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A long time ago, when people built things on computers, they sometimes had a problem. They wanted to share their creations with others, but it was really hard to do because everyone's computer was different, like having different types of Lego blocks, or having a different version of NodeJS, Mongo or JS, having a different set of environment variables, or even working on different Operating systems.
So, a smart person named Solomon Hykes thought of an idea. He wanted to make it easy for people to put their creations in special boxes, like lunchboxes, so that these creations could work on any computer, no matter what Lego blocks (local configuration) it had.
That's how Docker started! It's like putting your favorite toys in special boxes so you can take them to your friend's house and play with them there. These special boxes are called "containers."
# This is a Dockerfile! It's like a recipe to make a special box for our computer toys.
# First, we need a special box to start with. We'll use a box that already has some things inside it.
FROM magic_box
# Now, we want to put our favorite toy car inside the special box.
ADD toy_car /toys/
# We also want to add some yummy snacks, like cookies, to our box.
ADD cookies /snacks/
# We can even write down a note to remind ourselves to share this box with our friends.
LABEL note="Please share with friends!"
# Finally, we'll close the box and seal it up. Now, our special box is ready!
Docker makes it super simple for people to share their computer creations with others. It's like sharing your toys with friends without worrying about them getting mixed up or broken.
So, Docker is like a magical way to keep things neat and tidy when sharing stuff between computers. It's like having special lunchboxes for your computer games and making them easy to share with friends.
Cool, right?
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- AI ethics deal with moral issues arising from Artificial Intelligence use, aiming to promote fairness and prevent bias. - Ethical use of AI fosters trust and reliability and is important in tech development. - AI poses ethical challenges, including ensuring fairness in decision-making and dealing with dilemmas, such as whether to harm a pedestrian or protect a car passenger. - Misuse of AI can infringe on privacy rights and risk job losses. Therefore, transparency and accountability are crucial. - Global bodies, like UNESCO, and corporations, like IBM, guide ethical AI use through standards and guidelines. - AI ethics impact privacy rights, jobs, and human rights. The challenge is to design AI that respects privacy while avoiding bias and erosion of livelihoods. - The future of AI ethics involves bracing for new challenges, including those concerning privacy and bridging the technology-ethics gap. - Notable AI ethics codes include Isaac Asimov's Three Laws of Robotics and the Asilomar AI Principles. - There are resources available for understanding AI ethics, developing ethical AI, and understanding the importance of ethical AI code.
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- Machine Learning's key trait is its capacity to adapt and learn based on new data through experience. - Features, or measurable traits, enable Machine Learning to learn and make predictions. - Supervised Learning, akin to studying with a tutor, allows the machine to learn from previous data and make predictions. - Unsupervised Learning allows the machine to infer patterns and relationships in data with no prior guidance. - In healthcare, Machine Learning uses features like symptoms and health indicators to aid diagnosis and treatments, enhancing patient care and accelerating drug discovery. - Feature Selection is the process of choosing most useful data for ML algorithms, enhancing their speed and accuracy. - Features in Machine Learning are categorized into numerical and categorical. Numerical features have values in a number sequence, whereas categorical features have label-type values.
