After testing this Garmin rival, I won’t use a smartwatch without a built-in flashlight again


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pros and cons

Pros

  • Integrated LED flashlight with a vibrant AMOLED touchscreen display.
  • Support for the extensive Polar Flow ecosystem.
  • 50m water resistance and MIL-STD-810H rating.
Cons

  • Plastic case and bezel.
  • Single frequency GPS.
  • No support for ECG or blood oxygen.

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It’s that time of year when people start noticing I have tan lines on both my wrists from wearing two watches. One has an integrated LED flashlight for daily use, and the other is a smartwatch. Thanks to Polar’s new Street X smartwatch, picking up a powerful sports watch with a dual-color LED flashlight is much easier at the low $250 price point, which beats existing LED-equipped watches by at least $150. 

Also: I tested the best sports watches in 2026: Here are the latest and greatest watches, no matter your budget

Once you use a sports watch with an LED flashlight, you won’t use another watch without one. I use the device at least once daily to find things in the dark, read restaurant menus, make a bathroom trip in the middle of the night with red-light mode, and light up my way through dark areas. 

If Apple, Google, or Samsung add an integrated LED flashlight to a smartwatch, I might be able to wear one watch, but we haven’t heard any such rumors yet.

Design

I spent the first couple of weeks with the Polar Street X without knowing the price point and just assuming it was about $400. There are some trade-offs in the design compared to other Polar watches, but I was shocked by how affordable the device was when I started drafting this review after testing it out. 

The watch is mostly made of a lightweight, bio-based polymer and features a Gorilla Glass display. The 22mm silicone band is flexible and comfortable. While the casing and bezel are plastic, the watch still looks and feels well constructed and durable.

Five buttons and a touchscreen display make it easy to use

Matthew Miller/ZDNET

The Polar Street X is water-resistant to 50 meters and certified to the MIL-STD-810H shock-resistant criteria, so it’s rugged and built to last. At just 1.7 ounces (48 grams), this is one of the lightest watches I’ve ever tested. With a diameter of 45mm, it can also work well for those with smaller wrists.

LED flashlight

Garmin was the first company to launch a smartwatch with an integrated LED flashlight, and the firm continues to lead the way with flashlight controls available within specific workouts so you can have red and white lights shining at intervals that match your running. Amazfit and then Suunto followed with integrated LED lights, and now it’s up to Coros to join the lighting party.

Once you have a LED flashlight on a watch you won't go back

Matthew Miller/ZDNET

Polar’s LED light is well integrated, requiring a single press of the top-left button. There are five physical buttons on the watch, including one for turning the light on and off. The right-side up and down buttons control four levels of white brightness and one red light. It’s great to see Polar launch with this lighting scheme. I use the red light at night to keep my night vision intact and not wake up my wife while she sleeps, and I wander the house.

Using Polar Flow

One reason I didn’t think the Street X was priced this low is that the data it captures very effectively supports the Polar Flow ecosystem. Cardio Load status, running power, the work/rest guide, FitSpark training guidance, nightly recharge, daily readiness, and so many more features are supported on the watch and through your smartphone connection into the Polar Flow app.

Also: I replaced my Whoop with a rival fitness band that has no monthly fees – and it’s nearly as good

Thankfully, the Polar Flow smartphone app has been redesigned and improved as well. The main Diary screen appears when you launch the app, with a host of metric summaries providing glanceable information. You can also easily toggle various metrics on and off in the settings. 

Other displays include training/testing with mapping so you can use your phone connected to the watch for a big screen tracking experience, an activity tab with all of your daily movements, a nightly recharge tab with exhaustive details of your sleep, and a more tab that has 15 different options for fully customizing the Polar experience.

The Polar Flow smartphone app is much better and provides detailed insights

Matthew Miller/ZDNET

As I’ve shared in the past, Polar provides extreme customization of your workout training views with support for more than 170 activities, so there is virtually no activity that cannot be tracked by the Street X. Dashboard views and custom watch faces are also part of the experience so no other Street X will look just like yours after you spend a bit of time customizing the watch for your lifestyle.

