Dell GB10
Local experimentation, private inference, prototyping and team-scale AI use.
Explore GB10 →Compute for Super Intelligence · private and sovereign AI
AI infrastructure matched to the workload—not the hype.
Super Intelligence depends on real computational foundations. AFA helps organizations evaluate local, on-premises and sovereign AI infrastructure around workload, data sensitivity, model size, users, networking, storage and operating responsibility.
Toronto-based Canadian teamGovernance built into deliveryHuman accountability
AFA terminology
Super Intelligence is the frame. AI remains the technical vocabulary.
Super Intelligence is AFA’s human-centred description of intelligence extended beyond the practical limits of unaided cognition through computation, accumulated knowledge, models, machines and other instruments of intelligence.
We continue to use artificial intelligence (AI) for models, APIs, standards, regulations, procurement categories, vendor products and established search language. The transition is additive, not a denial of the technical field.
Two words matter: AFA’s Super Intelligence is not the same claim as the established one-word term superintelligence, commonly used for an intelligence exceeding human intelligence.
Read AFA’s definition →
Workload-led infrastructure
Start with the work, architecture and operating responsibility.
Problem and workload first. Architecture second. Hardware third. The right infrastructure depends on what must run, where information can live, who needs access, how models behave and what the organization is responsible for maintaining.
01
Define the workloadUsers, data, sensitivity, latency, model size, memory, storage and operating constraints.
02
Architect the environmentModels, identity, networking, storage, security, governance, support and continuity.
03
Select appropriate hardwareChoose workstation, local, departmental or rack-scale compute only after the requirements are clear.
Hardware families
We design around the workload first, then match compute, memory, storage, networking, security and governance to what the organization needs to run locally.
From desk-side private AI to departmental and rack-scale infrastructure.
Dell Precision T4 / T6
GPU workstations for visual, engineering, model and professional workloads.
Explore workstations →GB300
Higher-capacity private AI for demanding organizational workloads.
Explore GB300 →Rack-Scale AI
Private infrastructure for larger teams, governed workloads and AI factories.
Explore AI infrastructure →Workload paths
Choose infrastructure by the work it needs to perform.
Medical Imaging
Radiology, pathology, biomedical imaging and privacy-sensitive visual AI.
Medical imaging compute →Research & Life Sciences
Genomics, biotechnology, research institutes and high-IP R&D.
Research compute →Industrial Vision & NDT
Machine vision, industrial CT, inspection and digital-twin workloads.
Industrial AI →Geospatial & Utilities
LiDAR, point clouds, satellite imagery, remote sensing and critical infrastructure.
Geospatial AI →Regulated Institutions
Government, finance, legal and other organizations where control matters.
Regulated private AI →Physical AI & Industry
Robotics, edge operations, engineering, mining, telecom and visual industry.
Advanced industry AI →Bring us the decision, workload or capability you need to move forward.
We can help determine the right strategy, governance, training, architecture or infrastructure starting point.