Equipment Effectiveness (OEE). Energy companies must balance EV charger loads and manage grid performance in real time. Banks need to analyze audit logs from their website and application in real time frauds. Logistics companies need real-time tracking and historical analysis of shipments, fleet performance, and warehouse operations to optimize delivery times, reduce costs, and improve supply chain efficiency Technology platforms require real-time monitoring and analytics to personalize experiences and ensure performance. 32. The Interconnection of Analytics, Search, and AI Analytics, search, and AI are deeply interconnected

User + Usage + CapEx Growth = Unprecedented • AI Model Compute Costs High / Rising + Inference Costs Per Token Falling = Performance Converging + Developer Usage Rising • AI Usage + Cost + Loss Growth Page 293 USA – LLM #1 China USA – LLM #2 AI Model Compute Costs High / Rising + Inference Costs Per Token Falling = Performance Converging + Developer Usage Rising 3 Cost of Key Technologies Relative competitive. Breakthroughs in large models, cost-per-token declines, open-source proliferation and chip performance improvements are making new tech advances increasingly more powerful, accessible, and economically

. . . . . . . 374 30 Embedding Julia 377 30.1 High-Level Embedding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 377 30.2 High-Level Embedding on Windows with Visual Studio . . with backtrace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 414 34 Performance Tips 416 34.1 Performance critical code should be inside a function . . . . . . . . . . . . . . . . . 416 untyped global variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 416 34.3 Measure performance with @time and pay attention to memory allocation . . . . . . 417 34.4 Tools . . . . . . . .

. . . . . . . 374 30 Embedding Julia 377 30.1 High-Level Embedding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 377 30.2 High-Level Embedding on Windows with Visual Studio . . with backtrace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 414 34 Performance Tips 416 34.1 Performance critical code should be inside a function . . . . . . . . . . . . . . . . . 416 untyped global variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 416 34.3 Measure performance with @time and pay attention to memory allocation . . . . . . 417 34.4 Tools . . . . . . . .

. . . . . . . 398 31 Embedding Julia 400 31.1 High-Level Embedding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 400 31.2 High-Level Embedding on Windows with Visual Studio . . with backtrace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 441 35 Performance Tips 444 35.1 Performance critical code should be inside a function . . . . . . . . . . . . . . . . . 444 untyped global variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 444 35.3 Measure performance with @time and pay attention to memory allocation . . . . . . 445 35.4 Tools . . . . . . . .

. . . . . . . 398 31 Embedding Julia 400 31.1 High-Level Embedding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 400 31.2 High-Level Embedding on Windows with Visual Studio . . with backtrace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 441 35 Performance Tips 444 35.1 Performance critical code should be inside a function . . . . . . . . . . . . . . . . . 444 untyped global variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 444 35.3 Measure performance with @time and pay attention to memory allocation . . . . . . 445 35.4 Tools . . . . . . . .

. . . . . . . 398 31 Embedding Julia 400 31.1 High-Level Embedding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 400 31.2 High-Level Embedding on Windows with Visual Studio . . with backtrace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 441 35 Performance Tips 444 35.1 Performance critical code should be inside a function . . . . . . . . . . . . . . . . . 444 untyped global variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 444 35.3 Measure performance with @time and pay attention to memory allocation . . . . . . 445 35.4 Tools . . . . . . . .

. . . . . . . 402 31 Embedding Julia 404 31.1 High-Level Embedding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 404 31.2 High-Level Embedding on Windows with Visual Studio . . Comparison with backtrace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 451 35 Performance Tips 454 35.1 Table of contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1182 51.4 Implementation notes and performance . . . . . . . . . . . . . . . . . . . . . . . . 1185 51.5 Design inspiration . . . . . . . .

. . . . . . . 403 31 Embedding Julia 405 31.1 High-Level Embedding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 405 31.2 High-Level Embedding on Windows with Visual Studio . . Comparison with backtrace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 452 35 Performance Tips 455 35.1 Table of contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1180 51.4 Implementation notes and performance . . . . . . . . . . . . . . . . . . . . . . . . 1183 51.5 Design inspiration . . . . . . . .

. . . . . . . 402 31 Embedding Julia 404 31.1 High-Level Embedding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 404 31.2 High-Level Embedding on Windows with Visual Studio . . Comparison with backtrace . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 451 35 Performance Tips 454 35.1 Table of contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1179 51.4 Implementation notes and performance . . . . . . . . . . . . . . . . . . . . . . . . 1182 51.5 Design inspiration . . . . . . . .