Daily usage

With Polar, I have come to expect premium pricing for its wearables and a rather frustrating smartphone application. The Polar Street X changes that perception with a capable sports watch, with an LED flashlight, and an updated Polar Flow smartphone application that propels Polar back to one of my favorite brands. 

The free training programs and customization options make the Street X a highly recommended sports watch for anyone looking to use a watch to track daily life and improve their performance.

An older generation heart rate monitor and GPS chip impacts the performance

Matthew Miller/ZDNET

GPS and heart rate tracking weren’t as accurate as those of watches at a comparable price point, such as the Coros Pace 4. The defining feature of this watch is its LED flashlight, but the customization options in Polar Flow are also compelling. The watch has a rugged design that may not appeal to those seeking a sleeker, lighter model.

Also: There’s a right way to wear your Apple Watch – and it affects your data

The Polar Street X lasted a week between charges, with a few sessions of running, rowing, and biking. Enabling always-on mode reduces the battery life, but you don’t need it on when a twist of the wrist turns on the display

ZDNET’s buying advice

The Polar Street X is a bit of a departure for Polar with non-premium materials, a previous-generation GPS receiver and heart rate sensor, and some compromises on functionality. The device has the first integrated LED flashlight for Polar and supports most of what Polar Flow offers, with a vast array of customization options. 

The Street X is a great first sports watch if you want one with a dedicated LED light, but just be aware of the compromises in positioning and heart rate accuracy. 





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Embodied Intelligence and the Phenomenology of AI explores how human cognition arises from perception, embodiment, and experience in contrast to disembodied artificial intelligence.

Conceptual diagram illustrating embodied intelligence and the phenomenology of AI through perception, embodiment, environment, and experience.

A Conscious Intelligence Perspective

The rapid development of artificial intelligence has transformed modern discussions about cognition and intelligence. Machine learning systems now recognize patterns in data, generate language, analyze images, and assist with complex decision-making processes across scientific, economic, and technological domains. These capabilities have led some observers to suggest that artificial systems may eventually replicate or even surpass human intelligence.

Yet beneath these technological achievements lies a fundamental philosophical question: what does it mean to be intelligent? While artificial intelligence can perform impressive computational tasks, human cognition emerges from a far more complex interaction between perception, embodiment, and lived experience. Understanding this distinction requires examining the concept of embodied intelligence—the idea that human cognition arises through the dynamic interaction between mind, body, and environment.

Phenomenology, the philosophical study of conscious experience, offers a powerful framework for understanding embodied intelligence. Rather than treating cognition as a purely abstract computational process, phenomenology emphasizes that perception, thought, and understanding occur within a lived world shaped by sensory experience and bodily engagement. When applied to contemporary discussions of artificial intelligence, this perspective reveals important differences between human cognition and machine intelligence.

Within the framework of Conscious Intelligence (CI), embodied intelligence highlights the experiential foundations of human awareness and interpretation. It underscores why human cognition remains essential in guiding technological systems, particularly as artificial intelligence continues to expand its capabilities.

Understanding Embodied Intelligence

The concept of embodied intelligence challenges traditional views of cognition that treat the mind as an abstract information-processing system. Early models of artificial intelligence often assumed that intelligence could be replicated through symbolic reasoning and computational logic. According to this perspective, cognition could be understood as the manipulation of symbols according to formal rules.

However, research in cognitive science and philosophy has increasingly shown that human intelligence cannot be separated from bodily experience. Perception, movement, and environmental interaction play fundamental roles in shaping how individuals understand the world (Varela, Thompson, & Rosch, 1991).

Embodied intelligence suggests that cognition arises through continuous engagement between the organism and its environment. Rather than operating as a detached reasoning system, the mind develops within the context of sensory perception and physical action.

Consider a simple example: observing a bird in flight. This experience involves more than visual pattern recognition. The observer’s body subtly adjusts posture, attention tracks motion through space, and prior experiences shape expectations about movement and behavior. The act of perception becomes an integrated process involving vision, spatial awareness, memory, and anticipation.

