Apple M8 motion coprocessor
E494389
The Apple M8 motion coprocessor is a low-power chip used in certain Apple devices to continuously track motion and sensor data, enabling fitness, navigation, and context-aware features without heavily draining the main processor’s battery.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Apple M8 motion coprocessor canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T5100847 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Apple M8 motion coprocessor Context triple: [Apple Special Event September 2014, announcedChip, Apple M8 motion coprocessor]
-
A.
Apple A11 Bionic
Apple A11 Bionic is a 64-bit ARM-based system-on-a-chip designed by Apple for iPhones, notable for significantly boosting performance and efficiency while enabling advanced machine learning and augmented reality features.
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B.
Apple Neural Engine
Apple Neural Engine is Apple’s dedicated on-chip hardware accelerator designed to efficiently perform machine learning and AI computations on its devices.
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C.
CoreMotion
CoreMotion is an Apple framework that provides access to motion and fitness data from device sensors such as accelerometers and gyroscopes.
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D.
Apple A-series
Apple A-series is a line of custom ARM-based system-on-chip processors designed by Apple to power its mobile devices with high performance and energy efficiency.
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E.
Apple W1
The Apple W1 is a custom wireless audio chip designed by Apple to provide efficient Bluetooth connectivity, seamless pairing, and improved battery performance in compatible devices like AirPods and certain Beats headphones.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Apple M8 motion coprocessor Target entity description: The Apple M8 motion coprocessor is a low-power chip used in certain Apple devices to continuously track motion and sensor data, enabling fitness, navigation, and context-aware features without heavily draining the main processor’s battery.
-
A.
Apple A11 Bionic
Apple A11 Bionic is a 64-bit ARM-based system-on-a-chip designed by Apple for iPhones, notable for significantly boosting performance and efficiency while enabling advanced machine learning and augmented reality features.
-
B.
Apple Neural Engine
Apple Neural Engine is Apple’s dedicated on-chip hardware accelerator designed to efficiently perform machine learning and AI computations on its devices.
-
C.
CoreMotion
CoreMotion is an Apple framework that provides access to motion and fitness data from device sensors such as accelerometers and gyroscopes.
-
D.
Apple A-series
Apple A-series is a line of custom ARM-based system-on-chip processors designed by Apple to power its mobile devices with high performance and energy efficiency.
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E.
Apple W1
The Apple W1 is a custom wireless audio chip designed by Apple to provide efficient Bluetooth connectivity, seamless pairing, and improved battery performance in compatible devices like AirPods and certain Beats headphones.
- F. None of above. chosen
Statements (45)
| Predicate | Object |
|---|---|
| instanceOf |
Apple coprocessor
ⓘ
motion coprocessor ⓘ |
| alsoKnownAs | Apple M8 NERFINISHED ⓘ |
| announcedWith | iPhone 6 NERFINISHED ⓘ |
| announcementDate | September 2014 ⓘ |
| architectureRole | dedicated sensor hub ⓘ |
| dataTypeProcessed |
environmental sensor data
ⓘ
motion data ⓘ |
| designedBy | Apple Inc. NERFINISHED ⓘ |
| designedFor | low-power operation ⓘ |
| enablesFeature |
activity recognition
ⓘ
background motion logging ⓘ distance estimation ⓘ elevation tracking ⓘ step counting ⓘ |
| function |
continuous motion tracking
ⓘ
sensor data processing ⓘ |
| generation | second-generation Apple motion coprocessor ⓘ |
| integratedWith | Apple A8 system-on-chip NERFINISHED ⓘ |
| manufacturer | Apple Inc. ⓘ |
| marketedAs | M8 motion coprocessor NERFINISHED ⓘ |
| offloadsWorkFrom | main CPU ⓘ |
| powerCharacteristic | ultra-low power ⓘ |
| predecessor | Apple M7 motion coprocessor NERFINISHED ⓘ |
| purpose |
enable context-aware features
ⓘ
enable fitness tracking features ⓘ enable navigation features ⓘ reduce power consumption of main processor ⓘ |
| successor | Apple M9 motion coprocessor NERFINISHED ⓘ |
| supports |
Health and fitness applications
ⓘ
location-based services ⓘ |
| tracksSensor |
accelerometer
ⓘ
barometer ⓘ compass ⓘ gyroscope ⓘ |
| usedFor |
context awareness
ⓘ
fitness tracking ⓘ navigation ⓘ |
| usedInDevice |
iPad Air 2
NERFINISHED
ⓘ
iPad mini 4 NERFINISHED ⓘ iPhone 6 NERFINISHED ⓘ iPhone 6 Plus NERFINISHED ⓘ iPod touch (6th generation) NERFINISHED ⓘ |
| usedInSoC |
Apple A8
NERFINISHED
ⓘ
Apple A8X NERFINISHED ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Apple M8 motion coprocessor Description of subject: The Apple M8 motion coprocessor is a low-power chip used in certain Apple devices to continuously track motion and sensor data, enabling fitness, navigation, and context-aware features without heavily draining the main processor’s battery.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.