#AI

Wondershare Filmora V15 is an improved AI video editor that brings a host of new and improved feature. Learn more about it in this read.

Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., whereas DL uses deep neural networks with multiple layers. Machine learning works well with small to medium datasets, but deep learning requires massive amounts of data.

Artificial Intelligence is a new technology so it's the best time to make money using AI tools. We have included eight different ways to earn revenue using AI tools and services. Go through our article and explore all the methods.

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn from data. Basically, AI is the goal while Machine Learning is one of the methods to reach there.

Artificial Intelligence hallucinations are false, misleading, and fabricated information generated by AI systems. AI hallucinations occur when the AI system doesn't have complete information on a topic. Smaller AI models tend to hallucinate more. Researchers say that AI models should be taught to say "I don't know" when they are uncertain to reduce hallucination.

We have curated a list of top AI humanizer tools which can turn any AI-generated text into more natural, human-like text. I tested nearly all of them and found seven tools that reliably bypass AI detectors.

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the introduction of neural networks in 1950, breakthroughs like backpropagation in 1986, powerful GPU computing in 2000s, and introduction of the Transformer architecture in 2017. There are various deep learning models such as CNNs which are used for image recognition, GANs for synthetic data generation, transformers for language models, and more.

Among the types of Artificial Intelligence technology, Narrow AI is the only AI system that exists today. From ChatGPT to self-driving cars, they can't operate beyond their domains. Artificial General Intelligence (AGI) is another type of AI, but it has not been achieved yet. It can match humans at cognitive tasks. Following that, Artificial Superintelligence is still a theoretical concept, but researchers say it can surpass the brightest human minds.

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and objects. CNNs (Convolutional Neural Networks) got popular in 2012 with the introduction of AlexNet, which identified images with human-level accuracy.

AI systems learn patterns from data rather than following explicit instructions. Neural networks process information through connected layers to detect complex patterns. Modern AI chatbots like ChatGPT predicts the next word based on statistical probability.  Unlike humans, AI systems don't know what they are saying and lacks true understanding of the world.

Agentic AI refers to AI systems that can carry out tasks for you. It can set goals, plan actions, and execute tasks autonomously. Unlike AI chatbots that generate text, images or videos, Agentic AI can decide what to do next, take action, and adapt itself based on outcomes. Agentic AI is the next evolution of Generative AI, which brings agency to AI models.

The new Wondershare UniConverter V17 update integrates many AI features. Along with video conversion, you can upscale videos to 4K/8K resolution, generate subtitles, translate videos, and more. It can also reduce processing time by up to 130x. And file output is 90% smaller, thanks to intelligent optimization. So go ahead and check out the latest Wondershare UniConverter V17.