AI

When the audience doesn’t get your message, why not “send the text to Hollywood”… An idea almost as old as engineering itself. Even in the past, movie components boosted transparency and accelerated the mass adoption of new technologies, or logic, that had seemed too black-box before.

Architects and many others remember the tightrope walk between flexibility/performance and testability/predictability/V&V in systems with many run-time parameters, or parallelism, or late binding time ranging from polymorphism to SOA-UDDI and ad-hoc computing. Now, it’s leveled up by ML (machine learning).

Developers, more often than architects, tend to get frustrated by declarative programming, because it boosts expressive power at the cost of less testability.

I mars gjorde tillämpad AI stora rubriker igen. Den här gången var det machine learning (ML) med neurala nät i poker, Deep Stack.

Applied AI got its second wind from big data, Internet of Things (IoT), and adaptive Content Delivery Networks (CDN). Ever since compilers moved from rocket science “AI” to everyday life, each AI wave heightens the crossbar of automation toward more complex tasks.