This dynamic interaction between perception and action forms the basis of embodied cognition. Intelligence emerges not from isolated computation but from the ongoing relationship between body and world.

Phenomenology and the Lived Body

Phenomenology provides a philosophical foundation for understanding embodied intelligence. While early phenomenologists such as Edmund Husserl explored the intentional structure of consciousness, later thinkers emphasized the central role of the body in shaping perception and cognition.

The French philosopher Maurice Merleau-Ponty argued that human consciousness is fundamentally embodied. In his influential work Phenomenology of Perception, he described the body as the primary site through which individuals encounter the world (Merleau-Ponty, 2012). Rather than functioning as an object separate from consciousness, the body becomes the medium through which experience unfolds.

According to Merleau-Ponty, perception is not merely the passive reception of sensory data. Instead, it is an active process in which the body engages with the environment through movement, orientation, and attention. The body provides a framework through which space, time, and meaning become intelligible.

This perspective challenges purely computational models of intelligence. Artificial systems may process visual data or recognize objects in images, but they do not experience the world through a lived body. They do not move within environments, feel spatial relationships, or engage with objects through physical interaction.

Phenomenology therefore highlights a crucial distinction between human cognition and artificial intelligence: human intelligence is grounded in embodied experience, while most AI systems operate within abstract computational environments.

The Limits of Disembodied Artificial Intelligence

Modern artificial intelligence systems excel at tasks involving pattern recognition and data analysis. Deep learning networks can identify faces in images, translate languages, and predict complex trends based on large datasets. These capabilities have created the impression that machine intelligence may soon approximate human cognition.

However, AI systems typically operate in disembodied informational spaces. They process data within computational architectures rather than through physical interaction with the world. Their “perception” consists of numerical representations rather than lived sensory experience.

Philosopher Hubert Dreyfus argued that early AI research underestimated the importance of embodied and contextual knowledge in human cognition (Dreyfus, 1992). Humans navigate the world through intuitive understanding shaped by years of bodily interaction with their environment. Much of this knowledge remains implicit rather than formally articulated.

For example, people can effortlessly grasp objects, maintain balance while walking, or recognize subtle emotional expressions in social interactions. These abilities arise from complex sensorimotor systems that integrate perception and action.

Replicating such capabilities in artificial systems has proven extraordinarily challenging. While robotics research has made significant progress, the embodied adaptability of biological organisms remains difficult to reproduce through purely computational methods.

This limitation suggests that human intelligence involves dimensions of cognition that extend beyond algorithmic processing. Embodied experience provides a context for understanding that cannot easily be reduced to data structures or symbolic reasoning.

Embodiment and Meaning

One of the most important implications of embodied intelligence concerns the nature of meaning. Human understanding emerges through interaction with environments that are experienced through the body.

Language, for example, is deeply connected to embodied experience. Words describing spatial relationships, movement, and sensation reflect how humans encounter the world physically. Even abstract concepts often originate from metaphors grounded in bodily perception.

Artificial intelligence systems can generate language that appears coherent and meaningful, yet they do not experience the embodied contexts that give language its significance. Large language models predict patterns in textual data without possessing an experiential understanding of the concepts they describe.

This distinction helps explain why AI systems sometimes produce outputs that appear plausible yet lack deeper comprehension. Without embodied experience, machines cannot anchor meaning in lived reality.

Phenomenology therefore emphasizes that understanding involves more than symbolic manipulation. Meaning arises from engagement with the world, shaped by perception, movement, and social interaction.

Embodied Intelligence in Human Practice

Embodied intelligence is visible in many aspects of human activity. Artists, athletes, musicians, and craftspeople rely heavily on forms of knowledge that cannot easily be articulated through formal rules. Their expertise develops through repeated interaction between perception and action.

In observational practices such as photography, for example, perception involves more than simply recording visual information. The observer anticipates movement, adjusts bodily orientation, and interprets environmental cues to capture meaningful moments. These processes occur through embodied awareness rather than through explicit calculation.

Scientific inquiry also involves embodied intelligence. Researchers conduct experiments, manipulate instruments, and interpret physical phenomena through sensory engagement with experimental environments. Knowledge emerges through interaction between theory, observation, and experience.

