Across
- 3. computing This is effectively another way to say artificial intelligence. It’s used by marketing teams at some companies Corpus: A large dataset of written or spoken material that can be used to train a machine to perform linguistic tasks.
- 4. A collection of related data points, usually with a uniform order and tags
- 5. chaining A method where the model starts with the desired output and works in reverse to find data that might support it.
- 7. A popular programming language used for general programming.
- 8. A machine is described as autonomous if it can perform its task or tasks without needing human intervention.
- 10. learning This is a type of machine learning where structured datasets, with inputs and labels, are used to train and develop an algorithm.
- 12. learning This is a form of training where the algorithm is asked to make inferences from datasets that don’t contain labels. These inferences are what help it to learn.
- 13. learning: A function of artificial intelligence that imitates the human brain by learning from the way data is structured, rather than from an algorithm that’s programmed to do one specific thing.
- 14. language processing The umbrella term for any machine’s ability to perform conversational tasks, such as recognizing what is said to it, understanding the intended meaning and responding intelligibly.
- 16. A broad term referring to the product of AI training, created by running a machine learning algorithm on training data.
- 18. A set of rules that a machine can follow to learn how to do a task.
- 19. data The unlabeled data used to check that a machine learning model is able to perform its assigned task.
- 22. A large dataset of written or spoken material that can be used to train a machine to do a linguistic tasks. DATA mining: The process of analyzing datasets in order to discover new patterns that might improve the model.
- 23. data This refers to all of the data used during the process of training a machine learning algorithm, as well as the specific dataset used for training rather than testing.
Down
- 1. Assumptions made by a model that simplify the process of learning to do its assigned task. Most supervised machine learning models perform better with low bias, as these assumptions can negatively affect results.
- 2. annotation Tagging different search queries or products with the goal of improving the relevance of a search engine.
- 6. learning A method of teaching AI that sets a goal without specific metrics, encouraging the model to test different scenarios rather than find a single answer. Based on human feedback, the model can then manipulate the next scenario to get better results.
- 9. AI This field of research is focused on developing AI that is equal to the human mind when it comes to ability. General AI is a similar term often used interchangeably.
- 11. AI Also called narrow AI, this is a model that has a set range of skills and focuses on one particular set of tasks. Most AI currently in use is weak AI, unable to learn or perform tasks outside of its specialist skill set.
- 15. intelligence This refers to the general concept of machines acting in a way that simulates or mimics human intelligence. AI can have a variety of features, such as human-like communication or decision making.
- 17. A part of training data that identifies the desired output for that particular piece of data
- 20. test Named after Alan Turing, famed mathematician, computer scientist and logician, this tests a machine’s ability to pass for a human, particularly in the fields of language and behavior.
- 21. science Drawing from statistics, computer science and information science, this interdisciplinary field aims to use a variety of scientific methods, processes and systems to solve problems involving data.