revealed by recent studies and policy debates, underscores a growing call for government and industry accountability, echoing urgent lessons from the United States that resonate strongly with Thailand’s increasingly tech-centric society (Inquirer).

In Thailand’s connected world, parental controls are everywhere. Yet new research and expert consensus show a hard truth: even the best parental vigilance cannot fully shield children from online risks. This reality calls for greater accountability from governments and industry, echoing lessons from global debates that resonate with Thailand’s tech-driven households and schools.

Thai parents juggle screens, apps, and games across multiple devices. Tools such as screen-time limits, content filters, and monitoring apps help, but trusted researchers warn they offer only partial protection. A growing concern is that unofficial control apps can threaten privacy and are often bypassed by tech-savvy youths. While these findings come from international sources, they are increasingly relevant as Thailand expands its digital infrastructure in homes and classrooms.

Cutting-edge research has pulled back the curtain on the brain’s secret playbook for learning, unveiling rules that govern how we master new skills and knowledge—a discovery with profound implications for both education and artificial intelligence (AI). Scientists, backed by the U.S. National Institutes of Health (NIH), harnessed revolutionary synapse imaging technology to observe real-time changes among the brain’s neurons during learning, uncovering patterns that promise new understanding of how we become smarter—with practical lessons for schools in Thailand and emerging AI technologies worldwide SciTechDaily.

A new MIT study upends decades of neuroscience by showing the brain’s object-recognition pathway may also play a crucial role in processing spatial information. This could transform approaches to learning, AI, and brain health, including in Thailand.

For years, scientists have said the ventral visual stream is mainly about identifying objects—think recognizing a coffee cup on a Bangkok Skytrain or a rambutan vendor at Chatuchak. This view guided neuroscience education and powered computer-vision advances used in smartphones and smart cars. Now, MIT researchers led by graduate student Yudi Xie demonstrate that training deep learning models to grasp spatial details like location, rotation, and size yields brain activity in the ventral stream that matches, or even exceeds, traditional object-recognition models. The ventral stream may be a versatile toolkit for seeing and interacting with the world, not just a face- or product-recognition system.

A groundbreaking study from MIT is shaking up decades of neuroscience wisdom, revealing the brain’s “object recognition” pathway may also play a significant role in understanding spatial information—an insight that could revolutionize our approach to learning, artificial intelligence, and brain health around the world, including here in Thailand.

For years, scientists have believed the ventral visual stream, a key pathway in the human brain, is dedicated to recognizing objects—like a Starbucks cup on a Bangkok Skytrain or a rambutan vendor at the Chatuchak Market. This idea shaped not just neuroscience textbooks, but also inspired computer vision systems now used in everything from smartphones to smart cars. Yet, new research led by MIT graduate student Yudi Xie suggests the story is far more nuanced. Their findings, presented at the prestigious International Conference on Learning Representations, show that when deep learning models are trained not only to identify objects, but also to understand spatial features like location, rotation, and size, these models mirror neural activity in the ventral stream just as accurately as traditional object recognition models. In other words, the ventral stream might be wired for much more than recognizing faces or products—it could be a multifaceted toolkit for seeing and interacting with the world.