Remove 2022 Remove Data Collection Remove Experimentation Remove Modeling
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It’s a new dawn of AI-powered knowledge management

CIO Business Intelligence

Data exists in ever larger silos, but real knowledge still resides in employees. But the rise of large language models (LLMs) is starting to make true knowledge management (KM) a reality. These models can extract meaning from digital data at scale and speed beyond the capabilities of human analysts.

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Accelerating scope 3 emissions accounting: LLMs to the rescue

IBM Big Data Hub

This article explores an innovative way to streamline the estimation of Scope 3 GHG emissions leveraging AI and Large Language Models (LLMs) to help categorize financial transaction data to align with spend-based emissions factors. Figure 1 illustrates the framework for Scope 3 emission estimation employing a large language model.

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Digital listening reveals 3 leading innovation drivers

CIO Business Intelligence

It surpasses blockchain and metaverse projects, which are viewed as experimental or in the pilot stage, especially by established enterprises. Top Technologies Mentioned in Innovation Conversations Tweets from Verified Accounts, January 2021 – December 2022 Opportunities abound for innovating with AI. higher [in 2022] than in 2017.”

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Reimagining technology for the next generation

CIO Business Intelligence

These new, digitally enhanced worlds, realities, and business models are poised to revolutionize both life and enterprise in the next decade, as explored in Accenture’s recent Technology Vision 2022 report. Here are five implications these technologies will have on security and privacy as we build our collective future. .

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Frugal AI: Value at Scale Without Breaking the Bank

Dataiku

It’s no secret that training AI models is an energy-intensive and large dataset-dependent endeavor and, to corroborate this, researchers at the University of Massachusetts Amherst performed a lifecycle assessment on large, widely accepted AI models trained on the vast datasets needed to achieve accuracy. Today, in 2022, the code (i.e.,

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Backtesting index rebalancing arbitrage with Amazon EMR and Apache Iceberg

AWS Big Data

Testing scope For our testing purposes, consider the following example , in which a change to the S&P Dow Jones Indices is announced on September 2, 2022, becomes effective on September 19, 2022, and doesn’t become observable in the ETF holdings data that we will be using in the experiment until September 30, 2022.