These examples illustrate how intelligence unfolds through embodied practice. Human cognition develops not only through abstract reasoning but also through lived engagement with the world.

Embodied Intelligence and Conscious Intelligence

Within the framework of Conscious Intelligence, embodiment plays a crucial role in shaping how individuals understand and guide technological systems. The CI model emphasizes three pillars—meta-awareness, interpretive agency, and responsible alignment—and embodied intelligence provides experiential grounding for each.

Meta-awareness involves reflecting on one’s own cognitive processes. Phenomenological reflection encourages individuals to examine how perception and bodily engagement influence understanding.

Interpretive agency arises from the human capacity to assign meaning to experiences. Embodied perception provides the contextual richness that allows individuals to interpret information within lived environments.

Responsible alignment involves directing technological capabilities toward ethical and constructive purposes. Embodied awareness can deepen ethical reflection by highlighting the real-world consequences of technological decisions for human experience.

By emphasizing embodiment, the CI framework reinforces the importance of human awareness in guiding artificial intelligence. Machines may extend computational capabilities, but human cognition provides the experiential perspective necessary to interpret and apply technological outputs responsibly.

Toward Embodied Artificial Intelligence

Recognizing the limitations of disembodied AI has led some researchers to explore the possibility of embodied artificial intelligence. Robotics and sensorimotor learning systems attempt to integrate perception and action within physical environments.

These approaches acknowledge that intelligence may require interaction with the world rather than purely abstract computation. Robots equipped with sensors and mobility can learn through environmental feedback, gradually developing adaptive behaviors.

While such research represents an important step toward more flexible AI systems, replicating the complexity of human embodiment remains a significant challenge. Biological organisms possess highly sophisticated sensory systems, neural architectures, and evolutionary adaptations that enable nuanced interactions with their surroundings.

Nevertheless, the exploration of embodied AI highlights an important philosophical insight: intelligence may be inseparable from the environments in which it develops.

Embodied Intelligence in a Technological Civilization

As artificial intelligence becomes increasingly integrated into modern societies, understanding embodied intelligence becomes more important than ever. Digital technologies shape how individuals perceive information, communicate with others, and interact with the world.

Yet human cognition continues to depend on embodied experience. Perception, movement, and sensory engagement remain essential components of understanding.

The rise of AI therefore does not eliminate the importance of human intelligence. Instead, it emphasizes the need for conscious awareness capable of interpreting technological systems within lived contexts.

Embodied intelligence reminds us that cognition is not simply an abstract computational function. It is an activity embedded in perception, experience, and interaction with the world.

Conclusion

The concept of embodied intelligence reveals a fundamental dimension of human cognition often overlooked in discussions of artificial intelligence. While machines excel at processing data and recognizing patterns, human intelligence arises through the dynamic interaction between mind, body, and environment.

Phenomenology provides a philosophical framework for understanding this relationship by examining the structures of lived experience. Through the work of thinkers such as Merleau-Ponty, phenomenology shows that perception and understanding emerge from embodied engagement with the world.

In the age of artificial intelligence, this perspective becomes increasingly relevant. AI systems may extend human analytical capabilities, but they remain fundamentally different from human cognition, which is grounded in embodied experience.

Within the framework of Conscious Intelligence, embodied intelligence underscores the importance of human awareness in guiding technological systems. By integrating reflection, interpretation, and responsibility, individuals can ensure that artificial intelligence serves constructive purposes within human societies.

Ultimately, understanding intelligence requires acknowledging the role of the body in shaping perception and meaning. Human awareness remains rooted in lived experience, and this experiential foundation continues to guide the evolving relationship between human cognition and artificial intelligence.

References

Dreyfus, H. L. (1992). What computers still can’t do: A critique of artificial reason. MIT Press.

Merleau-Ponty, M. (2012). Phenomenology of perception. Routledge. (Original work published 1945)

Varela, F. J., Thompson, E., & Rosch, E. (1991). The embodied mind: Cognitive science and human experience. MIT Press.



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