Bi Fast Track Overview

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This document outlines B.I. Fast Track engagements which provide accelerated business intelligence roadmaps and previews using Microsoft 2010 BI Stack technologies. It describes the roles, responsibilities, and deliverables for two types of Fast Track engagements - Fast Track I provides a basic low-risk preview using customer data, while Fast Track II expands on this with additional dimensions, reports, and data mining samples. Both engagements follow schedules to design and build mini data marts, cubes, reports and dashboards over 1-2 weeks to demonstrate BI value for projects in early phases.

Technology

B.I. Fast Tracksm Providing Accelerated Business Intelligence Roadmaps & Previews

To Provide MSFT BI customers with low-risk previews of the stack’s end-to-end value using their own datasets

To Provide Deliverables that Kick-Start the preview’s real-world project counterpart

To Prove B.I. Voyage’s Expert CompetencyHow? ,[object Object]

Mini Solutions Developed using your data sets

Deliverables are good for previews but are not enterprise-ready solutions,[object Object]

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Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process. In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds. - These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.

GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...

Neo4j

Leonard Jayamohan, Partner & Generative AI Lead, Deloitte This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.

GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...

Neo4j

Dr. Sean Tan, Head of Data Science, Changi Airport Group Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.

Infrastructure Challenges in Scaling RAG with Custom AI models

Zilliz

Building Retrieval-Augmented Generation (RAG) systems with open-source and custom AI models is a complex task. This talk explores the challenges in productionizing RAG systems, including retrieval performance, response synthesis, and evaluation. We’ll discuss how to leverage open-source models like text embeddings, language models, and custom fine-tuned models to enhance RAG performance. Additionally, we’ll cover how BentoML can help orchestrate and scale these AI components efficiently, ensuring seamless deployment and management of RAG systems in the cloud.

Mariano G Tinti - Decoding SpaceX

Mariano Tinti

“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...

Edge AI and Vision Alliance

For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/ Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit. In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing. van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.

Building Production Ready Search Pipelines with Spark and Milvus

Zilliz

20240605 QFM017 Machine Intelligence Reading List May 2024

Matthew Sinclair

AI 101: An Introduction to the Basics and Impact of Artificial Intelligence

IndexBug