Leveraging Big Data: Important Data AI Researcher Should Track

AI + Big Data

Big Data appeared before everyone even realized its existence, and so far, it is the core element of modern technologies. This article will explain the intersection where big data meets AI as well as the key elements of their inseparable connection and the prospects for the further development of AI by using big data.

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AI Data Set creation, labeling and verification, and its importance for Machine Learning & Artificial Intelligence (AI)

AI Data Set creation

Data scientists continue to work tirelessly to try and replicate human intelligence through the algorithms they create.
Neural networks are systems with autonomous or intelligent behavior. They are able to perform tasks and solve problems independently (so-called artificial intelligence / AI). Before that, the neural algorithms have to be trained using sample data. AI systems learn from these data and can generalize them and apply what has been learned to new tasks.
The more accurate and extensive the amount of AI training data is, the better the first results of AI systems are.

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Artificial intelligence in medicine

Artificial intelligence + medicine

Big Data as the basis for reliable diagnoses, machine learning to select the best treatment, AI systems for accelerated drug development – The importance of artificial intelligence is also growing in the field of medicine. What is the potential of self-learning algorithms in the healthcare sector?

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Does Artificial Intelligence Optimize Human Beings?

Künstliche Intelligenz

The concept of the perfect human is as old as humanity itself. But self-learning algorithms are bringing the realization of this idea a little closer now, just as they entail the fear of the omnipotence of machines. Does artificial intelligence make us smarter, better looking, healthier and happier? Four questions and four answers.

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Does Artificial Intelligence benefit the Common Good?

Artificial Intelligence + Common Good

The invention of the steam engine triggered revolutionary societal changes. Machines replaced physical work. They produced goods cheaper, faster and more effectively. In the end everyone profited from that through more prosperity. A similar development is becoming apparent today: in many areas artificial intelligence is replacing processes which require human thinking. Will we also all benefit from this?

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Choosing the right AI model

AI Model

The popularity of AI (Artificial Intelligence) systems is growing in leaps and bounds. Businesses around the world are starting to understand how these systems can benefit them, but AI is not yet at the stage where you can simply take it out of the box and expect it to perform. AI systems require training, which is where AI models come into the equation.

An “AI model” is an algorithm that is taught using data and input from a human expert. The model is evaluated on its accuracy by comparing the results it provides against the decisions made by the human expert. This often requires the algorithm to review a significant amount of data. In addition, by accessing data from multiple sources, the model is better able to find patterns which it can use to further streamline its analysis. The model is attempting to replicate the decision process of a team of experts with access to the same data.

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Artificial Intelligence in Germany

AI in Germany

Artificial intelligence is changing the world. There is no doubt about it. Self-learning algorithms are now being developed all over the world and an increasing number of economies are focusing on promoting AI development at a domestic level. Machine learning benefits mankind all over the world – individual countries profit from it. But what is the current status of artificial intelligence in Germany? Can German AI development compete on an international level? And what about state subsidies?

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Types and Importance of AI Training Data

Types of AI Training Data

1997 was a pivotal year in the world of Artificial Intelligence (AI) as it was the first time a machine managed to defeat a world champion in chess. Deep Blue was an IBM Supercomputer and, after losing to Garry Kasparov 4-2 in 1996, had learned and improved and came back to defeat him in 1997 after a hard-fought battle.

Machine learning (ML) and AI use complicated algorithms to learn and process information. These algorithms mimic the human brain, and just like a human child learns, they can also be taught through data and experience.

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What are the benefits of artificial intelligence (AI) for the environment? – Seven astonishing insights

artificial intelligence + environment

Will AI-driven cars save the roads from a total gridlock? Can artificial intelligence help live a more resource-efficient life? Will artificial intelligence make the supply of energy easy to achieve? We provide insight into seven AI and the environment questions.

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Cognitive Computing – Hype or Progress?

Cognitive Computing

First, there was artificial intelligence, then the terms machine learning and deep learning followed. And now there is cognitive computing. What’s so special about this new concept? Is it just a new buzzword from the IT scene that can be exploited for marketing purposes? Or is it a new approach that brings machines one step closer to human thinking?

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