Statements (47)
Predicate | Object |
---|---|
gptkbp:instance_of |
gptkb:microprocessor
|
gptkbp:aims_to |
reduce training time for AI models
|
gptkbp:architecture |
custom-built hardware
|
gptkbp:built |
gptkb:Tesla's_Dojo_architecture
meet the demands of AI workloads |
gptkbp:can |
large datasets
|
gptkbp:competes_with |
gptkb:NVIDIA_DGX_systems
|
gptkbp:constructed_in |
deep learning applications
|
gptkbp:designed_by |
Tesla's engineering team
|
gptkbp:designed_for |
autonomous driving systems
|
gptkbp:developed_by |
gptkb:vehicles
gptkb:Tesla,_Inc. cutting-edge technology |
gptkbp:features |
high bandwidth memory
|
gptkbp:has |
high computational power
|
https://www.w3.org/2000/01/rdf-schema#label |
Dojo supercomputer
|
gptkbp:integrates_with |
gptkb:Tesla's_Full_Self-Driving_software
|
gptkbp:is |
a key component in Tesla's AI strategy
|
gptkbp:is_a |
high-performance computing system
|
gptkbp:is_capable_of |
real-time data processing
|
gptkbp:is_designed_for |
high throughput computing
|
gptkbp:is_designed_to |
handle complex simulations
|
gptkbp:is_expected_to |
accelerate AI research
support future AI advancements drive advancements in autonomous systems enhance Tesla's AI capabilities enhance Tesla's competitive edge improve AI training efficiency reduce costs of AI training transform AI training processes |
gptkbp:is_integrated_with |
Tesla's data collection systems
|
gptkbp:is_optimized_for |
video data processing
|
gptkbp:is_part_of |
Tesla's innovation strategy
Tesla's AI ecosystem Tesla's AI research initiatives Tesla's long-term vision for AI |
gptkbp:is_targeted_at |
AI developers
|
gptkbp:is_utilized_by |
Tesla's AI research team
|
gptkbp:location |
Tesla's facilities in Palo Alto, California
|
gptkbp:performance |
exaflop capabilities
|
gptkbp:purpose |
training AI models
|
gptkbp:released_in |
gptkb:2020
|
gptkbp:supports |
neural network training
|
gptkbp:uses |
gptkb:machine_learning
|
gptkbp:utilizes |
massive parallel processing
|
gptkbp:bfsParent |
gptkb:Tesla
|
gptkbp:bfsLayer |
4
|