Event-Driven Architectures (EDA) and the Actor Model both provide patterns for asynchronous, distributed computing. The EDA communicates through events, pieces of data that signify a state change, propagating them as messages to interested consumers. The Actor Model utilizes individual acting entities, or actors, each with its mailbox and behavior, processing incoming messages asynchronously.

In EDA, several styles exist, including event sourcing, Commands Query Responsibility Segregation (CQRS), and event-carried state transfer. Event sourcing concerns capturing all changes as events, offering strong audit trails and temporal queries. CQRS divides an application into command and query models, reducing contention and complexity. Event-carried state transfer involves sharing state updates via events reducing service dependency.

The Actor Model is an architectural model for concurrent computation in distributed systems, with actors being the universal primitives. Actors encapsulate state and behavior, communicate through asynchronous messaging, and dynamically create other actors. They provide high-level abstractions for distributed and concurrent computation.

EDA and Actor Model both cater to the increasing demand for high-concurrency, distributed systems. They can handle high volumes of data changes and operations, allowing robust, flexible, and scalable applications. However, they require careful design to manage consistency and fault tolerance effectively. They don't naturally provide the ACID guarantees common to traditional relational database operations.

Moreover, implementing EDA and Actor Model entails a shift in thinking - strong emphasis on message passing, state encapsulation, and asynchronicity. They are powerful, but they may not be suitable for all types of applications. It's vital to evaluate fit and ROI based on specific needs.

Thoughtful implementation of EDA might lead to systems that can respond in real time to information updates, learning from them and dynamically adjusting their operation. In a wider perspective, this could pave the way for more adaptive, intelligent systems, impacting human destiny. Yet, this also highlights the increasing dependency on digital systems and their reliability.

EDA in Clojure can be implemented using libraries like `core.async` for asynchronous communication. The Actor Model can be created with `pulsar`.

(ns eda-example (:require [clojure.core.async :as async]))

(defchannel updates)

;; Producer (async/go-loop [] (async/>! updates (generate-update)) (async/<! (async/timeout 1000)) (recur))

;; Consumer (async/go-loop [] (let [update (async/<! updates)] (process-update update)) (recur))

1. What are the primary trade-offs in selecting an event-driven architecture versus a more traditional, request-response model?
2. Given a system with a mix of fast and slow consumers, how might an event-driven architecture be designed to prevent slow consumers from becoming a bottleneck?
3. How does the Actor Model handle failures and ensure message delivery in a distributed environment?

• Event-Driven Architectures, Microsoft Azure
• Event-Driven Architectures, Google Cloud
• Google Cloud Solutions - Event-Driven Architecture with Pub/Sub
• Distributed Publish-Subscribe in Akka
• Actor Model, Wikipedia