The modern digital era, while shimmering with potential, casts shadows of doubt due to AI's profound influence on social media.…
How AI is influencing our life already and what kind of impact we could expect. Informations about and experiments.
In short by partly AI written articles and posts in my blog you can see the informations and developments about the future of AI. Articles written by/with AI are marked with a disclaimer in the footer.
With small experiments I would like to try how AI is influencing and maybe already/still helping to make our life easier. Just think back to the time when we all started to use a calculator.
I´m open for exchange with other blogger, scientists, engineers who are developing/working together with AI.
The modern digital era, while shimmering with potential, casts shadows of doubt due to AI's profound influence on social media.…
AI refers to the simulation of human intelligence in machines. It’s a branch of computer science aiming to create systems capable of performing tasks that require human-like thinking, such as visual perception, speech recognition, decision-making, and translation between languages.
While AI is a broader concept of machines being able to perform tasks in a way we consider “intelligent”, ML is a subset of AI that involves the practice of using algorithms to parse data, learn from it, and then make determinations or predictions.
AI, in itself, isn’t dangerous. However, how it’s used can pose risks. Concerns arise when considering biased algorithms, loss of jobs due to automation, or the potential misuse in military or surveillance applications. Like any tool, its safety depends on its applications and governance.
AI is expected to automate certain tasks, potentially leading to job displacement in specific sectors. However, it’s also expected to create new jobs and enhance others. The challenge is in ensuring a smooth transition, with proper training and education.
No, AI doesn’t have emotions or consciousness. It operates based on its programming and doesn’t have feelings, self-awareness, or subjective experiences.
Neural networks, inspired by the human brain’s structure, are a set of algorithms designed to recognize patterns. They interpret sensory data and are a key technology in deep learning, which is a subset of machine learning, and thus also a part of the broader AI domain.
Proposed by Alan Turing in 1950, the Turing Test is a measure of a machine’s ability to exhibit intelligent behavior indistinguishable from that of a human. If a machine can converse with a human without the human knowing they’re interacting with a machine, it passes the test.
AI has limitations such as requiring large amounts of data for training, having difficulty understanding context in natural language, being susceptible to biases present in training data, and lacking the general adaptability and common sense that humans have.
AI is used in various ways: voice assistants (like Siri or Alexa), recommendation systems (like Netflix or YouTube), email filtering, credit fraud detection, and even in autonomous vehicles.
AI algorithms themselves aren’t inherently biased, but they can reflect or amplify biases present in their training data. If the data used to train an AI system contains biases, the AI system can inherit and even exacerbate those biases.
