Remove Algorithm Remove Analysis Remove Due Diligence
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Four challenges with ERP vendor-led AI roadmaps and how to solve them

CIO

Challenge 2: Leaving on-premises data behind For AI algorithms to be successful, they need a massive amount of historical data to draw from. Remember the garbage in, garbage out adage: The more clean data available to an AI algorithm, the more predictive and fine-tuned the results will be.

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DTN’s CTO on combining IT systems after a merger

CIO

Given the investment in time and money necessary to merge two companies’ IT systems, “it’s worthwhile spending an extra few weeks up-front to make a more thorough analysis of which solution or which pieces of which solutions should come together,” Ewe says. At DTN, says Ewe, “We have a sophisticated due-diligence checklist for technology.

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Testing New AI Applications is Crucial Before Bringing them to Market

Smart Data Collective

Creating a new software application with complex AI algorithms is a very time and resource-intensive process. You are going to need to do your due diligence and make sure that you get it right. However, bringing a software application with malfunctioning AI algorithms to market would be a much more serious and costlier problem.

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New DoE Program Drives Demand For Machine Learning Programmers

Smart Data Collective

The head of the Department of Energy announced that they will be investing $30 million in artificial intelligence and machine learning algorithms. However, the detailed findings of intelligent asset performance analysis allow financers to minimize risks and maximize expected returns,” the company reports.

Learning 351
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Venture Capital in the Age of AI: Transforming Due Diligence

Alpha Sense BI

On the AlphaSense platform, this reality rings true as we noticed an over 50% increase in documents mentioning “due diligence” over the past year. Once an arduous and time-consuming task, the dawn of artificial intelligence (AI) and generative AI (genAI) has transformed the way venture capital investors conduct due diligence.

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What is the Cost of Hiring Data Savvy Software Developers?

Smart Data Collective

These software programs are strongly dependent on new algorithms that incorporate data science capabilities. Many of them are experienced with data science projects, but you have to do your due diligence and review previous projects carefully. The majority of offshore projects go bankrupt due to: 1.

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The Evolution of AI in Asset Management

Alpha Sense BI

AI enables analysts to uncover opportunities even amidst volatility, operate with higher agility, perform data analysis at scale, and assess risk more accurately. Sentiment Analysis : AI tools using Natural Language Processing (NLP) to extract sentiment from documents allow you to assess more nuanced meaning behind text.