Advanced RAG Techniques | Weaviate weaviate.io/blog/advanced-ra…

Making sense of AI’s contradictions: Technology infrastructure | Slalom slalom.com/us/en/insights/ma…

NIST releases Dioptra for testing AI model risk Works on only open source LLMs like Llama, Gemma, Mistral, Falcon. techcrunch.com/2024/07/27/ni…

Is AWS Lambda a Halo Product? architectelevator.com/cloud/…

A data leader’s technical guide to scaling gen AI | Mckinsey mckinsey.com/capabilities/mc…

One year in: Lessons learned in scaling up generative AI for financial services | McKinsey mckinsey.com/industries/fina…

Scaling gen AI in banking: Choosing the best operating model | McKinsey mckinsey.com/industries/fina…

RT @KeneOliobi: "Humans are underrated." - Elon Musk Human-in-the-loop is key to an effective AI/ML strategy. Why Human Intuition Is Esse…

Optimize Generative AI LLMs: Top 20 Hyperparameters You Need to Know | WSaaS wsaas.ai/blog/llm-hyperparam…

Been there, doing that: How corporate and investment banks are tackling gen AI | McKinsey mckinsey.com/industries/fina…

Optimize Generative AI LLMs: Top 20 Hyperparameters You Need to Know #generativeai #llms #hyperparameters #deeplearning #machinelearning keneoliobi.substack.com/p/op…

Knowledge Graph vs. Vector RAG: Benchmarking, Optimization Levers, and a Financial Analysis Example | Neo4j neo4j.com/developer-blog/kno…

A generative AI reset: Rewiring to turn potential into value in 2024 | McKinsey mckinsey.com/capabilities/mc…

Implementing generative AI with speed and safety | McKinsey mckinsey.com/capabilities/ri…

Enhancing the Accuracy of RAG Applications With Knowledge Graphs | Neo4j neo4j.com/developer-blog/enh…

Moving past gen AI's honeymoon phase: Seven hard truths for CIOs to get from pilot to scale | Gartner mckinsey.com/capabilities/mc…

Event-Driven Architecture vs Message-Driven Architecture: Four Differences When designing asynchronous / decoupled / loosely-coupled systems, many of us conflate Event-Driven Architecture with Message-Driven Architecture. events != messages Here are four ways to think about the differences between an Event-Driven Architecture [EDA] and a Message-Driven Architecture [MDA]: 1️⃣ EDA is Noun-Oriented. MDA is Verb-Oriented. • EDA: Notification [Noun] that something happened. E.g., User Visited, Product Added to Cart, Order Placed. Producer is Broadcaster: Consumer chooses what to do with notification, if anything. • MDA: Instruction [Verb] to do something. E.g., Update Inventory, Ship Order, Email Customer. Producer is Director: Consumer must follow instruction. 2️⃣ EDA is Many Consumers. MDA is Single Consumer. • EDA: Many consumers can act on any given event / notification. • MDA: One and only one consumer acts on any given message. 3️⃣ EDA is Dumb-Service-to-Smart Service. MDA is Smart-Service-to-Dumb-Service. • Dumb Service: Zero to minimal business logic. E.g., Log an event [e.g., "User Visited"] without any further processing; Publish an event [e.g., "Order Placed"] to a stream without any knowledge of who will consume it. • Smart Service: Intelligent business logic. E.g., Receive a message "Update Inventory" and perform the necessary inventory update logic; Consume a message "Email Customer" and use customer information and order details to craft and send a personalized email. 4️⃣ EDA publishes to Stream / Topic. MDA publishes to Queue. I'll also add that you can use an event-driven system to implement a message-driven system; but generally not the other way around. So on AWS, for instance, you can implement an event-driven architecture using: • Amazon Managed Streaming for Apache Kafka [MSK] • Amazon Kinesis Data Streams • Amazon EventBridge • Amazon Simple Notification Service [SNS] For a message-driven architecture, I could use any of the above services. Overkill, yes, but possible. You can implement a message-driven architecture on AWS with Amazon Simple Queue Service [SQS]. However, implementing an event-driven architecture on SQS [or attempting to do so] would be an anti-pattern. Hope this helps!

A generative AI reset: Rewiring to turn potential into value in 2024 | McKinsey mckinsey.com/capabilities/mc…

Moving past gen AI’s honeymoon phase: Seven hard truths for CIOs to get from pilot to scale | McKinsey mckinsey.com/capabilities/mc…

Navigating the Generative AI Landscape: A Strategic Blueprint for CEOs and CIOs | AWS aws.amazon.com/blogs/enterpr…