Fri.Nov 17, 2023

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Sam Altman fired as CEO of OpenAI

Analytics Vidhya

In a surprising turn of events, OpenAI, the leading artificial intelligence research lab, has announced the termination of its co-founder and CEO, Sam Altman. This unexpected decision, announced on November 17, 2023, has sent ripples through the tech industry, raising questions about the future of the organization and its AI research. Chief technology officer Mira […] The post Sam Altman fired as CEO of OpenAI appeared first on Analytics Vidhya.

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IHG maximizes hospitality with multicloud

CIO Business Intelligence

For IHG Hotels and Resorts, the cloud provides just the right accommodation for business success. “First and foremost we see our journey to the cloud as the most extremely important part of both our technology and commercial strategies,” says George Turner, chief commercial and technology officer of the British multinational, which relies heavily on its sophisticated cloud infrastructure, chatbots, and AI to drive more digital business at its 19 hotel brands — more so at the edge.

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Microsoft Unveils first AI chip: Maia 100 Chip and Cobalt CPU

Analytics Vidhya

In a groundbreaking move at the annual Ignite conference, Microsoft unveiled the highly anticipated Maia 100 chip and Cobalt CPU. This strategic initiative aims to seize control of technology, establishing dominance in the fiercely competitive AI computing market. CEO Satya Nadella outlined ambitious plans to harness the power of these innovative chips.

Marketing 319
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What is a managed service provider? Strategic outsourcing for IT services

CIO Business Intelligence

What is a managed service provider? A managed service provider (MSP) is an outsourcer contracted to remotely manage or deliver IT services such as network, application, infrastructure, or security management to a client company by assuming full responsibility for those services, determining proactively what technologies and services are needed to fulfill the client’s needs.

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15 Modern Use Cases for Enterprise Business Intelligence

Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

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A Deep Dive into Model Quantization for Large-Scale Deployment

Analytics Vidhya

Introduction In AI, two distinct challenges have surfaced: deploying large models in cloud environments, incurring formidable compute costs that impede scalability and profitability, and accommodating resource-constrained edge devices struggling to support complex models. The common thread among these challenges is the imperative to shrink model size without compromising accuracy.

Modeling 316
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Speed up queries with the cost-based optimizer in Amazon Athena

AWS Big Data

Amazon Athena is a serverless, interactive analytics service built on open source frameworks, supporting open table file formats. Athena provides a simplified, flexible way to analyze petabytes of data where it lives. You can analyze data or build applications from an Amazon Simple Storage Service (Amazon S3) data lake and 30 data sources, including on-premises data sources or other cloud systems using SQL or Python.

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The 5 Best Vector Databases You Must Try in 2024

KDnuggets

The top vector databases are known for their versatility, performance, scalability, consistency, and efficient algorithms in storing, indexing, and querying vector embeddings for AI applications.

Modeling 118
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Unlocking the Future of AI with Jepson Taylor

Analytics Vidhya

In this episode of Leading With Data, we interacted with Jepson Taylor, Co-lead AI Masterclass at NYU and ex-chief AI Strategist at Dataiku. Unfolding the future of AI, Taylor shares invaluable insights into the pivotal moments of his journey – from chemical engineering to AI entrepreneurship, a successful startup acquisition, and the rise of generative […] The post Unlocking the Future of AI with Jepson Taylor appeared first on Analytics Vidhya.

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Use custom domain names with Amazon Redshift

AWS Big Data

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. With Amazon Redshift, you can analyze all your data to derive holistic insights about your business and your customers. Amazon Redshift now supports custom URLs or custom domain names for your data warehouse. You might want to use a custom domain name or CNAME (Canonical Name) for the following reasons: A custom domain name is straightforward to recall and use.

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A Microsoft Engineer’s Guide to AI Innovation and Leadership

KDnuggets

Dive into the insights of AI innovation with Microsoft's Senior Software Engineer, Manas Joshi: A journey of technology, triumph, and teachings for the next generation.

Software 101
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8 Steps to Transformation at Speed & Scale – Your Guide to Deploying StratOps

📌Is your Data & AI transformation struggling to really impact the business? Discover the game-changing StratOps approach that: Bridges the Gap : Connect your Data & AI strategy to your operating model, to ensure alignment at every level. Prioritizes Outcomes : Focuses on concrete business outcomes from day one, rather than capabilities in isolation.

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Implement data warehousing solution using dbt on Amazon Redshift

AWS Big Data

Amazon Redshift is a cloud data warehousing service that provides high-performance analytical processing based on a massively parallel processing (MPP) architecture. Building and maintaining data pipelines is a common challenge for all enterprises. Managing the SQL files, integrating cross-team work, incorporating all software engineering principles, and importing external utilities can be a time-consuming task that requires complex design and lots of preparation. dbt (DataBuildTool) offers this

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Retrieval Augmented Generation (In Plain English!)

Dataiku

In the ever-evolving realm of AI, a groundbreaking technique known as Retrieval Augmented Generation (RAG) is making waves. But what exactly is RAG and why should enterprises be excited about its potential? In the latest installment of our “In Plain English” blog series, we’ll cover the basics of RAG and how it works, as well as provide insights on why it’s a game changer.

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Visualize Amazon DynamoDB insights in Amazon QuickSight using the Amazon Athena DynamoDB connector and AWS Glue

AWS Big Data

Amazon DynamoDB is a fully managed, serverless, key-value NoSQL database designed to run high-performance applications at any scale. DynamoDB offers built-in security, continuous backups, automated multi-Region replication, in-memory caching, and data import and export tools. The scalability and flexible data schema of DynamoDB make it well-suited for a variety of use cases.