Optimizing AI Efficiency: Effective Use of Data via Qymatix Cloud Connector
As businesses increasingly leverage artificial intelligence (AI) to streamline operations, optimize decision-making, and gain insights, the role of data as the lifeblood of AI has become indisputable. Data acts as the foundation upon which AI models are built, providing the raw materials necessary for AI to learn, adapt, and evolve.
However, manually handling and extracting data for AI can be time-consuming, costly, and fraught with errors. This is where the Qymatix cloud connector comes into play.
What are Algorithms - Easily Explained
Algorithms - the word gets tossed around today for everything from your basic Instagram feed recommendations to complex interfaces like ChatGPT. But what are algorithms? Are they just for computers? How do they help you?
In today’s article, we’ll explain what algorithms are and give some examples of how you can benefit from this ubiquitous but often-misunderstood technology.
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How to Set More-Realistic Sales Targets using Historical Data
How to set more-realistic sales targets using historical data and Predictive Analytics.
To replace the legendary Jack Welch as CEO, the General Electric (GE) Board had selected Jeffrey Immelt in November 2000. As he took the reins, Immelt set an ambitious sales target: “We believe that GE can grow two to three times faster than world gross domestic product, which translates to about 8 per cent sustained sales growth.”
To give you some perspective, the industrial segment of GE had grown 4 per cent historically.
Likewise, on December 4, 2003, Rockwell Automation announced that its board of directors had elected Keith Nosbusch as president and chief executive officer.
How can AI help with labour shortage in B2B wholesale and manufacturing?
The importance of predictive sales software to address the skills shortage in Germany's specialist wholesale sector.
The shortage of skilled workers in Germany has reached alarming proportions and is particularly affecting the specialist wholesale trade. Sales managers and directors of specialist wholesalers in Germany are under great pressure as they face an acute shortage of skilled workers.
Predictive Analytics vs Prescriptive Analytics
With so many types of data analytics and analytical methods out there, many people are curious about the relationship between predictive analytics vs prescriptive analytics.
Today, we’ll review all four types of analytics and delve into predictive and prescriptive analytics to help you understand when and how to use both.
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What artificial intelligence can and can´t do
For years, artificial intelligence has fluctuated between the terms "Terminator", "technology of the future", or "new superpower", and "doesn't work", "is disappointing", or "no confidence".
It is not surprising that there have repeatedly been so-called "AI summers" and "AI winters" over 70 years. More specifically, there have been two AI winters since the 1950s, when AI was being researched and developed: In the early 1970s and late 1980s, the high expectations for the technology were dashed. Investors pulled out, and researchers got less funding.
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Explainable, Responsible and Trustworthy Artificial Intelligence – What is behind?
Since June 2023, the "AI Act" has been taking shape. With the AI Regulation, the EU Parliament is for the first time planning a legal framework for the development and use of artificial intelligence (AI) - also known as the "AI Act":
“The European AI strategy aims to make the EU a world-class hub for AI and ensure that AI is human-centric and trustworthy.” - European Comission.
How Artificial Intelligence improves Sales Forecasting
Creating and using AI sales forecasts is essential for any B2B company. It is also one of the most important tasks for sales managers who use sales forecasts for sales planning and strategy.
There are many ways to create sales forecasts. From sales rep surveys and estimates of future sales to rule-based Excel calculations or business intelligence applications. But the most unbeatable predictions use artificial intelligence. This article discusses why this is the case.
Roughly speaking, sales forecasts help companies gain some planning certainty in an uncertain future. The goal is to allocate resources efficiently, save money and costs and increase sales.
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Deep Learning vs Machine Learning
Even before the advent of deep learning, we’ve been creating smarter processors that can help us do complex tasks like IBM Watson.
But now that machine learning has been divided into subsets, many of these terms get confused or conflated. Take deep learning vs machine learning; one is a part of the other, but often is thrown about interchangeably.
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How to Predict Customer Churn in B2B with AI
For businesses selling ad-hoc, it's hard for companies to predict customer churn. That is in contrast to as-a-Service subscription-based businesses for whom identifying at-risk customers is more accessible right from the initial sign-up.
SaaS businesses benefit from constantly updated, deep, live client usage statistics in the free trial and beyond when they become subscribers. They build AI-based churn prediction models on historical data tracking how often clients log in and what features they use.
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