Across
- 2. Vision Computer Vision aims to mimic human vision by electronically perceiving and interpreting an image or a sequence of images. It is a key technology for fields like autonomous vehicles, medical imaging, and face recognition.
- 4. Has a trunk
- 6. Learning: Deep Learning is a type of machine learning that utilizes neural networks with many layers to analyze data and derive conclusions. It is especially adept at processing large amounts of unstructured data, such as images and text.
- 7. Language Processing (NLP):** NLP is a field of AI that focuses on the interaction between computers and humans through natural language. The ultimate objective is to read, decipher, understand, and make sense of human language in a valuable way.
- 8. Large marsupial
- 11. Man's best friend
- 12. Networks These are computational models inspired by the human brain. They consist of interconnected nodes or "neurons" that process information and identify patterns in data. They are the backbone of deep learning.
- 13. Likes to chase mice
- 15. Neural Networks (RNNs):** RNNs are a type of deep learning model designed to recognize patterns in sequences of data, making them particularly effective for tasks such as language modeling and speech recognition.
- 18. General Intelligence (AGI):** AGI refers to a type of artificial intelligence that has the ability to understand, learn, and apply its intelligence to any intellectual task that a human being can do.
- 19. Learning (ML) Machine Learning, a crucial subset of AI, leverages algorithms and statistical models to enable machines to improve their performance over time through experience and training. It's essentially about teaching computers to learn from data.
- 20. Intelligence (AI) AI is a subfield of computer science that aims to create systems capable of performing tasks typically requiring human intelligence. These tasks include learning, reasoning, problem-solving, perception, and language understanding.
Down
- 1. Flying mammal
- 2. Neural Networks (CNNs):** CNNs are a type of deep learning model primarily used for image processing. They have proven to be highly effective in areas such as face recognition and image and video recognition.
- 3. Unsupervised Learning involves training an AI model using data that is neither classified nor labeled, enabling the model to identify patterns and structures within the data on its own.
- 5. Learning A type of machine learning where an 'agent' learns to make decisions by taking actions in an environment to maximize some notion of cumulative reward
- 9. in AI: Bias in AI refers to situations where AI systems may systematically produce outcomes that are unfair or discriminatory, typically as a result of biases present in the training data or the design of the algorithms.
- 10. Adversarial Networks (GANs):GANs are a class of machine learning systems invented by Ian Goodfellow and his colleagues in 2014. Two neural networks contest with each other in a game, with one network (the generator) making data instances to fool the other network (the discriminator).
- 14. In Supervised Learning, an AI model is trained using labeled data. It involves the model learning to map input data to the correct output using feedback from a 'teacher'.
- 16. Extraction:** This refers to the process of transforming raw data into a set of input features that can be handled by a machine learning algorithm. This process can dramatically improve the p
- 17. Learning:** Transfer Learning is a machine learning method where a pre-trained model is adapted for a new, different data set. It's a powerful technique when there's a lack of labeled data for the task at hand.