Real-Time Multimodal AI

Build sub-second voice, vision, and video pipelines

Build real-time multimodal AI systems — from CLIP embeddings to voice assistants under 200ms latency, edge deployment with ONNX/TensorRT, and graceful degradation patterns.

13 levels
1
Multimodal LandscapeSpeed Quiz

Map the VLM ecosystem — know which model fits which job

+100 XP
2
CLIP Deep DiveConcept Matcher

Match contrastive learning variants to their strengths

+100 XP
3
Whisper MasteryParameter Tuner

Configure a production streaming speech-to-text pipeline

+100 XP
4
Streaming ProtocolsSpeed Quiz

Pick the right transport for every real-time AI use case

+100 XP
5
Voice Assistant ArchitecturePipeline Builder

Build the correct real-time voice AI pipeline in order

+100 XP
6
Edge DeploymentCost Optimizer

Optimize vision model deployment cost across cloud vs edge vs browser

+100 XP
7
Real-Time Video AnalysisPipeline Builder

Build the correct camera-to-insight inference pipeline

+100 XP
8
GPU MultiplexingSpeed Quiz

Match GPU sharing strategies to the right production scenario

+100 XP
9
Graceful DegradationDiagnosis Lab

Diagnose a cascading production failure in a live voice assistant

+100 XP
10
Multimodal Interview GauntletSpeed Quiz

20 expert-level multimodal AI questions — score 80% to advance

+200 XP
11
CAPSTONE: Systems ThinkingSpeed Quiz

Design complete AI systems under real constraints — whiteboard style

+200 XP
12
CAPSTONE: Portfolio DifferentiatorsDiagnosis Lab

Identify what actually makes an AI engineer portfolio stand out

+200 XP
13
CAPSTONE: System Design InterviewSpeed Quiz

Final challenge — whiteboard-style questions testing all 5 chapters

+200 XP