Apple Neural Engine
E38961
Apple Neural Engine is Apple’s dedicated on-chip hardware accelerator designed to efficiently perform machine learning and AI computations on its devices.
All labels observed (3)
| Label | Occurrences |
|---|---|
| Apple Neural Engine canonical | 8 |
| Neural Engine | 8 |
| 16-core Apple Neural Engine | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T300072 — 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.
Target entity: Apple Neural Engine Context triple: [Apple M1, neuralEngineType, Apple Neural Engine]
-
A.
Apple M1
Apple M1 is Apple’s first in-house ARM-based system-on-a-chip for Macs, known for its high performance and power efficiency compared to previous Intel-based processors.
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B.
Apple M2
Apple M2 is a second-generation ARM-based system-on-a-chip designed by Apple that delivers improved performance and efficiency for modern Mac computers and iPads.
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C.
Apple silicon
Apple silicon is Apple’s custom family of ARM-based system-on-a-chip processors that power modern Macs and other Apple devices, offering high performance with improved energy efficiency.
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D.
Apple M3
Apple M3 is a generation of Apple-designed ARM-based system-on-a-chip processors that power newer Mac computers, offering improved performance and energy efficiency over its predecessors.
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E.
iPhone
The iPhone is Apple's flagship smartphone line that revolutionized mobile technology by combining a touchscreen interface, internet connectivity, and a robust app ecosystem into a single device.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Target entity: Apple Neural Engine Target entity description: Apple Neural Engine is Apple’s dedicated on-chip hardware accelerator designed to efficiently perform machine learning and AI computations on its devices.
-
A.
Apple M1
Apple M1 is Apple’s first in-house ARM-based system-on-a-chip for Macs, known for its high performance and power efficiency compared to previous Intel-based processors.
-
B.
Apple M2
Apple M2 is a second-generation ARM-based system-on-a-chip designed by Apple that delivers improved performance and efficiency for modern Mac computers and iPads.
-
C.
Apple silicon
Apple silicon is Apple’s custom family of ARM-based system-on-a-chip processors that power modern Macs and other Apple devices, offering high performance with improved energy efficiency.
-
D.
Apple M3
Apple M3 is a generation of Apple-designed ARM-based system-on-a-chip processors that power newer Mac computers, offering improved performance and energy efficiency over its predecessors.
-
E.
iPhone
The iPhone is Apple's flagship smartphone line that revolutionized mobile technology by combining a touchscreen interface, internet connectivity, and a robust app ecosystem into a single device.
- F. None of above. chosen
Statements (53)
| Predicate | Object |
|---|---|
| instanceOf |
hardware accelerator
ⓘ
neural processing unit ⓘ |
| alsoKnownAs | ANE ⓘ |
| architectureType | parallel processing architecture ⓘ |
| designedFor |
artificial intelligence computations
ⓘ
machine learning workloads ⓘ on-device inference ⓘ |
| developer | Apple Inc. ⓘ |
| enables | on-device privacy-preserving ML ⓘ |
| evolvesWith | each new Apple SoC generation ⓘ |
| firstReleaseYear | 2017 ⓘ |
| hasCapability | multiple TOPS throughput (tera operations per second) ⓘ |
| includedInChipFamily |
Apple A-series
ⓘ
Apple M-series ⓘ Apple S-series ⓘ Apple T-series ⓘ |
| integratedWith |
Apple CPU cores
ⓘ
Apple GPU ⓘ |
| introducedInProduct |
iPhone
ⓘ
surface form:
iPhone 8
iPhone ⓘ
surface form:
iPhone X
|
| introducedWithChip | Apple A11 Bionic ⓘ |
| optimizationGoal |
energy efficiency
ⓘ
high performance ⓘ low power consumption ⓘ |
| partOf | Apple system on a chip ⓘ |
| performs |
convolution operations
ⓘ
matrix multiplications ⓘ neural network inference ⓘ |
| programmedVia |
Core ML
ⓘ
surface form:
Core ML API
Metal graphics API ⓘ
surface form:
Metal Performance Shaders
|
| supports |
Face ID
ⓘ
surface form:
Animoji
Core ML ⓘ Face ID ⓘ augmented reality workloads ⓘ camera computational photography ⓘ image recognition ⓘ natural language processing ⓘ on-device Siri processing ⓘ speech recognition ⓘ |
| targetPlatform |
iOS
ⓘ
iPadOS ⓘ macOS ⓘ tvOS ⓘ visionOS ⓘ watchOS ⓘ |
| usedBy |
third-party iOS apps
ⓘ
third-party macOS apps ⓘ |
| usedIn |
Apple TV
ⓘ
Vision Pro ⓘ
surface form:
Apple Vision Pro
Apple Watch ⓘ Mac ⓘ iPad ⓘ iPhone ⓘ |
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.
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.
Subject: Apple Neural Engine Description of subject: Apple Neural Engine is Apple’s dedicated on-chip hardware accelerator designed to efficiently perform machine learning and AI computations on its devices.
Referenced by (17)
Full triples — surface form annotated when it differs from this entity's canonical label.