The rapid dissemination of misinformation on the internet complicates the decision-making process for individuals seeking reliable information, particularly parents researching child development topics. This misinformation can lead to adverse consequences, such as inappropriate treatment of children based on myths. While previous research has utilized text-mining techniques to predict child abuse cases, there has been a gap in the analysis of child development myths and facts. This study addresses this gap by applying text mining techniques and classification models to distinguish between myths and facts about child development, leveraging newly gathered data from publicly available websites. The research methodology involved several stages. First, text mining techniques were employed to pre-process the data, ensuring enhanced accuracy. Subsequently, the structured data was analysed using six robust Machine Learning (ML) classifiers and one Deep Learning (DL) model, with two feature extraction techniques applied to assess their performance across three different training-testing splits. To ensure the reliability of the results, cross-validation was performed using both k-fold and leave-one-out methods. Among the classification models tested, Logistic Regression (LR) demonstrated the highest accuracy, achieving a 90% accuracy with the Bag-of-Words (BoW) feature extraction technique. LR stands out for its exceptional speed and efficiency, maintaining low testing time per statement (0.97 microseconds). These findings suggest that LR, when combined with BoW, is effective in accurately classifying child development information, thus providing a valuable tool for combating misinformation and assisting parents in making informed decisions.

Myth: There is nothing you can personally do to stop climate change. Fact: There is something you can personally do, but you didn't do it. Myth: Our children will wander tornado-swept wastes strewn with the shards of a great civilization. Fact: Typhoon-swept wastes will be more common. Myth: Earth's climate has changed naturally in the past, so modern climate change must also be a natural process.

In reality, the most popular methods for assessing the accuracy of an AI model aren't as trustworthy as you might think... You just watched The Shining and your neighborhood's seen an unusual number of burglaries in recent weeks. You're on edge, but then you remember: your new security system. It's state of the art, with a camera that promises to recognize not just strange movements but also a stranger's face, in real-time. You trust that this system will alert you if someone suspicious approaches your home, so you sleep soundly.

Will robots take over our jobs? Let's seperate popular myths from facts! In religious mythology the existence of humankind is linked to the world of gods and spirits, narratives explaining unknowns about the world. Myths claim that the truths they communicate are valid, but in reality, they are a widely held but false belief. Soon we will see narratives like the super-intelligence Skynet in the 1990s science fiction block, becoming commonplace.

This video was based on Max's book "Life 3.0", which you can find at: http://amzn.to/2iEwe6w We live in an era of self driving cars, autonomous drones, deep learning algorithms, computers that beat humans at chess and go, and so on. So it's natural to ask, will artificial superintelligence replace humans, take our jobs, and destroy human civilization? Or will AI just become tools like regular computers. AI researcher Max Tegmark helps explain the myths and facts about superintelligence, the impending machine takeover, etc. MinutePhysics is on twitter - @minutephysics And facebook - http://facebook.com/minutephysics

Ever faster processors, cheaper sensors, abundant open-source code, ubiquitous connectivity, and the advent of 3D printing are some of the forces behind the recent proliferation of robots. As I see things, these forces will only get stronger, and as more robots become part of our lives--in homes, offices, factories, hospitals, and many other places--we'll inevitably face challenges involving our adoption and use of robots. Some observers are voicing their fears about a decline in human-human interaction, while others warn of an irreversible and senseless loss of jobs, with robots taking over tasks that, they argue, should not be performed by machines (such as caring for the elderly). Trade-offs will certainly be part of our growing reliance on robotics and automation. And it will be up to us to manage these trade-offs, just as we have with other technologies such as electricity, the automobile, aviation, nuclear power, computers, and the Internet.